A Self-Attention Legendre Graph Convolution Network for Rotating Machinery Fault Diagnosis

A Self-Attention Legendre Graph Convolution Network for Rotating Machinery Fault Diagnosis

Rotating machinery is widely used in modern industrial systems, and its health status can directly impact the operation of the entire system. Timely and accurate diagnosis of rotating machinery faults is crucial for ensuring production safety, reducing economic losses, and improving efficiency. Trad...

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Bibliographic Details
Main Authors: Jiancheng Ma, Jinying Huang, Siyuan Liu, Jia Luo, Licheng Jing
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:Sensors
Subjects:
graph convolutional network
fault diagnosis
rotating machinery
Legendre polynomial
graph theory
Online Access:https://www.mdpi.com/1424-8220/24/17/5475

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https://www.mdpi.com/1424-8220/24/17/5475

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