Condition Monitoring of Induction Motors Using Wavelet Based Analysis of Vibration Signals

Jeevanand, S.; Mathew, Abraham T.

doi:10.1109/fgcns.2008.22

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Cited by 9 publications

(2 citation statements)

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“…In [59] it is used to decompose the electromagnetic torque signal and optimize the inverter control strategy. Since the WT provides good information on Current Transients, and has shown good results in the applications that have been implemented, there are several proposals to implement WT in Control systems [59][60][61][62][63][64][65][66][67].…”

Section: Control Systemmentioning

confidence: 99%

Wavelet transform to induction motor analysis: review

2018

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Section: Control Systemmentioning

confidence: 99%

Wavelet transform to induction motor analysis: review

2018

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“…This method is quick and effective however it is complex and requires a lot of computation. It is observed that combined MCSA and Wavelet technique yields the better results over FFT [9, 10]. The AI has a broad classification over these methods.…”

Section: Introductionmentioning

confidence: 99%

Cyber–physical microgrid components fault prognosis using electromagnetic sensors

Agarwal

Niknejad

Rahimnejad

et al. 2019

IET cyber-phys. syst.

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Condition monitoring of induction motor using Artificial Neural Network

Bhavsar

Patel

Bhalja

2014

2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD)

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This paper deals with stator fault detection of induction motor. Mathematical modeling of induction motor for healthy and stator fault condition are explained. In this paper Artificial Neural Network technique is applied for stator fault detection in induction motor. By collecting the simulation data from the mathematical model developed in MATLAB simulink, ANN is trained. 16 different parameters of induction motor have been taken to train the neural network. ANN gives best performance with 10 neurons in hidden layer. The results clearly show that trained neural network can precisely detect the faults before any major problem occurs.

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Condition Monitoring of Induction Motors Using Wavelet Based Analysis of Vibration Signals

Cited by 9 publications

References 7 publications

Wavelet transform to induction motor analysis: review

Wavelet transform to induction motor analysis: review

Cyber–physical microgrid components fault prognosis using electromagnetic sensors

Condition monitoring of induction motor using Artificial Neural Network

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