Online dimensional control of rolled steel profiles using projected fringes

AbstractFringe projection is a versatile method for mapping the topography of surfaces. In this paper, it is used to measure the defects on the head of railroad rails while the rails are moving. Railroad rails are made by hot rolling. The quality of the finished product is generally good, but surface texture will deteriorate with increasing temperature. A method for online inspection therefore is very desirable. In the present experiment, dimensional inspection of the railroad rails was made online while moving at a speed of 1–2 m/s. Therefore, it is important to minimize the registration time. To achieve this, we apply a method of fringe location with sub-pixel accuracy that requires only …

Investigation and reduction of losses on inverter-fed induction motors

An electric motor is more effective and flexible when supplied by a frequency converter. The frequency converter not only produces the fundamental voltage but also a set of higher harmonics which cause additional losses in the motor. Losses in the frequency converter are normally neglected in the drive dimensioning due to insufficient data available from manufacturers. Motor's losses can be reduced by increasing the switching frequency of frequency converters. An increase of the switching frequency may result in higher losses in the frequency converter. This work investigates analytically and experimentally the dependence of the losses of modern motor and frequency converter on a switching …

Hybrid Three-Phase Transformer-Based Multilevel Inverter With Reduced Component Count

The topology of the static synchronous compensator of reactive power for a low-voltage three-phase utility grid capable of asymmetric reactive power compensation in grid phases has been proposed and analysed. It is implemented using separate, independent cascaded H-bridge multilevel inverters for each phase. Every inverter includes two H-bridge cascades. The first cascade operating at grid frequency is implemented using thyristors, and the second one—operating at high frequency is based on the high-speed MOSFET transistors. The investigation shows that the proposed compensator is able to compensate the reactive power in a low-voltage three-phase grid when phases are loaded by highly asymmet…

Crash Response of a Repaired Vehicle - Influence of Welding UHSS Members

A Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore

Published version of an article in the journal: Modeling, Identification and Control. Also available from the publisher at: http://dx.doi.org/10.4173/mic.2012.2.4 Open access This paper presents a review of different approaches for Condition Based Maintenance (CBM) of induction machines and drive trains in offshore applications. The paper contains an overview of common failure modes, monitoring techniques, approaches for diagnostics, and an overview of typical maintenance actions. Although many papers have been written in this area before, this paper puts an emphasis on recent developments and limits the scope to induction machines and drive trains applied in applications located offshore.

Sensorless small wind turbine with a sliding-mode observer for water heating applications

Water heating applications consume a considerable portion of electricity demand in most of countries. Small wind turbines are one of attractive alternatives for grid electricity based water heating systems. Wind energy can be converted to heat energy in a high efficient manner. However it is essential that wind turbine based water heating systems should be economical and reliable. Maximum power point tracking algorithm of most of available wind turbines requires information from a wind speed sensor and a rotor speed sensor which reduces the reliability of the system. In this paper, the proposed 5 kW wind turbine does not require external wind speed sensors and rotor speed sensors. The syste…

Multiresolution wavelet-based approach to identification of modal parameters of a vehicle full-scale crash test

In this work estimation of vehicle modal parameters was achieved by application of a wavelet-based method. The time-frequency analysis, which comprises those techniques that study a signal in both the time and frequency domains simultaneously, using Morlet wavelet properties are applied to the measured acceleration pulse of the colliding vehicle. Determination of the ridge of the wavelet coefficients matrix makes it possible to identify the frequency components of the recorded crash pulse. Subsequently, by using the estimated natural frequency of the system, the values of damping factor for a given mode shape are assessed. In this work there are concerned both: the major frequencies of the …

Energy analysis of a non-linear dynamic impact using FEM

In the car industry, the Finite Element Method (FEM) is being more and more used to analyze the crashworthiness performance of vehicles. In order to validate the results, these impact simulations are normally compared with real crash footage and acceleration data. This paper studies the deformation- and energy output of a simple dummy model during a non-linear dynamic impact. The dummy model is crashed into an obstacle at three different velocities to observe the energy dissipated through different damping mechanisms. Furthermore, in impact simulations, material damping plays an important role in energy dissipation. However, it can be difficult to determine realistic damping parameter value…

Voltage Source Multilevel Inverters With Reduced Device Count: Topological Review and Novel Comparative Factors

Multilevel inverters (MLIs) have gained increasing interest for advanced energy-conversion systems due to their features of high-quality produced waveforms, modularity, transformerless operation, voltage, and current scalability, and fault-tolerant operation. However, these merits usually come with the cost of a high number of components. Over the past few years, proposing new MLIs with a lower component count has been one of the most active topics in power electronics. The first aim of this article is to update and summarize the recently developed multilevel topologies with a reduced component count, based on their advantages, disadvantages, construction, and specific applications. Within …

Optimization of Vehicle-to-Vehicle Frontal Crash Model Based on Measured Data Using Genetic Algorithm

In this paper, a mathematical model for vehicle-to-vehicle frontal crash is developed. The experimental data are taken from the National Highway Traffic Safety Administration. To model the crash scenario, the two vehicles are represented by two masses moving in opposite directions. The front structures of the vehicles are modeled by Kelvin elements, consisting of springs and dampers in parallel, and estimated as piecewise linear functions of displacements and velocities, respectively. To estimate and optimize the model parameters, a genetic algorithm approach is proposed. Finally, it is observed that the developed model can accurately reproduce the real kinematic results from the crash test…

Sliding-mode observer based sensor-less control of a small wind energy conversion system

Small wind turbines are becoming an attractive solution for household applications. These micro generation units can be used as standalone applications or grid connected applications. However to get the full potential benefits of these wind turbines, systems should be low cost and reliable. Introducing the wind speed and rotor speed sensors at the generator shaft may reduce the reliability of small wind turbines. In this study, a grid connected sensor-less 5 kW small wind energy conversion system has been studied. The maximum power point tracking method of the wind turbine is totally independent from wind speed and rotor speed measurements. Optimum rotor speed and actual rotor speed are est…

Autoencoders and Recurrent Neural Networks Based Algorithm for Prognosis of Bearing Life

Bearings are one of the most critical components in electric motors, gearboxes and wind turbines. Therefore, bearing fault detection and prognosis of remaining useful life are important to prevent productivity losses. In this study, a novel method is proposed for prognosis of bearing life using an autoencoder and recurrent neural networks-based prediction algorithm. Promising results have been obtained from the experimental data. A monotonic upward trend of the produced health indicator is obtained for all test cases, being one of critical indicators of a proper prognosis. The remaining useful life estimation is moderately accurate under a limited data.

Parameter Identification of a Winding Function Based Model for Fault Detection of Induction Machines

Prediction of machines' faulty parts is important in industrial applications in order to reduce productivity losses. As far as electrical machines are considered, a model-based fault diagnosis approach is usually used for this purpose. The model is derived from the modified winding function theory and hence, it requires a considerable amount of parameters at various operating conditions in order to be successfully used. However, the complete set of parameters is difficult to be obtained, as manufacturers of electric machines normally provide only the parameters that describe simple motor models (e.g. T-equivalent circuit at rated conditions). Therefore, the current work presents a method th…

Diagnostics of stator winding failures in wind turbine pitch motors using Vold-Kalman filter

Pitch systems are among the most failure-prone components in wind turbines. Winding failures in pitch motors are common due to high start-up loads and poor ventilation. This article presents a diagnostics scheme that can detect the stator winding failures in the pitch motors under time-varying speed and load conditions. The proposed approach based on three-phase motor currents can be directly integrated into the motor drive and can be used for induction as well as permanent magnet synchronous machines. The extended Park's vector calculated on the motor currents is order tracked based on the supply frequency from the drive using Vold-Kalman filter. The approach is shown to be robust under ar…

Towards farm-level health management of offshore wind farms for maintenance improvements

This paper studies a conceptual architecture for health management of offshore wind farms. To this aim, various necessary enablers of a health management sys- tem are presented to improve reliability and availability while optimizing maintenance costs. The main focus lies on improving existing condition monitoring systems based on concepts of condition-based maintenance and relia- bility centered maintenance. A brief review of the rel- evant state-of-the-art is presented and gaps to be filled towards realization of such health management system are discussed.

Mathematical models for assessment of vehicle crashworthiness: a review

This article reviews approaches to mathematical modeling of a vehicle crash. The growing focus on vehicle and occupant safety in car crashes has triggered the need to study vehicle crashworthiness in the initial stages of vehicle development. The major motivation for this work is to support vehicle crashworthiness design during the product development process.The article is divided into two parts; the first one overviews existing mathematical models used to solve engineering problems. The second part describes modeling strategies applied for replicating non-linear vehicle crash event and occupant kinematics in an occupant protection loadcase. We also highlight alternative modeling strategie…

Influence of unloading modes of spring-mass-damper models on vehicle to pole collision simulation results

Author's verion of a chapter in the book: Proceedings of the 30th Chinese Control Conference. Also available from the publisher at: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06001448 Our intention, in this brief note, is to investigate what influence the viscoelastic models' unloading properties have on models' accuracy of representing vehicle crash event. Two types of simple spring-mass-damper systems (Kelvin models) such underdamped and critically damped conditions are analyzed. Subsequently, two different unloading scenarios are specified: elastic rebound in which only the damper is an energy dissipating element and plastic collision in which the model's maximum achievable disp…

Application of viscoelastic hybrid models to vehicle crash simulation

This paper presents an application of physical models composed of springs, dampers and masses in various arrangements to simulate a real car collision with a rigid pole. Equations of motion of these systems are being established and subsequently solutions to obtain differential equations are formulated. We begin with a general model consisting of two masses, two springs and two dampers and illustrate its application to modelling fore-frame and aft-frame of a vehicle. Hybrid models, as being particular cases of two-mass–spring–damper model, are elaborated afterwards and their application to predict results of real collision is shown. Models’ parameters are obtained by fitting their response …

Effect of welding and heat treatment on the properties of UHSS used in automotive industry

This paper deals with the undesired effects of the heat treatments on the mechanical properties of (UHSS) Ultra High Strength Steel used nowadays in automotive industry to improve crashworthiness performance of vehicles. The UHSS specimens were extracted from certain parts of the car body and subjected to different heat treatments. Four types of specimens were tested: untreated, welded with metal inert gas welding, heat treated at 800 °C, and heat treated at 1250 °C. All heat-treated specimens showed dramatically reduced values of strength. The results suggest that it is important to follow the official repair manuals avoiding unnecessary welding and improper heat treatments of UHSS. The ex…

Toward farm-level health management of wind turbine systems: status and scope for improvements

An outline of health management for OWFs has been detailed in this chapter with description of various important elements. The need for such farm level management is explained and benefits are discussed. Key gaps to be filled in order to realize such a system are identified. The proposed health management system is mainly based on the existing knowledge of fleet-level management in the aerospace sector. Health management is much broader than CM; there are a number of aspects beyond the prognostics capabilities that are to be designed in order to arrive at a comprehensive maintenance management scheme. A comprehensive maintenance program that is sensitive to the health of the assets and adap…

Data-based modeling of vehicle crash using adaptive neural-fuzzy inference system

Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research. For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different…

Multiple Fault Diagnosis of Electric Powertrains Under Variable Speeds Using Convolutional Neural Networks

Electric powertrains are widely used in automotive and renewable energy industries. Reliable diagnosis for defects in the critical components such as bearings, gears and stator windings, is important to prevent failures and enhance the system reliability and power availability. Most of existing fault diagnosis methods are based on specific characteristic frequencies to single faults at constant speed operations. Once multiple faults occur in the system, such a method may not detect the faults effectively and may give false alarms. Furthermore, variable speed operations render a challenge of analysing nonstationary signals. In this work, a deep learning-based fault diagnosis method is propos…

Mathematical modeling and parameters estimation of a car crash using data-based regressive model approach

Author's version of an article in the journal: Applied Mathematical Modelling. Also available from the publisher at: http://dx.doi.org/10.1016/j.apm.2011.04.024 n this paper we present the application of regressive models to simulation of car-to-pole impacts. Three models were investigated: RARMAX, ARMAX and AR. Their suitability to estimate physical system parameters as well as to reproduce car kinematics was examined. It was found out that they not only estimate the one quantity which was used for their creation (car acceleration) but also describe the car's acceleration, velocity and crush. A virtual experiment was performed to obtain another set of data for use in further research. An A…

Patenter som innovasjonsindikatorer : Komparativ analyse av 3 ulike bransjer i 4 nordiske land i perioden 1996 til 2005

Ved bruk av patentdatabasen USPTO (US Patent & Trademark Office) som inneholder samtlige amerikanske patenter og mønsterbeskyttelser, er det utført en analyse med formål å sammenligne patenteringsaktivitet i Norge, Danmark, Sverige og Finland for følgende tre bransjer: Kuldeteknikk, Offshoreteknikk, og Telekommunikasjon. Målet med denne undersøkelsen er en studie av: • Indikatorer for teknologisk utvikling og innovasjon. • Patenter benyttet som innovasjonsindikatorer. • Patenteringsaktivitet i tre ulike bransjer/patentklasser i fire forskjellige land. Fra analysen kan følgende oppsummeres: • Bruk av Patentstatistikk, ved å telle antall patenter, benyttes for å vurdere omfanget av patenterin…

Development of lumped-parameter mathematical models for a vehicle localized impact

Published version of an article in the journal:Journal of Mechanical Science and Technology. Also available from the publisher on SpringerLink: http://dx.doi.org/10.1007/s12206-011-0505-x In this paper, we propose a method of modeling for vehicle crash systems based on viscous and elastic properties of the materials. This paper covers an influence of different arrangement of spring and damper on the models’ response. Differences in simulating vehicle-torigid barrier collision and vehicle-to-pole collision are explained. Comparison of the models obtained from wideband (unfiltered) acceleration and filtered acceleration is done. At the end we propose a model which is suitable for localized co…

RMS Based Health Indicators for Remaining Useful Lifetime Estimation of Bearings

Estimating the remaining useful life (RUL) of bearings from healthy to faulty is important for predictive maintenance. The bearing fault severity can be estimated based on the energy or root mean square (RMS) of vibration signals, and a stopping criterion can be set based on a threshold given by an ISO standard. However, the vibration RMS is often not monotonically increasing with damage, which renders a challenge for predicting the RUL. This study proposes a novel method for splitting the vibration signal into multiple frequency bands before RMS calculations to generate multiple health indicators. Monotonic health indicators are identified using the Spearman coefficient, and the RUL is aft…

Novel Three-Phase Multi-Level Inverter with Reduced Components

A new multilevel converter topology is proposed in this paper. Low component count and compact design are the main features of the proposed topology. Furthermore, the proposed converter is a capacitor-, inductor-, and diode-free configuration, allowing reducing the converter footprint, increasing the lifetime and simplifying the control strategy. Further, a comparative study is carried out to highlight the merits of the proposed circuit as compared to existing multilevel topologies. Finally, simulation results for the three-level version using different modulation strategies are presented.

A Novel Technique for Modeling Vehicle Crash using Lumped Parameter Models

This paper presents a novel technique for modeling a full frontal vehicle crash. The crash event is divided into two phases; the first until maximum crush and the second part when the vehicle starts pitching forward. This novel technique will help develop a three degrees of freedom (DOF) lumped parameter model (LPM) for crash and support in the vehicle development process. The paper also highlights the design process for reducing vehicle pitching in occupant protection load cases. The model has been validated against a finite element (FE) simulation of a full frontal crash of a Chevrolet Silverado developed by the National Highway Traffic Safety Administration (NHTSA), and the LPM shows goo…

Investigation of vehicle crash modeling techniques: theory and application

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-013-5320-3 Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this work, a brief overview of different vehicle crash modeling methodologies is proposed. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed informati…

Accelerated bearing life-Time test rig development for low speed data acquisition

Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. In the development phase, sensor data from a healthy and damaged bearing rotating at low-speed is required to verify the performance of such algorithms. A test rig for performing accelerated life-time t…

SIGNAL ANALYSIS AND PERFORMANCE EVALUATION OF A VEHICLE CRASH TEST WITH A FIXED SAFETY BARRIER BASED ON HAAR WAVELETS

Author's version of an article published in the journal: International Journal of Wavelets, Multiresolution and Information Processing. Also available from the publisher at: http://dx.doi.org/10.1142/s0219691311003979 This paper deals with the wavelet-based performance analysis of the safety barrier for use in a full-scale test. The test involves a vehicle, a Ford Fiesta, which strikes the safety barrier at a prescribed angle and speed. The vehicle speed before the collision was measured. Vehicle accelerations in three directions at the center of gravity were measured during the collision. The yaw rate was measured with a gyro meter. Using normal speed and high-speed video cameras, the beha…

New Multilevel Inverter Topology with Reduced Component Count

This paper introduces a new topology of modular multilevel inverters, being suitable in medium and high voltage applications. As compared to the existing circuits, the proposed topology has advantages of high ‘levels/components’ ratio, increasing the output voltage levels without increasing the voltage stress across the used switches, structure simplicity, isolation features, and modularity. These merits allow it to fit well in high-reliability medium-power applications, which require fast troubleshooting and maintenance flexibility. Operating principles of the proposed scheme are detailed in low frequency and pulse width modulation. Simulation and experimental results validate the effectiv…

Vehicle crashworthiness performance in frontal impact: Mathematical model using elastic pendulum

Vehicle occupant injuries due to collisions cause many fatalities every year. Safe vehicle design plays a critical role in averting serious injuries to occupants and vulnerable road users in the event of a crash. In this paper we study a full frontal vehicle crash against a rigid barrier introducing a Lumped Parameter Model (LPM) inspired by the elastic pendulum motion. The model uses polar coordinates to simplify the problem and the governing equations have been defined using Lagrangian formulation. The Simulink model has been validated against Finite Element (FE) data demonstrating good correlation with pitching angle and maximum crush of the vehicle. These parameters are crucial for desi…

Data-based modeling of vehicle collisions by nonlinear autoregressive model and feedforward neural network

Vehicle crash test is the most direct and common method to assess vehicle crashworthiness. Visual inspection and obtained measurements, such as car acceleration, are used, e.g. to examine impact severity of an occupant or to assess overall car safety. However, those experiments are complex, time-consuming, and expensive. We propose a method to reproduce car kinematics during a collision using nonlinear autoregressive (NAR) model which parameters are estimated by the use of feedforward neural network. NAR model presented in this study is derived from the more general one - nonlinear autoregressive with moving average (NARMA). Suitability of autoregressive systems for data-based modeling was …

Mathematical modeling of vehicle frontal crash by a double spring-mass-damper model

This paper presents development of a mathematical model to represent the real vehicle frontal crash scenario. The vehicle is modeled by a double spring-mass-damper system. The front mass m1 represents the chassi of the vehicle and rear mass m2 represents the passenger compartment. The physical parameters of the model (Stiffness and dampers) are estimated using Nonlinear least square method (Levenberg-Marquart algorithm) by curve fitting the response of a double spring-mass-damper system to the experimental displacement data from the real vehicle crash. The model is validated by comparing the results from the model with the experimental results from real crash tests available.

Erratum to “A fuzzy logic approach to modeling a vehicle crash test” by W. Pawlus, H. Reza, K. G. Robbersmyr

Abstract The original version of the article was published in Central European Journal of Engineering 3, 67–79 (2013), DOI: 10.2478/s13531-012-0032-2. Unfortunately, the original version of this article contains a mistake in Figure 17. Here we display the corrected version of this figure.

Cross-correlation of whitened vibration signals for low-speed bearing diagnostics

Abstract Rolling-element bearings are crucial components in all rotating machinery, and their failure will initially degrade the machine performance, and later cause complete shutdown. The period between an initial crack and complete failure is short due to crack propagation. Therefore, early fault detection is important to avoid unexpected machine shutdown and to aid in maintenance scheduling. Bearing condition monitoring has been applied for several decades to detect incipient faults at an early stage. However, low-speed conditions pose a challenge for bearing fault diagnosis due to low fault impact energy. To reliably detect bearing faults at an early stage, a new method termed Whitened …

A Data-Based Approach for Modeling and Analysis of Vehicle Collision by LPV-ARMAX Models

Published version of an article in the journal: Journal of Applied Mathematics. Also available from the publisher at: http://dx.doi.org/10.1155/2013/452391 Open Access Vehicle crash test is considered to be the most direct and common approach to assess the vehicle crashworthiness. However, it suffers from the drawbacks of high experiment cost and huge time consumption. Therefore, the establishment of a mathematical model of vehicle crash which can simplify the analysis process is significantly attractive. In this paper, we present the application of LPV-ARMAX model to simulate the car-to-pole collision with different initial impact velocities. The parameters of the LPV-ARMAX are assumed to …

Improved Quadratic Time-frequency Distributions for Detecting Inter-turn Short Circuits of PMSMs in Transient States

This paper aims to improve quadratic time-frequency distributions to adapt condition monitoring of electrical machines in transient states. Short-Time Fourier transform (STFT) has been a baseline signal processing technique for detecting fault characteristic frequencies. However, limits of window sizes due to loss of frequency- or time-resolution, make it hard to capture rapid changes in frequencies. Within this study, Choi-Williams and Wigner-Ville distributions are proposed to effectively detect peaks at characteristic frequencies while still maintaining low computation time. The improved quadratic time-frequency distributions allow for generating spectrograms of a longer lasting data sig…

EEMD based analysis of vehicle crash responses

The vehicle crash is a complex process with nonlinear large deformation of structures. The analysis of the crash process is one of the challenges for all vehicle safety researchers. In this paper, the Ensemble Empirical Mode Decomposition (EEMD) method is applied in the analysis of crash responses in order to achieve some meaningful results. With the help of EEMD, the crash responses are decomposed into a trend signal and some high frequency fluctuations. By studying the load path of vehicle design, each component is corresponding to the structure of vehicle body. Consequently, some parameters of vehicle crash model can be identified. A frontal crash of Toyota Yaris is employed for demonstr…

Oil whip-induced wear in journal bearings

Published version of an article in the journal: International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-014-5805-8 This paper investigates the effect of oil whirl and oil whip in fluid film radial bearings due to possible metallic contact. The degree of metallic contact and thereby wear and tear between rotating shafts and bearing bushes is assessed by measuring electric currents through the oil film. The current as well as the voltage varied in accordance with the contact ratio between the shaft and bush in the fluid film radial bearing. The gauge signal thus indicates the degree of metallic contact based on the thi…

Autoencoders and Data Fusion Based Hybrid Health Indicator for Detecting Bearing and Stator Winding Faults in Electric Motors

The main objective of a condition monitoring programs is to track the health status of critical components of a machine. In this paper, a hybrid health indicator is proposed to monitor the health status of bearings and stator winding of a motor. The proposed method is based on a feature learning from deep autoencoders and data fusion. The features can be learned by autoencoders using individual current and vibration signals, and then learning features are fused to make final health indicators. The experimental data from a permanent magnet synchronous motor is used to validate the proposed method. Promising results in detecting faults and severities of the stator and bearing faults at differ…

Early detection and classification of bearing faults using support vector machine algorithm

Bearings are one of the most critical elements in rotating machinery systems. Bearing faults are the main reason for failures in electrical motors and generators. Therefore, early bearing fault detection is very important to prevent critical system failures in the industry. In this paper, the support vector machine algorithm is used for early detection and classification of bearing faults. Both time and frequency domain features are used for training the support vector machine learning algorithm. The trained classier can be employed for real-time bearing fault detection and classification. By using the proposed method, the bearing faults can be detected at early stages, and the machine oper…

WAVELET-BASED ESTIMATION OF MODAL PARAMETERS OF A VEHICLE INVOLVED IN A FULL-SCALE IMPACT

In this paper, a wavelet-based approach is presented for estimation of vehicle modal parameters. The acceleration of a colliding vehicle is measured in its center of gravity — this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of a vehicle in time domain), the frequency analysis (identification of the parameters of the crash pulse in frequency domain), and the time-frequency analysis, which comprises those techniques that study a signal in both the time and frequency domains simultaneously, using Morlet wavelet properties. The frequency compone…

Towards online bearing fault detection using envelope analysis of vibration signal and decision tree classification algorithm

Online bearing fault detection is an important method for monitoring the health status of bearings in critical machines. This work proposes a classification algorithm, which can be extended towards an online bearing fault detection. The objective is to detect and classify the bearing faults in early stages. The overall design aspects of the online bearing fault detection and classification system are discussed. The proposed method is validated using experimental data, and a high accuracy of the fault classification was observed. Therefore, the proposed method can be applied for an online early fault detection and classification system.

Mathematical Modeling and Parameters Estimation of Car Crash Using Eigensystem Realization Algorithm and Curve-Fitting Approaches

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/262196 Open Access An eigensystem realization algorithm (ERA) approach for estimating the structural system matrices is proposed in this paper using the measurements of acceleration data available from the real crash test. A mathematical model that represents the real vehicle frontal crash scenario is presented. The model's structure is a double-spring-mass-damper system, whereby the front mass represents the vehicle-chassis and the rear mass represents the passenger compartment. The physical parameters of the model are estimated using cu…

Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets

Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity-this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of…

Application of Genetic Algorithm on Parameter Optimization of Three Vehicle Crash Scenarios

Abstract This paper focuses on the development of mathematical models for vehicle frontal crashes. The models under consideration are threefold: a vehicle into barrier, vehicle-occupant and vehicle to vehicle frontal crashes. The first model is represented as a simple spring-mass-damper and the second case consists of a double-spring-mass-damper system, whereby the front mass and the rear mass represent the vehicle chassis and the occupant, respectively. The third model consists of a collision of two vehicles represented by two masses moving in opposite directions. The springs and dampers in the models are nonlinear piecewise functions of displacements and velocities respectively. More spec…

Online Fault Diagnosis System for Electric Powertrains Using Advanced Signal Processing and Machine Learning

Online condition monitoring and fault diagnosis systems are necessary to prevent unexpected downtimes in critical electric powertrains. The machine learning algorithms provide a better way to diagnose faults in complex cases, such as mixed faults and/or in variable speed conditions. Most of studies focus on training phases of the machine learning algorithms, but the development of the trained machine learning algorithms for an online diagnosis system is not detailed. In this study, a complete procedure of training and implementation of an online fault diagnosis system is presented and discussed. Aspects of the development of an online fault diagnosis based on machine learning algorithms are…

Bearing fault diagnosis for inverter-fed motors via resonant filters

Current-based technique is an economic solution to detect bearing faults in drive-trains. Localized faults produce characteristic vibration frequencies. When an electric motor is supplied by a frequency-converter, the current response includes not only the fundamental and fault related frequencies but also higher harmonics from the inverter. This paper introduces a resonant filter to pick up frequency components caused by the localized faults. The bearing fault frequencies are calculated by bearing geometry and motor speeds. The filter frequencies are selected as a function of motor speeds. The filter is independent of the load condition, so it can work at different motor operating points t…

Analyse av internasjonal forretningsutvikling ved en typisk norsk lystbåtprodusent

Rapporten beskriver kartlegging av en bedrifts internasjonalisering. GrimstadBåt AS er den valgte bedrift, og er en fiktiv bedrift lokalisert på Sørlandet. I dette prosjektet har vi foretatt ”intervjuer” med de mest sentrale personene ved GrimstadBåt AS. I rapporten gir vi beskrivelse av bedriften og en analyse av bedriftens internasjonalingsstrategi.

Phase error analysis of clipped waveforms in surface topography measurement using projected fringes

Abstract When working with the method of projected fringes outside the optical laboratory one often encounters the problem of uncontrollable ambient light. This might cause saturation of the camera which in turn results in clipping of the fringes. Since standard theories describing phase-shifting techniques assume the projected fringes to be purely sinusoidal, such clipping will result in measurement error. In this paper a detailed analysis of this problem is given, and relations between phase errors, the amount of fringe clipping and the number of phase steps are found. Moreover, the phase difference between the clipped and the unclipped fringes is described. This investigation is based on…

Detecting Eccentricity and Demagnetization Fault of Permanent Magnet Synchronous Generators in Transient State

Eccentricity and demagnetization fault of a four-pole 1.5 kW surface mounted permanent-magnet synchronous-generator (PMSG) were modelled by using time-discretised finite element analysis (FEA). Both fault types are caused by magnetic asymmetry in the generator. The faulty behaviour of a PMSG under transient operating condition is studied with FEA. Two search coils were wound around stator teeth on opposite sides of the rotor. The induced voltage from these coils will be equal in healthy case. A fault is detected when the induced voltages are non-identical. The simulation results revealed that the envelope of the induced search coil voltage had sinusoids during dynamic eccentricity and demag…

Adaptive neural-fuzzy inference system based method to modeling of vehicle crash

Various areas of research need to be considered in order to establish a mathematical model of a vehicle crash. To enhance the modeling process, a novel ANFIS-based approach to reconstruct behavior of impacting vehicles is presented in this paper. Kinematics of center of gravity (COG) a vehicle involved in an oblique barrier collision is reproduced by application of a five-layered ANFIS structure. Then, the same ANFIS system is used to simulate a different collision type than the one which was used in the training stage. The points of interests are selected to be the locations of accelerometers mounting. The accuracy of the proposed method is evaluated by the comparative analysis with the re…

The harp: a vehicle crash test apparatus for full-scale crash test experiments

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-012-3960-3 The current paper describes an apparatus for full-scale vehicle crash test experimentation. This apparatus is referred to as the harp. In brief, the harp may either accelerate a trolley which is impacted into a test vehicle or the test vehicle itself may be accelerated and impacted into an object such as a barrier, a pole, or another vehicle. If a trolley is accelerated, it is equipped with load cells to record the axial crushing force. If a test vehicle is accelerated, it is equipped with a three-ax…

Identification of parameters and harmonic losses of a deep-bar induction motor

High frequency harmonics from a frequency converter causes additional losses in a deep-bar induction motor. The harmonics have their own amplitude and phase with respect to the fundamental signal, but the harmonic loss is only dependent on the amplitude of harmonics. A deep-bar induction motor can be modelled by a triple-cage circuit to take skin effect into account. The triple cage circuit having many parameters could be estimated from a small-signal model of the machine by using Differential Evolution. The correctly estimated parameters make the triple-cage circuit valid in a wide range of frequencies. However, the triple-cage circuit is very complicated which makes it difficult to model …

A Two-Stage Fault Detection and Classification Scheme for Electrical Pitch Drives in Offshore Wind Farms Using Support Vector Machine

Pitch systems are one of the components with the most frequent failure in wind turbines. This paper presents a two-stage fault detection and classification scheme for electric motor drives in wind turbine pitch systems. The presented approach is suitable for application in offshore wind farms with electric pitch systems driven by induction motors as well as permanent magnet synchronous motors. The adopted strategy utilizes three-phase motor current sensing at the pitch drives for fault detection and only when a fault condition is detected at this stage, features extracted from the current signals are transmitted to a support vector machine classifier located centrally to the wind farm. The …

Reconstruction and simulation of the vehicle to road safety barrier oblique collision based on the Levenberg–Marquardt algorithm

Vehicle crash modeling and reconstruction is an important field for research since the safety statistics from many countries show that the fatality rate of passenger vehicle occupants involved in road accidents is high. In particular, side impact are considered to be a serious problem. For this reason, in this paper, there is presented a methodology to reconstruct a given vehicle to road safety barrier oblique collision. An easy to analyze, viscoelastic model is established to represent a vehicle crash event. The reasonable modeling simplifications are assumed (namely: the vehicle is rigid and deformation of the safety barrier is negligible) which let the computational efficiency of the pro…

Reproduction of kinematics of cars involved in crash events using nonlinear autoregressive models

Vehicle crashworthiness can be assessed by the variety of methods - the most common and direct one is a vehicle crash test. Visual inspection and obtained measurements, such as car acceleration, are used to examine impact severity of an occupant and overall car safety. However, those experiments are complex, time-consuming, and expensive. We propose a method to reproduce car kinematics during a collision using a feedforward neural network to estimate the system by use of nonlinear autoregressive (NAR) models. Specifically, feasibility of applying neural networks with an NAR model to the analysis of experimental data is explored by application to measurements of a vehicle crash test. This mo…

Data-based modeling and estimation of vehicle crash processes in frontal fixed-barrier crashes

Abstract As a complex process, vehicle crash is challenging to be described and estimated mathematically. Although different mathematical models are developed, it is still difficult to balance the complexity of models and the performance of estimation. The aim of this work is to propose a novel scheme to model and estimate the processes of vehicle-barrier frontal crashes. In this work, a piecewise model structure is predefined to represent the accelerations of vehicle in frontal crashes. Each segment in the model is corresponding to the energy absorbing component in the crashworthiness structure. With the help of Ensemble Empirical Mode Decomposition (EEMD), a robust scheme is proposed for …

Development and validation of a nonlinear dynamic impact model for a notch impact

Finite element simulations are being more and more applied when studying the crash-worthiness of vehicles during impact. This paper deals with setting up such a simulation and discusses several ways to simplify and verify a simulated crash. For this purpose, a notch impact-testing machine will be released from a certain angle and crash into a model constructed with three different wall thicknesses. The plastic and elastic deformation is measured in the front of the model and is then used for validation of the simulation. In the end, the simulation was found to be in good agreement with the real crash data.

Analysis of the Relationship between Energy Absorbing Components and Vehicle Crash Response

Bearing fault detection based on time-frequency representations of vibration signals

To prevent failures of a rolling bearing in the gearbox drive system, acceleration sensors are used to detect fault-related signals of the bearing. It is a big challenge to observe and identify signals caused by bearing defects in the time domain or the frequency spectrum by a conventional Fourier analysis. The time-frequency representation of the fault-related signals implemented by the windowed Fourier transform is studied in this work. It is shown that the fault characteristic frequencies can be clearly identified in the time-frequency spectrum if a fault occurs in the bearing of the gearbox at different speeds. Otherwise, the shaft frequency and its multiples are the main harmonics in t…

Bearing fault detection for drivetrains using adaptive filters based wavelet transform

Predicting a localized defect on a rolling bearing during the degradation process before a complete failure is crucial to prevent system failures, unscheduled downtimes and substantial loss of productivity. During this process, impulses associated with the fault are weak, nonstationary or time-frequency varying, and contaminated by noises, which render the problem of extracting these impulses very difficult. This work investigates the effectiveness of common signal processing techniques on predicting incipient faults, e.g. Fast Fourier transform, Short-Time Fourier transform, Wavelet transform. It was found that an adaptive filter is required to enhance and reconstruct the signals during th…

Four-Level Three-Phase Inverter With Reduced Component Count for Low and Medium Voltage Applications

This paper proposes a novel three-phase topology with a reduced component count for low- and medium-voltage systems. It requires three bidirectional switches and twelve unidirectional switches for producing four-level voltages without using flying capacitors or clamping diodes, reducing the size, cost, and losses. Removing flying capacitors and clamping diodes allows it to simplify control algorithms and increase the reliability, efficiency, and lifetime. A modified low-frequency modulation (LFM) scheme is developed and implemented on the proposed topology to produce a staircase voltage with four steps. Further, a level-shifted pulse width modulation (LSPWM) is used to reduce the filter siz…

Analyse av utviklingsprosessen ved en typisk norsk lystbåtprodusent

Rapporten beskriver kartlegging av produktutviklingsprosessen ved en bedrift lokalisert på Sørlandet, GrimstadBåt AS (GB). Dette er et fiktivt navn på en båtprodusent lokalisert på sørlandet og rapporten baserer seg på intervjuer med bedriftens nøkkelpersoner i produktutviklingsprosessen. Det faglige grunnlaget er nedfelt i UNIC-prosjektets manual [1,2]. Rapporten vektlegger flaskehalser i utviklingsprosessen og at GB ikke legger tilstrekkelig vekt på den effektivisering av produksjon og produktutvikling (PU) som skjer hos konkurrentene Rapporten beskriver bedriften og en analyse av bedriftens produktutviklingsstrategi.

Multiple Classifiers and Data Fusion for Robust Diagnosis of Gearbox Mixed Faults

Detection and isolation of single and mixed faults in a gearbox are very important to enhance the system reliability, lifetime, and service availability. This paper proposes a hybrid learning algorithm, consisting of multilayer perceptron (MLP)- and convolutional neural network (CNN)-based classifiers, for diagnosis of gearbox mixed faults. Domain knowledge features are required to train the MLP classifier, while the CNN classifier can learn features itself, allowing to reduce the required knowledge features for the counterpart. Vibration data from an experimental setup with gearbox mixed faults is used to validate the effectiveness of the algorithms and compare them with conventional metho…

An EEMD Aided Comparison of Time Histories and Its Application in Vehicle Safety

In the context of signal processing, the comparison of time histories is required for different purposes, especially for the model validation of vehicle safety. Most of the existing metrics focus on the mathematical value only. Therefore, they suffer the measuring errors, disturbance, and uncertainties and can hardly achieve a stable result with a clear physical interpretation. This paper proposes a novel scheme of time histories comparison to be used in vehicle safety analysis. More specifically, each signal for comparison is decomposed into a trend signal and several intrinsic mode functions (IMFs) by ensemble empirical mode decomposition. The trend signals reflect the general variation a…

Mathematical modeling of a vehicle crash test based on elasto-plastic unloading scenarios of spring-mass models

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher on SpringerLink: htp://dx.doi.org/10.1007/s00170-010-3056-x This paper investigates the usability of spring which exhibit nonlinear force-deflection characteristic in the area of mathematical modeling of vehicle crash. We present a method which allows us to obtain parameters of the spring-mass model basing on the full-scale experimental data analysis. Since vehicle collision is a dynamic event, it involves such phenomena as rebound and energy dissipation. Three different spring unloading scenarios (elastic, plastic, and elasto-plastic) are covered…

A two-stage fault detection and classification for electric pitch drives in offshore wind farms using support vector machine

This article presents a two-stage fault detection and classification scheme, for induction motor drives in wind turbine pitch systems. The presented approach is suitable for application in offshore wind farms. The adopted strategy utilizes three phase motor current sensing at the pitch drives for fault detection and only when a fault is detected at this stage, features extracted from the current signals are transmitted to a central support vector machine classifier. The proposed method is validated in a laboratory setup of the pitch drive.

Mixed Fault Classification of Sensorless PMSM Drive in Dynamic Operations Based on External Stray Flux Sensors

This paper aims to classify local demagnetisation and inter-turn short-circuit (ITSC) on position sensorless permanent magnet synchronous motors (PMSM) in transient states based on external stray flux and learning classifier. Within the framework, four supervised machine learning tools were tested: ensemble decision tree (EDT), k-nearest neighbours (KNN), support vector machine (SVM), and feedforward neural network (FNN). All algorithms are trained on datasets from one operational profile but tested on other different operation profiles. Their input features or spectrograms are computed from resampled time-series data based on the estimated position of the rotor from one stray flux sensor t…

Data-driven Fault Diagnosis of Induction Motors Using a Stacked Autoencoder Network

Current signatures from an induction motor are normally used to detect anomalies in the condition of the motor based on signal processing techniques. However, false alarms might occur if using signal processing analysis alone since missing frequencies associated with faults in spectral analyses does not guarantee that a motor is fully healthy. To enhance fault diagnosis performance, this paper proposes a machinelearning based method using in-built motor currents to detect common faults in induction motors, namely inter-turn stator winding-, bearing- and broken rotor bar faults. This approach utilizes single-phase current data, being pre-processed using Welch’s method for spectral density es…

The performance investigation of viscoelastic hybrid models in vehicle crash event representation

Aurthor's version of a chapter published in the book: Proceedings of the 18th IFAC World Congress 2011. Also available from the publisher at: http://dx.doi.org/10.3182/20110828-6-IT-1002.00284

Direct Torque Control of a Small Wind Turbine with a Sliding-Mode Speed Controller

In this paper. the method of direct torque control in the presence of a sliding-mode speed controller is proposed for a small wind turbine being used in water heating applications. This concept and control system design can be expanded to grid connected or off-grid applications. Direct torque control of electrical machines has shown several advantages including very fast dynamics torque control over field-oriented control. Moreover. the torque and flux controllers in the direct torque control algorithms are based on hvsteretic controllers which are nonlinear. In the presence of a sliding-mode speed control. a nonlinear control system can be constructed which is matched for AC/DC conversion …

Data-based modeling of vehicle collision by LPV-ARMAX model approach

Vehicle crash are considered to be events with high complexity from the mathematical points of view. The high experiment cost and huge time-consumption make the establishment of a mathematical model of vehicle crash which can simplify the analysis process in great demand. In this work, we present the application of LPV-ARMAX model to simulate the car-to-pole collision with different initial impact velocities. The parameters of the LPV-ARMAX are assumed to be functions of the initial impact velocities. Instead of establishing a set of LTI models for vehicle crashes with various impact velocities, the LPV-ARMAX model is comparatively simple and applicable to predict the responses of new colli…

A state-space approach to mathematical modeling and parameters identification of vehicle frontal crash

In this paper a state-space estimation procedure that relies on the time-domain analysis of input and output signals is used for mathematical modeling of vehicle frontal crash. The model is a double-spring–mass–damper system, whereby the front mass and real mass represent the chassis and the passenger compartment, respectively. It is observed that the dynamic crash of the model is closer to the dynamic crash from experimental when the mass of the chassis is greater than the mass of the passenger compartment. The dynamic crash depends on pole placement and the estimated parameters. It is noted that when the poles of the model are closer to zero, the dynamic crash of the model is far from the…

Fuzzy logic approach to predict vehicle crash severity from acceleration data

Vehicle crash is a complex behavior to be investigated as a challenging topic in terms of dynamical modeling. On this aim, fuzzy logic can be utilized to analyze the crash dynamics rapidly and simply. In this paper, the experimental data of the frontal crash is recorded using an accelerometer located at the centre of the gravity of the vehicle. The acceleration signal was the raw data from which the collision intensity expressed by the kinetic energy and the jerk were derived. The fuzzy logic model was then developed from the two inputs namely kinetic energy and jerk. The output variable is the crash severity expressed as the dynamic crash. The result shows that the jerk contributes much to…

Deformation measurement of circular steel plates using projected fringes

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-013-5276-3 Fringe projection is a versatile method for mapping the surface topography. In this paper, it is used to measure the deformation of steel plates under static penetration. Here, the surface shape changes continuously. Therefore, it is important to minimize the registration time. To achieve this, we apply a method of fringe location with subpixel accuracy that requires only a single exposure for each registration. This is in contrast to phase shifting techniques that require at least three separate exp…

Rib-Roller Wear in Tapered Rolling Element Bearings: Analysis and Development of Test Rig for Condition Monitoring

Rolling Element Bearings (REBs) are present in virtually all machines with moving or rotating parts, and are vital for proper performance and safe operation. Condition Monitoring (CM) of bearings often receive particular interest, as this component group rarely reach design lifetime and hence is responsible for unplanned machine downtime. Unplanned maintenance can represent a large cost which motivates development of improved CM methods for implementation of advanced maintenance regimes. Based on observations of a used bearing from an offshore drilling machine, wear on roller ends in the rib-roller contact area was identified as an area of interest for future research. A test rig for creati…

Toward Self-Supervised Feature Learning for Online Diagnosis of Multiple Faults in Electric Powertrains

This article proposes a novel online fault diagnosis scheme for industrial powertrains without using historical faulty or labeled training data. The proposed method combines a one-class support vector machine (SVM) based anomaly detection and supervised convolutional neural network (CNN) algorithms to online detect multiple faults and fault severities under variable speeds and loads. The one-class SVM algorithm is to derive a score for defining faults or health classes in the first stage, and the resulting health classes are used as the training data for the CNN-based classifier in the second stage. Within this framework, the self-supervised learning of the proposed CNN algorithm allows the…

Product development and project-based learning in Mechatronics, in the context of digitization and sustainability

Engineering projects affect many of the UN’s sustainability goals. The development and design of new products and systems using a circular economy perspective is an important challenge towards a more sustainable society. Product development projects have common process characteristics, but methodologies, tools and methods differ for developing hardware (mechanical and electrical) or developing software. In Mechatronics such methods need to be combined, and product development and project-based learning is well suited for teaching and learning within Mechatronics, in addition to technical specialization subjects within both mechanical, electrical and software engineering. It is also suited f…

Projected fringes for the measurement of large aluminum ingots

The method of projected fringes is applied to the measurement of the surface topography of aluminum ingots with surface areas of several square meters. The measurements are performed inside the casting hall of an aluminum factory. To meet the challenges encountered in such a demanding environment, it is important to keep the equipment as simple and robust as possible. Therefore a method for locating the fringe positions with sub-pixel accuracy without using for example phase shifting techniques is applied. Also the nonlinearity of the phase when using divergent illumination is discussed. The developed measuring system is tested measuring eight different aluminum ingots, and the results agre…

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Abstract Large wind farms are gaining prominence due to increasing dependence on renewable energy. In order to operate these wind farms reliably and efficiently, advanced maintenance strategies such as condition based maintenance are necessary. However, wind turbines pose unique challenges in terms of irregular load patterns, intermittent operation and harsh weather conditions, which have deterring effects on life of rotating machinery. This paper reviews the state-of-the-art in the area of diagnostics and prognostics pertaining to two critical failure prone components of wind turbines, namely, low-speed bearings and planetary gearboxes. The survey evaluates those methods that are applicabl…

Modelling Demagnetized Permanent Magnet Synchronous Generators using Permeance Network Model with Variable Flux Sources

The partial demagnetization in a four-pole 1.5 kW surface mounted permanent-magnet synchronous-generator was modeled by permeance network model (PNM). The results were compared to a 2-D time-stepping finite element analysis (FEA). Both models where simulated in scenarios where one of the magnets where 20 % and 100 % demagntized and when none of the magnets where demagnetised. The results showed that the proposed PNM with variable magnetic flux sources matched the results of the FEA. The proposed method only need to invers the permeance matrix once before the time simulation, while the traditinal PNM need to invers it in every time step. This make the proposed model less computationally heav…

Novel Threshold Calculations for Remaining Useful Lifetime Estimation of Rolling Element Bearings

The prognostics objective is to avoid sudden machinery breakdowns and to estimate the remaining useful life after initial degradation. Typically, physical health indicators are derived from available sensor data, and a mathematical model is tuned to fit them. The time it takes for the model to reach a failure threshold is the estimated remaining useful life. The failure threshold may be determined from historical failure data, but that is not always readily available. ISO standard 10816–3 defines permissible velocity vibration levels for machines that may be used as a failure threshold. However, velocity vibration is not suitable for bearing prognostics due to the effect of integration from…

Autonomous Bearing Fault Diagnosis Method based on Envelope Spectrum

Abstract Rolling element bearings are one of the fundamental components of a machine, and their failure is the most frequent cause of machine breakdown. Monitoring the bearing condition is vital to preventing unexpected shutdowns and improving their maintenance planning. Specifically, the bearing vibration can be measured and analyzed to diagnose bearing faults. Accurate fault diagnosis can be achieved by analyzing the envelope spectrum of a narrowband filtered vibration signal. The optimal narrow-band is centered at the resonance frequency of the bearing. However, how to determine the optimal narrow-band is a challenge. Several methods aim to identify the optimal narrow-band, but they are …

Multi-band identification for enhancing bearing fault detection in variable speed conditions

Abstract Rolling element bearings are crucial components in rotating machinery, and avoiding unexpected breakdowns using fault detection methods is an increased demand in industry today. Variable speed conditions render a challenge for vibration-based fault diagnosis due to the non-stationary impact frequency. Computed order tracking transforms the vibration signal from time domain to the shaft-angle domain, allowing order analysis with the envelope spectrum. To enhance fault detection, the bearing resonance frequency region is isolated in the raw signal prior to order tracking. Identification of this region is not trivial but may be estimated using kurtosis-based methods reported in the li…

Health Indicator for Low-Speed Axial Bearings Using Variational Autoencoders

This paper proposes a method for calculating a health indicator (HI) for low-speed axial rolling element bearing (REB) health assessment by utilizing the latent representation obtained by variational inference using Variational Autoencoders (VAEs), trained on each speed reference in the dataset. Further, versatility is added by conditioning on the speed, extending the VAE to a conditional VAE (CVAE), thereby incorporating all speeds in a single model. Within the framework, the coefficients of autoregressive (AR) models are used as features. The dimensionality reduction inherent in the proposed method lowers the need of expert knowledge to design good condition indicators. Moreover, the sugg…

Robust Active Learning Multiple Fault Diagnosis of PMSM Drives with Sensorless Control under Dynamic Operations and Imbalanced Datasets

Authors accepted manuscript © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper proposes an active learning scheme to detect multiple faults in permanent magnet synchronous motors in dynamic operations without using historical labelled faulty training data. The proposed method combines the self-supervised anomaly detector based on a local outlier factor…

A novel soft-stall power control for a small wind turbine

In this paper, the problem of Soft-stall power control design for a small wind turbine is considered. Passive stalling and furling methods are widely used to limit the output power of small wind turbines at above-rated wind speed conditions. However, these methods have substantial limitations, for instance, related to tracking the maximum power at some wind speed levels, limited variable speed operation and introducing unbalanced forces on wind turbine blades. Soft-stall power control is a promising technique to overcome above limitations and improve the performance of small wind turbines. Small wind turbines have a comparatively low moment of inertia value, and it is possible to make fast …

Field Reconstruction for Modeling Multiple Faults in Permanent Magnet Synchronous Motors in Transient States

Conventional field reconstruction model (FRM) for electrical machines has proved its main strength in efficient computations of magnetic fields and forces in healthy permanent magnet synchronous machines (PMSM) or faulty machines in steady states. This study aims to develop a magnet library of different magnet defects and include inter-turn short-circuit (ITSC) in the FRM for PMSM. The developed FRM can model a combination fault between ITSC, and magnet defect in a PMSM in transient states. Within the framework, an 8-turn ITSC was modelled in both finite element analysis (FEA) and FRM, and then identified by the extended Park’s vector approach. The air-gap magnetic field reproduced b…

Diagnosis of inverter-fed induction motors in short time windows using physics-assisted deep learning framework

This article presents a framework for accurate fault diagnostics in inverter-fed induction machinery operating under variable speed and load conditions within very short time windows. Condition indicators based on fault characteristic frequencies observed over the extended Park's vector modulus are fused with deep features extracted using stacked autoencoders to generate a multidimensional feature space for fault classification using support vector machine. The proposed approach is demonstrated in a laboratory setup to detect the most commonly occurring faults, namely, the stator turns fault, broken rotor bars fault and bearing fault with an accuracy > 98% within a short time window of 2–3 …

A Mathematical Model for Vehicle-Occupant Frontal Crash Using Genetic Algorithm

In this paper, a mathematical model for vehicle-occupant frontal crash is developed. The developed model is represented as a double-spring-mass-damper system, whereby the front mass and the rear mass represent the vehicle chassis and the occupant, respectively. The springs and dampers in the model are nonlinear piecewise functions of displacements and velocities respectively. More specifically, a genetic algorithm (GA) approach is proposed for estimating the parameters of vehicle front structure and restraint system. Finally, it is shown that the obtained model can accurately reproduce the real crash test data taken from the National Highway Traffic Safety Administration (NHTSA). The maximu…

Current signature based fault diagnosis of field-oriented and direct torque-controlled induction motor drives

In this article, the operation of three-phase squirrel-cage induction motors is analysed under faulty conditions in closed loop with state-of-the-art controllers, namely, the field-oriented control...

Further results on mathematical models of vehicle localized impact

Accepted version of an article published by IEEE. (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works Published version:http://dx.doi.org/10.1109/ISSCAA.2010.5634041 In this paper, we propose a method of modeling for vehicle crash systems based on viscous and elastic properties of the materials. This paper covers an influence of different arrangement of spring and damper on the models? respons…

Novel Three-Phase Multilevel Inverter With Reduced Components for Low- and High-Voltage Applications

In this article, a novel multilevel topology for three-phase applications, having three-level and hybrid N -level modular configurations, enabling low-, medium-, and high-voltage operations, is presented. The proposed topology has several attractive features, namely reduced component count, being capacitor-, inductor-, and diode-free, lowering cost, control-complexity, and size, and can operate in a wide range of voltages and powers. Selected simulation and experimental results are presented to verify the performance of the proposed topology. Further, the overall efficiency of the topology and loss distribution in switches are studied. Finally, the key features of the proposed topology in t…

The performance investigation of viscoelastic hybrid models in vehicle crash event representation

Aurthor's version of a chapter published in the book: Proceedings of the 18th IFAC World Congress 2011. Also available from the publisher at: http://dx.doi.org/10.3182/20110828-6-IT-1002.00284 This paper presents application of physical models composed of springs, dampers and masses joined together in various arrangements to simulation of a real car collision with a rigid pole. Equations of motion of those systems are being established and subsequently solutions to obtained differential equations are formulated. We start with a general model consisting of two masses, two springs, and two dampers, and illustrate its application to represent fore-frame and aft-frame of a vehicle. Hybrid model…

Fault Diagnostics for Electrically Operated Pitch Systems in Offshore Wind Turbines

This paper investigates the electrically operated pitch systems of offshore wind turbines for online condition monitoring and health assessment. The current signature based fault diagnostics is developed for electrically operated pitch systems using model-based approach. The electrical motor faults are firstly modelled based on modified winding function theory and then, current signature analysis is performed to detect the faults. Further, in order to verify the fault diagnostics capabilities in realistic conditions, the operating profiles are obtained from FAST simulation of offshore wind turbines in various wind conditions. In this way, the applicability of current signature analysis for …

On Detection of Yaw and Roll Angle Information for Vehicle Oblique Crash using Hough Transform

When performing vehicle crash tests, it is common to capture high frame rate video (HFR) to observe the vehicle motion during the impact. Such videos contain a lot of information, especially when it comes to geometric data. The yaw and roll angles from the HFR video is detected by using the Hough Transform and Matlab's Image processing Toolbox. The measured Yaw angle from the HFR video are compared with real life test data captured with a gyroscopic device inside the vehicle during the oblique vehicle impact.

Prediction of Vehicle Crashworthiness Parameters Using Piecewise Lumped Parameters and Finite Element Models

Estimating the vehicle crashworthiness parameters experimentally is expensive and time consuming. For these reasons different modelling approaches are utilized to predict the vehicle behaviour and reduce the need for full-scale crash testing. The earlier numerical methods used for vehicle crashworthiness analysis were based on the use of lumped parameters models (LPM), a combination of masses and nonlinear springs interconnected in various configurations. Nowadays, the explicit nonlinear finite element analysis (FEA) is probably the most widely recognized modelling technique. Although informative, finite element models (FEM) of vehicle crash are expensive both in terms of man-hours put into…

Mathematical Modeling and Optimization of a Vehicle Crash Test based on a Single-Mass

In this paper mathematical modelling of a vehicle crash test based on a single mass is studied. The models under consideration consist of a single mass, a spring and/or a damper. They are constructed according to the measured vehicle speed before the collision and measured vehicle accelerations in three directions at the centre of gravity. A new model of nonlinear spring-mass-damper is also proposed to describe the crash. Simulation results are provided to show the effectiveness and applicability of the proposed methods.

Comparative analysis of vehicle to pole collision models established using analytical methods and neural networks

This paper presents a comparison between two modeling approaches of vehicle to pole collision. Firstly, analytical and curve fitting methods are explained and subsequently they are utilized to create lumped parameter models. Having parameters of such systems and their responses we proceed to brief description of the radial basis function neural network and its application to the linear models' coefficients' identification. Comparative analysis of the models formulated according to those two different manners is done. (6 pages)

A fuzzy logic approach to modeling a vehicle crash test

Published version of an article in the journal: Central European Journal of Engineering. Also available from the publisher at: http://dx.doi.org/10.2478/s13531-012-0032-2 This paper presents an application of fuzzy approach to vehicle crash modeling. A typical vehicle to pole collision is described and kinematics of a car involved in this type of crash event is thoroughly characterized. The basics of fuzzy set theory and modeling principles based on fuzzy logic approach are presented. In particular, exceptional attention is paid to explain the methodology of creation of a fuzzy model of a vehicle collision. Furthermore, the simulation results are presented and compared to the original vehic…