Motor Fault Detection and Feature Extraction Using RNN-Based Variational Autoencoder

Motor Fault Detection and Feature Extraction Using RNN-Based Variational Autoencoder

In most of the fault detection methods, the time domain signals collected from the mechanical equipment usually need to be transformed into frequency domain or other high-level data, highly relying on professional knowledge such as signal processing and fault pattern recognition. Contrary to those e...

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Bibliographic Details
Main Authors: Yang Huang, Chiun-Hsun Chen, Chi-Jui Huang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Motor fault detection
feature extraction
recurrent neural network
variational autoencoder
Online Access:https://ieeexplore.ieee.org/document/8835037/

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