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Acoustic analysis based condition monitoring of induction motors: A review
conference contribution
posted on 2023-05-23, 15:12 authored by Nipuna Rajapaksha, Shantha Jayasinghe Arachchillage, Hossein EnshaeiHossein Enshaei, Buddhika Sembukutti VidanelageThe most common Induction Motor (IM) faults discussed in literature are of three types, namely, bearing faults, stator faults, and rotor faults. These faults often result in unexpected failures or unplanned shutdowns of IMs. A reliable condition monitoring method, however, can ensure their safe and uninterrupted operation. The acoustic signal analysis is one of the effective condition monitoring techniques used to identify incipient faults in IMs while Artificial Intelligence (AI) technology has been widely integrated with Machine Learning (ML) algorithms to automate the machinery condition monitoring process. This paper reviews application of acoustic signal analysis to detect impending failures of IMs. Moreover, time domain and frequency domain analysis techniques and features that can be derived from raw acoustic data are also discussed in detail. The paper also presents intelligent condition monitoring systems that are developed to improve fault diagnostic accuracy and recent developments in acoustic signal analysis based condition monitoring of IMs.
History
Publication title
Proceedings of the 2021 IEEE Annual Southern Power Electronics Conference (SPEC)Pagination
1-10ISBN
978-1-6654-3623-6Department/School
Australian Maritime CollegePublisher
Institute of Electrical and Electronics EngineersPlace of publication
United StatesEvent title
IEEE Annual Southern Power Electronics Conference (SPEC)Event Venue
Kigali, RwandaDate of Event (Start Date)
2021-12-06Date of Event (End Date)
2021-12-09Rights statement
Copyright 2021 IEEERepository Status
- Restricted