Search results for "Fault"

Fault Diagnostics for Electrically Operated Pitch Systems in Offshore Wind Turbines

2016

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 …

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

2018

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.

Bearing fault diagnosis for inverter-fed motors via resonant filters

2014

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…

Remote diagnosis and control of wheelchair electrical drive systems

2005

A new Diagnostic and Protective System (DPS) suitable for wheelchair electrical drive applications has been prepared. Such a system is able to perform both monitoring and long-distance transmission of key signals that are used as pre-fault and fault indicators. The system, moreover, may detect several anomalous working conditions by means of reliable diagnosis procedures and carries out actions to protect the electrical drive and to drive the disabled people in safe conditions. In particular the design, the realization and the performance analysis of the new dedicated diagnostic system, which exploits a programmable logic controller (PLC) as DRS hardware, are described and discussed. The ef…

CNN based Gearbox Fault Diagnosis and Interpretation of Learning Features

2021

Machine learning based fault diagnosis schemes have been intensively proposed to deal with faults diagnosis of rotating machineries such as gearboxes, bearings, and electric motors. However, most of the machine learning algorithms used in fault diagnosis are pattern recognition tools, which can classify given data into two or more classes. The underlined physical phenomena in fault diagnosis are not directly interpretable in machine learning schemes, thus it is usually called black/gray box models. In this study, convolutional neural networks (CNN) machine learning algorithm is proposed to classify gearbox faults, and the learning features of the CNN filters are visualized to understand the…

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

2019

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 …

Automatic detection of thermal anomalies in induction motors

2021

The paper proposes a methodology based on Artificial Intelligence techniques for the automatic detection of abnormal thermal distributions in electric motors, to rapidly identify pre-faults or fault conditions. The proposed approach, applied to induction motors of different sizes, installed in waterworks plants, is based on the execution of Thermographic Non-Destructive Tests, which allow identifying abnormal operating conditions without interrupting the ordinary working conditions of the system. Thermographic images of induction motors are acquired at the installation site and with perspectives visible to the operator, which are sometimes partially obstructed. These thermographic images ar…

Study, project and implementation of new metrics for distributed measurement system in medium voltage smart grid

2022

A set of indicators for arc faults detection based on low frequency harmonic analysis

2016

In this paper a novel set of indicators is presented for arc faults detection in electrical circuits. The indicators are defined starting from an experimental characterization of the arc fault phenomenon and the study of the arcing current in several test conditions, which were chosen in accordance with the UL 1699 Standard requirements. The proposed parameters are measured by means of a high resolution low frequency spectral analysis of the arcing current, which allows to achieve a good spectral resolution even with short observation windows.

Broken rotor bars detection via Park's vector approach based on ANFIS

2014

Many attempts have been made on fault diagnosis of induction motors based on frequency and time domain analysis of stator current. In this paper, first the Park's vector transformation and frequency analysis for fault detection of induction motors are introduced. Then a smart approach using Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed. This approach uses the time domain features derived from the Park's vector transformation of stator current. By the proposed method, a partial break including 5 mm crack on a bar, one broken bar and two broken bars using experimental data are investigated. It will be shown that features derived from Park's vector compared to features obtained fro…