A Compact Convolutional Neural Network Augmented with Multiscale Feature Extraction of Acquired Monitoring Data for Mechanical Intelligent Fault Diagnosis-Reference-Cited by-同舟云学术

A Compact Convolutional Neural Network Augmented with Multiscale Feature Extraction of Acquired Monitoring Data for Mechanical Intelligent Fault Diagnosis

Published:2020-04 Issue: Volume:55 Page:273-284
ISSN:0278-6125
Container-title:Journal of Manufacturing Systems
language:en
Short-container-title:Journal of Manufacturing Systems

Author:

Zhang Kaiyu,Chen Jinglong,Zhang Tianci,Zhou Zitong

Funder

National Natural Science Foundation of China

Major Research Plan of the National Natural Science Foundation of China

National Natural Science Foundation of China - Civil Aviation Joint Research Fund of China Civil Aviation Administration

China Postdoctoral Science Foundation

Shaanxi Natural Science Foundation

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Hardware and Architecture,Software,Control and Systems Engineering

Reference45 articles.

1. Bearing remaining useful life prediction based on deep autoencoder and deep neural networks;Ren;J. Manuf. Syst.,2018

2. Online detection of bearing incipient fault with semi-supervised architecture and deep feature representation;Mao;J. Manuf. Syst.,2020

3. A novel method to classify bearing faults by integrating standard deviation to refined composite multi-scale fuzzy entropy;Minhas;Meas. J. Int. Meas. Confed.,2020

4. Generalized demodulation with tunable E-Factor for rolling bearing diagnosis under time-varying rotational speed;Liu;J. Sound Vib.,2018

5. Multi-bearing remaining useful life collaborative prediction: A deep learning approach;Ren;J. Manuf. Syst.,2017

Cited by 76 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Lightweight pyramid attention residual network for intelligent fault diagnosis of machine under sharp speed variation;Mechanical Systems and Signal Processing;2025-01

2. Research on tool remaining useful life prediction algorithm based on machine learning;Engineering Research Express;2024-07-11

3. Wavelet-driven differentiable architecture search for planetary gear fault diagnosis;Journal of Manufacturing Systems;2024-06

4. Insights into airborne particulate matter: artificial intelligence-driven PM2.5 modelling in Hyderabad district, India;Stochastic Environmental Research and Risk Assessment;2024-05-09

5. Fault Diagnosis Method of Box-Type Substation Based on Improved Conditional Tabular Generative Adversarial Network and AlexNet;Applied Sciences;2024-04-08