Comparative Analysis of MFCC and Mel-Spectrogram Features in Pump Fault Detection Using Autoencoder

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Comparative Analysis of MFCC and Mel-Spectrogram Features in Pump Fault Detection Using Autoencoder

Pump maintenance plays a pivotal role in industrial operations, where timely detection of faults is key to avoiding costly downtimes. This research explores the influence of two audio feature extraction techniques, Mel-Frequency Cepstral Coefficients (MFCC) and Mel-spectrograms, on the effectiveness...

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Bibliographic Details
Published in:	Proceedings - 2024 2nd International Conference on Computer Graphics and Image Processing, CGIP 2024
Main Author:	Bin Saharom A.S.; Ehara F.
Format:	Conference paper
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195138022&doi=10.1109%2fCGIP62525.2024.00030&partnerID=40&md5=1fc5cf69559c98b2c3ada8c7fb5819b2

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