Fault Diagnosis Method for Rotating Machinery Based on Multi-scale Features

Fault Diagnosis Method for Rotating Machinery Based on Multi-scale Features

Abstract The vibration signals of rotating machinery usually contain various natural oscillation modes, exhibiting multi-scale features. This paper proposes a Multi-Branch one-dimensional deep Convolutional Neural Network model (MBCNN) that can extract multi-scale features from raw data hierarchical...

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Bibliographic Details
Main Authors: Ruijun Liang, Wenfeng Ran, Yao Chen, Rupeng Zhu
Format: Article
Language:English
Published: SpringerOpen 2023-11-01
Series:Chinese Journal of Mechanical Engineering
Subjects:
Fault diagnosis
Multi-scale features
Convolutional neural network
Rotating machinery
Anti-noise ability
Online Access:https://doi.org/10.1186/s10033-023-00966-7

Internet

https://doi.org/10.1186/s10033-023-00966-7

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