Signal processing tools for monitoring induction drive

Raison, Bertrand; Rostaing, Gilles; Rognon, Jean-Pierre

doi:10.1109/iecon.1999.819382

Cited by 9 publications

(4 citation statements)

References 11 publications

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“…Different methods and analytical techniques are used to analyze the VSI switches fault. For example, Fast Fourier Transform (FFT) method is used to analyzed the current spectrum for characteristics of an open transistor detection [4]. Other researcher used wavelet transform for examined information about the fault signatures for fault detection and classification [5].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Open and Short-Circuit Switches Faults Voltage Source Inverter (VSI) Analysis Using Time-Frequency Distributions

Manap

Ahmad

Abdullah

et al. 2015

AMM

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Voltage source inverter (VSI) plays an important roles in electrical drive systems. Consistently, expose to hash environmental condition, the lifespan of the electronic component such as insulated-gate bipolar transistor (IGBT) may shorten and many faults related to the inverter especially switches can be occur. The present of VSI switches faults causing equipment failure and increased the cost of manufacturing process. Therefore, faults detection analysis is mandatory to identify the VSI switches faults. This paper presents the analysis of VSI switches faults using time-frequency distributions (TFDs) which are short times Fourier transform (STFT) and spectrogram. From time-frequency representation (TFR) obtained by using the TFDs, parameters of the faults signal are estimated such as instantaneous of average, root mean square (RMS), fundamental, Total Waveform Distortion (TWD), Total Harmonics Distortion (THD) and Total non-Harmonic Distortion (TnHD) of current signals. Then, based on the characteristics of the faults calculated from the signal parameters, VSI switches faults can be detected and identified. The performance of TFD for the faults analysis is also demonstrated to obtain the best TFD for switches faults detection and identification system. The results show that, STFT is the best technique to classify and identify VSI switches faults and can be implemented for automated system.

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Section: Introductionmentioning

confidence: 99%

Comparison of Open and Short-Circuit Switches Faults Voltage Source Inverter (VSI) Analysis Using Time-Frequency Distributions

Manap

Ahmad

Abdullah

et al. 2015

AMM

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“…In works [1][2][3][4][5][6][7][8][9][10][11][12][13][14] the questions of diagnostics for bearings and asynchronous motors and also mechanical units are considered. The methods of artificial intelligence [15][16][17][18][19][20] are one of modern instruments for decision-making in the field of technical diagnostics.…”

Section: Introductionmentioning

confidence: 99%

Research of Electric and Mechanical Diagnostic Parameters of Drive Equipment

Stepanov

Lagutkin

2014

AMM

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“…The breakdown of one part of a machine can stop the complete process and cause losses in terms of time and money. Therefore, it led to the implementation of monitoring systems [5][6][7][8], so as to be able, at any time, to provide information on the operating condition of the various parts of the production process, such as asynchronous machines and their load. In most situations, diagnosis is based on the analysis of mechanical signals (acceleration, speeds, etc.)…”

Section: Introductionmentioning

confidence: 99%

Detection of Bearing Damage Using Stator Current, and Voltage to Cancel Electrical Noise

Ibrahim

Bonnardot

Badaoui

et al. 2011

EURASIP J. Adv. Signal Process.

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This paper investigates the detection of a bearing defect in an asynchronous machine by analysing the electric signals. For this purpose, it is considered that the voltage is imposed and independent of mechanical aspect and that the mechanical defect appears only in the current thanks to the variation of impedance. Wiener filtering is used to extract mechanical information contained in the electrical current; this will then enable the use of statistical indicators such as kurtosis which identify the presence of a defect. Initially, the small fluctuation in electric current around the electric cycle (50 Hz) is reduced in order to reinforce cyclostationarity. Then, a filter between the voltage and current is estimated, using Wiener's technique. Since the voltage is decorrelated of mechanical elements, the residual signal (current − predicted current) contains the mechanical part. This study is corroborated by an envelope analysis of the vibration signal. Experimentation on a faulty outer raceway bearing has shown the excellent performance of the proposed method. This method is easier to implement since the sensors' position does not influence the measure the way it does when using accelerometer sensors. This diagnosis could be embedded into a fed converter. However, it is less sensitive than a direct measure of the defect (accelerometer).

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Signal processing tools for monitoring induction drive

Cited by 9 publications

References 11 publications

Comparison of Open and Short-Circuit Switches Faults Voltage Source Inverter (VSI) Analysis Using Time-Frequency Distributions

Comparison of Open and Short-Circuit Switches Faults Voltage Source Inverter (VSI) Analysis Using Time-Frequency Distributions

Research of Electric and Mechanical Diagnostic Parameters of Drive Equipment

Detection of Bearing Damage Using Stator Current, and Voltage to Cancel Electrical Noise

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