A New Diagnostic Technique for Real-Time Diagnosis of Power Converter Faults in Switched Reluctance Motor Drives

Marques, Jorge; Estima, Jorge O.; Gameiro, Natalia S.; Cardoso, António J. Marques

doi:10.1109/tia.2013.2279898

Cited by 85 publications

(47 citation statements)

References 19 publications

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“…In [26], one extra current sensor is needed in addition to the phase current sensors to measure the dc-link current for comparison with the estimated dc-link current calculated from the phase currents, which increase the cost and complexity of the drive. In [27], the difference between the averages of the phase currents is calculated to diagnose the faults for SRM drives with four current sensors used for four phases. The diagnostic system under different control parameters is not investigated.…”

Section: Comparison Of the Proposed Fault Diagnosis Scheme With Exmentioning

confidence: 99%

“…Compared to the existing schemes in [23]- [27], and [29], the proposed fault diagnosis scheme uses only a dc-link current sensor without any additional diagnosis devices and much change to the circuitry, which will considerably reduce the volume and complexity of the motor drive. The proposed scheme is found to be more accurate and easier to implement for fault diagnosis purposes by extracting the fault coefficient from the detected current through WPD algorithm.…”

Section: Comparison Of the Proposed Fault Diagnosis Scheme With Exmentioning

confidence: 99%

“…However, one extra current sensor is also needed in addition to the phase current sensors, increasing the cost and volume of the drive. In [27], a similar diagnostic method is proposed based on the difference between the averages of the phase currents. Moreover, the supply current polar chart is used for converter faults analysis [28].…”

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confidence: 99%

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Wavelet Packet Decomposition-Based Fault Diagnosis Scheme for SRM Drives With a Single Current Sensor

Gan

Yang

et al. 2016

IEEE Trans. Energy Convers.

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Abstract-Power converters are a key, but vulnerable component in switched reluctance motor (SRM) drives. In this paper, a new fault diagnosis scheme for SRM converters is proposed based on the wavelet packet decomposition (WPD) with a dc-link current sensor. Open-and short-circuit faults of the power switches in an asymmetrical half-bridge converter are analyzed in details. In order to obtain the fault signature from the phase currents, two pulse-width modulation signals with phase shift are injected into the lower-switches of the converter to extract the excitation current, and the WPD algorithm is then applied to the detected currents for fault diagnosis. Moreover, a discrete degree of the wavelet packet node energy is chosen as the fault coefficient. The converter faults can be diagnosed and located directly by determining the changes in the discrete degree from the detected currents. The proposed scheme requires only one current sensor in the dc link, while conventional methods need one sensor for each phase or additional detection circuits. The experimental results on a 750-W three-phase SRM are presented to confirm the effectiveness of the proposed fault diagnosis scheme.Index Terms-Current sensor, discrete degree, fault diagnosis, node energy, power converter, pulse-width modulation (PWM), switched reluctance motor (SRM), wavelet packet decomposition (WPD).

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Section: Comparison Of the Proposed Fault Diagnosis Scheme With Exmentioning

confidence: 99%

Section: Comparison Of the Proposed Fault Diagnosis Scheme With Exmentioning

confidence: 99%

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Wavelet Packet Decomposition-Based Fault Diagnosis Scheme for SRM Drives With a Single Current Sensor

Gan

Yang

et al. 2016

IEEE Trans. Energy Convers.

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“…Regarding diagnostic of these open switch faults, several methods by using output currents have been proposed based on various techniques. Some of these techniques are neural network method [11,12], artificial intelligence [13], wavelet transform [14][15][16], current deviation method [17], fuzzy logic [18,19] and normalized dc current method [20,21]. In [22], induction machine faults based on time-frequency representation and feature vector size was optimized by PSO.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Three Fault Diagnostic Methods for Three Phase Inverter with Induction Motor

Asghar¹,

Talha²,

Kim³

2017

IJFIS

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In recent times, inverters are considered as the basic building block in an electrical drive system used widely in many industrial drive applications. However, the reliability of these inverters is mainly affected by the failure of power electronic switches. Various faults in inverter may influence the system operation by unexpected maintenance, which increases the cost factor and reduce overall efficiency. In this paper, comparative study of three different fault detection and diagnosis systems for three phase inverter is presented. The basic purpose of these fault detection and diagnosis systems is to detect single or multiple faults efficiently. These techniques rely on the neural network for fault detection and diagnosis by using Clarke transformed two-dimensional features extraction, three-dimensional features extraction and features extraction using discrete wavelet transform (DWT) with a different number of features in each technique. Several features are extracted using different mechanisms and used in the neural network as input for fault detection and diagnosis. Furthermore, a simulation study is carried out to analyze the fault detection and diagnosis response of these techniques. Also, a comparative study has been performed by considering fault detection time and accuracy. Comparison results prove the supremacy of three-dimensional feature extraction technique over other two techniques as it can detect and diagnose single, double and triple faults in a single cycle with high accuracy as compared to other two techniques multi-cycles detection.

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“…The relatively vulnerable parts in a SRM are stator windings, power transistors, bearings and sensors. There are a number of research works on Fault Detection and Diagnosis (FDD) of stator winding, power electronics and bearing of SRM [9][10][11][12][13] but very few publications concerning the FDD of position sensor [14]. Although it is a trend that the position sensor will be eliminated with the mature of sensor-less control technology [15][16][17][18][19], most SRGs still have position sensors in a considerable period of time.…”

Section: Introductionmentioning

confidence: 99%

A Fault Diagnostic Method for Position Sensor of Switched Reluctance Wind Generator

Wang¹,

Liu²,

Liu³

et al. 2016

Journal of Electrical Engineering and Technology

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-Fast and accurate fault diagnosis of the position sensor is of great significance to ensure the reliability as well as sensor fault tolerant operation of the Switched Reluctance Wind Generator (SRWG). This paper presents a fault diagnostic scheme for a SRWG based on the residual between the estimated rotor position and the actual output of the position sensor. Extreme Learning Machine (ELM), which could build a nonlinear mapping among flux linkage, current and rotor position, is utilized to design an assembled estimator for the rotor position detection. The data for building the ELM based assembled position estimator is derived from the magnetization curves which are obtained from Finite Element Analysis (FEA) of an SRWG with the structure of 8 stator poles and 6 rotor poles. The effectiveness and accuracy of the proposed fault diagnosis method are verified by simulation at various operating conditions. The results provide a feasible theoretical and technical basis for the effective condition monitoring and predictive maintenance of SRWG.

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A New Diagnostic Technique for Real-Time Diagnosis of Power Converter Faults in Switched Reluctance Motor Drives

Cited by 85 publications

References 19 publications

Wavelet Packet Decomposition-Based Fault Diagnosis Scheme for SRM Drives With a Single Current Sensor

Wavelet Packet Decomposition-Based Fault Diagnosis Scheme for SRM Drives With a Single Current Sensor

Comparative Study of Three Fault Diagnostic Methods for Three Phase Inverter with Induction Motor

A Fault Diagnostic Method for Position Sensor of Switched Reluctance Wind Generator

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