An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis

As a critical component of rotating machinery, the operating status of rolling bearings is not only related to significant economic interests but also has a far-reaching impact on social security. Hence, ensuring an effective diagnosis of faults in rolling bearings is paramount in maintaining operat...

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Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 11990 - 26
Main Authors:	Yan, Hao, Shang, Liangliang, Chen, Wan, Jiang, Mengyao, lu, Tianqi, Li, Fei
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 08.04.2025 Nature Publishing Group Nature Portfolio
Subjects:	639/166/987 639/166/988 Algorithms Aquila optimizer algorithm Classification Extreme learning machine Fault diagnosis Humanities and Social Sciences Learning algorithms multidisciplinary Rolling bearings Science Science (multidisciplinary) Stacked denoising autoencoders Fault diagnosis Extreme learning machine Stacked denoising autoencoders Rolling bearings Aquila optimizer algorithm
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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