| Issue |
ITM Web Conf.
Volume 86, 2026
5th International Conference on Current Research in Engineering and Technology (ICCRET-2026)
|
|
|---|---|---|
| Article Number | 02001 | |
| Number of page(s) | 7 | |
| Section | Data Science & Analytics | |
| DOI | https://doi.org/10.1051/itmconf/20268602001 | |
| Published online | 05 June 2026 | |
Predicting Air Compressor Performance of AC Motor Using Machine Learning Algorithm
1 Electrical and Electronics Engg, KLE Technological University Dr.M.S.Sheshgiri Campus Belagavi, Karnataka, India
2 Electrical and Electronics Engg, KLE Technological University Dr.M.S.Sheshgiri Campus Belagavi, Karnataka, India
3 Electrical and Electronics Engg, KLE Technological University Dr.M.S.Sheshgiri Campus Belagavi, Karnataka, India
4 Electrical and Electronics Engg, KLE Technological University Dr.M.S.Sheshgiri Campus Belagavi, Karnataka, India
5 Electrical and Electronics Engg, KLE Technological University Dr.M.S.Sheshgiri Campus Belagavi, Karnataka, India
6 Electrical and Electronics Engg, KLE Technological University Dr.M.S.Sheshgiri Campus Belagavi, Karnataka, India
Abstract
The theme is all about the Predictive Maintenanceand Fault Detection of AC Motor Driven Air Compressors basedon innovative machine learning algorithms. By employing theuse of Long Short-Term Memory Networks, the theme aims atpredicting performance and developing models based upon dataassociated with the usage or consumption of electric energy. TheAC motor stability and radiator performance are the most criticalaspects associated with efficiency. The use of comprehensive datapreprocessing and machine learning algorithms is utilised forsuccessfully predicting important key factors associated with aircompressors.
Key words: Predictive maintenance / Air compressor / Machinelearning / Fault detection / Radiator / Energy consumption / AC motor
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© The Authors, published by EDP Sciences, 2026
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