Gearbox Fault Diagnosis Based on Two-Class NMF Network Under Variable Working Conditions
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42835-021-00825-2.pdf
Reference35 articles.
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2. Yu J (2019) A selective deep stacked denoising autoencoders ensemble with negative correlation learning for gearbox fault diagnosis. Comput Ind 108:62–72
3. Yang D, Liu Y, Li S et al (2015) Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm. Mech Mach Theory 219–229
4. Wang J, Cheng F, Qiao W et al (2018) Multiscale filtering reconstruction for wind turbine gearbox fault diagnosis under varying speed and noisy conditions. IEEE Trans Ind Electron 4268–4278
5. Simani S, Farsoni S, Castaldi P (2015) Fault diagnosis of a wind turbine benchmark via identified fuzzy models. IEEE Trans Ind Electron 3775–3782
Cited by 2 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. Advanced Diagnosis of Armature Winding Short-Circuit Faults in Variable Flux Reluctance Machines Using Information Fusion on Mechanical and Electrical Signals;Journal of Electrical Engineering & Technology;2023-11-26
2. A Machine Learning Approach for Gearbox System Fault Diagnosis;Entropy;2021-08-30
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