Measurement of harmonic distortion and Skewness of stator current of induction motor at crawling in Clarke plane

Chattopadhyay, Surajit; Chattopadhyay, Surajit; Sengupta, Samarjit

doi:10.1049/iet-smt.2013.0082

Cited by 12 publications

(6 citation statements)

References 33 publications

(38 reference statements)

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“…where Y¯ denotes the mean, S denotes the standard deviation, N denotes the number of data points. Kurtosis [32] is a parameter that describes the shape of a random variable's probability distribution with respect to normal condition. The datasets with high kurtosis tend to have heavy outliers and datasets with low kurtosis lack outliers.…”

Section: Statistical Parameters Under Considerationmentioning

confidence: 99%

“…Skewness [32] is a measure of the symmetry of any dataset, i.e. a dataset is symmetric, if it looks same to the left and right of the centre point.…”

Section: Parametric Analysis Of Dwt‐based Mra Coefficientsmentioning

confidence: 99%

“…Different new mathematical tools have been introduced for signal assessment [31]. Skewness of detailed and approximate coefficients of various DWT‐based decomposition levels have been found effective for signal assessment and fault diagnosis [32]. Frequency analysis of the reactive power component has been utilised to identify eccentricity faults in doubly‐fed wound rotor induction machine coupled with a closed‐loop control system [33].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Inter‐turn short‐circuit assessment of DC motor used in railway locomotive

Ray

Chattopadhyay²,

Sharma

et al. 2018

IET Electric Power Applications

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This study deals with inter-turn short-circuit assessment of DC traction motors used in railway locomotives. This has been done by analysing input current spectra of rectifier unit feeding the traction motor. The analysis includes multi-resolution analysis and discrete wavelet transform (DWT) of current spectra to calculate approximate and detailed coefficients and then to evaluate the skewness, kurtosis and root mean square values. Variation of those values with respect to percentage of inter-turn short circuit at different DWT decomposition levels has been observed. A number of curves have been chosen for fault assessment based on the observations. Deviations from normal condition have also been observed by logic matrix. Depending on the features obtained, normal and different percentages of short in the traction motor windings have been classified and an algorithm has been proposed accordingly. Case study has been carried out on Indian WAP4 locomotive, wherein the input current to the rectifiers has been analysed and efficacy of the proposed algorithm has been validated. If for the locomotives, these parameters are monitored, percentage of inter-turn short circuit in the winding may be assessed far before massive system degradation occurs.

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Section: Statistical Parameters Under Considerationmentioning

confidence: 99%

“…Skewness [32] is a measure of the symmetry of any dataset, i.e. a dataset is symmetric, if it looks same to the left and right of the centre point.…”

Section: Parametric Analysis Of Dwt‐based Mra Coefficientsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Inter‐turn short‐circuit assessment of DC motor used in railway locomotive

Ray

Chattopadhyay²,

Sharma

et al. 2018

IET Electric Power Applications

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“…For reliable operation of drives, fault diagnosis is an important aspect that should be paid attention to. A lot of study and research is going on in this field [21][22][23][24][25] for fault diagnosis of the converter and motor drives. Useful mathematical tools were presented in [22].…”

Section: Introductionmentioning

confidence: 99%

Fast Fourier transform and wavelet‐based statistical computation during fault in snubber circuit connected with robotic brushless direct current motor

Ghosh¹,

Chattopadhyay²,

Das

2022

Cognitive Comp and Systems

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The snubber circuit plays an important role in motor drives. This paper deals with the detection of the inverter switch snubber circuit resistance fault (ISSCRF) in brushless direct current (BLDC) motors used for robotic applications. This has been carried out in two parts: Fast‐Fourier‐Transform‐based analysis and wavelet‐decomposition‐based analysis on the stator current of the BLDC motor. The first analysis investigates the effects of different percentages of ISSCRF on direct current (DC) component, fundamental frequency component and total harmonic distortion percentage. Next analyses consider all of kurtosis, skewness and root‐mean‐square values of wavelet coefficients of stator current harmonic spectra. Comparative learning is made to obtain a few selective parameters best fit for the detection of ISSCRF. A fault detection algorithm to detect ISSCRF has been proposed and validated by three case studies. The algorithm is again modified with best‐fit parameters. Comparative discussion and novel contributions of the work have also been presented.

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“…Ambulatory of three-dimensional foot displacement has been measured during treadmill walking using wearable wireless ultrasonic sensor network [15]. Very recently, some new methods have been introduced for signal assessment [16] and statistical parameters like kurtosis, skewness and so on are becoming very popular for non-stationary signal analysis [17,18]. These parameters have been used for electrical signal analysis which is useful in measurement, condition monitoring, fault diagnosis and control.…”

Section: Introductionmentioning

confidence: 99%