Modeling Stator Winding Inter-Turn Short Circuit Faults in PMSMs including Cross Effects
Author's accepted manuscript. © 2020 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 presents a detailed analysis of stator winding inter-turn Short Circuit (ITSC) faults, taking the cross effects in the three phases of a permanent magnet synchronous motor (PMSM) into account by considering insulation degradation resistances. A PMSM with series coils in eac…
Parameters identification of induction motor dynamic model for offshore applications
The paper presents a technique to identify parameters of the LuGre dynamic friction model applied to represent mechanical losses of an induction motor. This method is based on Artificial Neural Networks (ANNs) system identification which is able to estimate parameters of nonlinear mathematical models. Within the presented approach, the network is first trained to associate model parameters with predicted friction torque, being given the reference motor speed. When this process completes, the inverse operation is performed and the network delivers estimated parameters of the model based on the reference friction torque. These parameters are then integrated with the dynamic model of the induc…
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…
Sensorless control of induction motors using an extended Kalman filter and linear quadratic tracking
Induction motors are the most commonly used prime-movers in industrial applications. Many induction motors supplied by frequency converters are coupled with a physical angular rotor position/velocity sensor which makes the drive complex and require maintenance. This paper presents a sensorless control structure to avoid using a physical angular rotor position/velocity sensor. The proposed method estimates and control the angular rotor velocity using optimal control theory. The optimal controller used in this paper is based on linear quadratic tracking and the states of the machine are estimated using an extended Kalman filter. Both the controller and the estimator utilize the same internal …
Diagnosis of Sensor Faults in PMSM and Drive System Based on Structural Analysis
This paper presents a model-based fault diagnosis method to detect sensor faults in permanent magnet synchronous motor (PMSM) drives based on structural analysis technique. The structural model is built based on the dynamic model of the PMSM in matrix form, including unknown variables, known variables, and faults. The Dulmage-Mendelsohn (DM) decomposition is applied to evaluate the redundancy of the model and obtain redundant testable sub-models. These testable redundant sub-models are used to form residuals to observe the system state, and distinguish between healthy and faulty conditions. This work investigates faults in eleven sensors in a PMSM drive, thus nine structured residuals are d…
Heat Pump Induction Motor Faults Caused by Soft Starter Topology — Case Study
This paper presents a case study of electrical machine faults, emerging in heat pump systems. In Nordic countries, heat pumps have been gaining popularity during the past years and have become one of the leading ways of heating in households and smaller public buildings. Although not a very complicated setup, the devices used are still prone to unexpected failures, especially if wrongly chosen, installed or maintained. The paper presents a study conducted on five real-life cases with very similar outcomes and failure modes. The setup of the systems is explained, faults are listed and presented, causes of the faults including modeling and measurement data are provided. The suggestions are gi…
Harmonic mitigation of a grid-connected photovoltaic system using shunt active filter
Conventional LC filters cannot compensate effectively harmonics due to non-linear loads in a grid-connected photovoltaic (PV) system. Thus, active power filters (APF) are introduced due to its characteristics and performances, for compensation of harmonics from non-linear loads in the grid-connected photovoltaic (PV) system. This work presents a three-phase voltage-fed shunt active power filter implementation to mitigate the harmonics in which the filter control system focuses on generating reference source current for compensating harmonic effects from non-linear loads. Furthermore, the developed model is verified with an experimental data from a nonlinear load.
Methods of Condition Monitoring and Fault Detection for Electrical Machines
Nowadays, electrical machines and drive systems are playing an essential role in different applications. Eventually, various failures occur in long-term continuous operation. Due to the increased influence of such devices on industry, industrial branches, as well as ordinary human life, condition monitoring and timely fault diagnostics have gained a reasonable importance. In this review article, there are studied different diagnostic techniques that can be used for algorithms’ training and realization of predictive maintenance. Benefits and drawbacks of intelligent diagnostic techniques are highlighted. The most widespread faults of electrical machines are discussed as well as techniques fo…
Signal Spectrum-Based Machine Learning Approach for Fault Prediction and Maintenance of Electrical Machines
Industrial revolution 4.0 has enabled the advent of new technological advancements, including the introduction of information technology with physical devices. The implementation of information technology in industrial applications has helped streamline industrial processes and make them more cost-efficient. This combination of information technology and physical devices gave birth to smart devices, which opened up a new research area known as the Internet of Things (IoT). This has enabled researchers to help reduce downtime and maintenance costs by applying condition monitoring on electrical machines utilizing machine learning algorithms. Although the industry is trying to move from schedu…
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 …
Detection and Discrimination of Inter-Turn Short Circuit and Demagnetization Faults in PMSMs Based on Structural Analysis
This paper presents a fault diagnosis method based on structural analysis of permanent magnet synchronous motors (PMSMs), focusing on detecting and discriminating two of the most common faults in PMSMs, namely demagnetization and inter-turn short circuit faults. The structural analysis technique uses the dynamic mathematical model of the PMSM in matrix form to evaluate the system’s structural model. After obtaining the analytical redundancy using the over-determined part of the system, it is divided into redundant testable sub-models. Four structured residuals are designed to detect and isolate the investigated faults, which are applied to the system in different time intervals. Finally, th…
Real-Time Detection of Incipient Inter-Turn Short Circuit and Sensor Faults in Permanent Magnet Synchronous Motor Drives Based on Generalized Likelihood Ratio Test and Structural Analysis.
This paper presents a robust model-based technique to detect multiple faults in permanent magnet synchronous motors (PMSMs), namely inter-turn short circuit (ITSC) and encoder faults. The proposed model is based on a structural analysis, which uses the dynamic mathematical model of a PMSM in an abc frame to evaluate the system’s structural model in matrix form. The just-determined and over-determined parts of the system are separated by a Dulmage–Mendelsohn decomposition tool. Subsequently, the analytical redundant relations obtained using the over-determined part of the system are used to form smaller redundant testable sub-models based on the number of defined fault terms. Furthermore, fo…
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.
Cascaded Multilevel Inverter-Based Asymmetric Static Synchronous Compensator of Reactive Power
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…
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...
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 …
Power Line Monitoring through Data Integrity Analysis with Q-Learning Based Data Analysis Network
To monitor and handle big data obtained from electrical, electronic, electro-mechanical, and other equipment linked to the power grid effectively and efficiently, it is important to monitor them continually to gather information on power line integrity. We propose that data transmission analysis and data collection from tools like digital power meters may be used to undertake predictive maintenance on power lines without the need for specialized hardware like power line modems and synthetic data streams. Neural network models such as deep learning may be used for power line integrity analysis systems effectively, safely, and reliably. We adopt Q-learning based data analysis network for anal…