Condition monitoring and fault detection of induction motor based on wavelet denoising with ensemble learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-022-01523-6.pdf
Reference43 articles.
1. Mayadevi N, Mini VP, Kumar RH, Prins S (2020) Fuzzy-based intelligent algorithm for diagnosis of drive faults in induction motor drive system. Arab J Sci Eng 45(3):1385–1395
2. Almounajjed A, Ashwin KS, Mani KK, Muhannad A (2021) Investigation techniques for rolling bearing fault diagnosis using machine learning algorithms. In: 2021 5th international conference on intelligent computing and control systems (ICICCS). IEEE, pp 1290–1294
3. Almounajjed A, Ashwin KS, Mani KK, Mhamad WB (2021) Condition monitoring and fault diagnosis of induction motor-an experimental analysis. In: 2021 7th international conference on electrical energy systems (ICEES). IEEE, pp 433–438
4. Aghazadeh F, Tahan A, Thomas M (2018) Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process. Int J Adv Manuf Technol 98(9–12):3217–3227
5. Almounajjed A, Sahoo AK, Kumar MK (2021) Diagnosis of stator fault severity in induction motor based on discrete wavelet analysis. Measurement 109780
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