Fault Diagnosis of Rolling Bearing Based on Improved Sparrow Search Algorithm Optimized LSTM

In order to precisely diagnose the operational status and fault categories of rolling bearings, this paper employs a long short-term memory (LSTM) neural network as a classifier to categorize and diagnose the rolling bearing dataset. Initially, time-domain and frequency-domain characteristic paramet...

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Bibliografiske detaljer

Principais autores:	Yu ZHOU, Qian FANG, Zexuan PEI, Lei BAI
Format:	Artigo
Sprog:	Inglês
Udgivet:	Editorial Department of Journal of Sichuan University (Engineering Science Edition) 2024-03-01
Serier:	工程科学与技术
Fag:	sparrow search algorithm fault diagnosis long short-term memory neural network feature extraction rolling bearing
Online adgang:	http://jsuese.scu.edu.cn/thesisDetails#10.15961/j.jsuese.202200709
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