Bearing fault diagnosis in high noise environment using multi-scale processing, channel-attention and feature-enhanced convolutional neural network model

• Main Authors: Xiuyu, Li, Shirley Johnathan, Tanjong
• Format: Article
• Language: English
• Published: Learning Gate 2025
• Subjects: T Technology (General); TJ Mechanical engineering and machinery
• Online Access: http://ir.unimas.my/id/eprint/47773/1/3601-EAST20259%282%292132-2146.pdf; http://ir.unimas.my/id/eprint/47773/; https://learning-gate.com/index.php/2576-8484/article/view/5050; https://doi.org/10.55214/25768484.v9i2.5050

This paper presents a model using deep learning techniques which includes Multi-scale processing, Channel attention, Feature enhancement, and anomaly Classification layers, referred to as MCFCNN, for bearing fault diagnosis in noisy industrial environments. The MCFCNN network combines multi-channel...