A Review: Condition Based Techniques and Predictive Maintenance for Motor
| Autor: | Aniket A. Manjare, B. G. Patil |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Electric motor
0209 industrial biotechnology Downtime Computer science Process (engineering) Context (language use) 02 engineering and technology Predictive maintenance Manufacturing engineering 020901 industrial engineering & automation Phone 0202 electrical engineering electronic engineering information engineering Key (cryptography) Revenue 020201 artificial intelligence & image processing |
| Zdroj: | 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS). |
| DOI: | 10.1109/icais50930.2021.9395903 |
| Popis: | In today's world, without an electric motor, it will be hard for us to survive. If you take an industry, every individual machine has an electric motor. A very significant portion of manufacturing processes also consists of electric motors. In technology today, everything is powered by an electric motor, and your phone has a vibration motor, too. So, without an electric motor, it's difficult to think of. A halt in any industrial process can cost revenue, and when an electric motor fails results in significant downtime, losing a larger piece of machinery. The rise of Industry 4.0 has prompted a wide usage of sensors which have encouraged assembling activities. In sectors for testing the condition state of industrial machinery, CbM and predictive maintenance (PdM) approaches have been commonly applied. There has also been a growing trend in PdM over the last few years. The current paper reviews the work done on predictive maintenance in the context of motors. Besides, it talks about the outcomes, recognizes the current research, and highlights the key contributions of the Researchers. |
| Databáze: | OpenAIRE |
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