Research on diagnosis algorithm of mechanical equipment brake friction fault based on MCNN-SVM-Reference-Cited by-同舟云学术

Research on diagnosis algorithm of mechanical equipment brake friction fault based on MCNN-SVM

Published:2021-12 Issue: Volume:186 Page:110065
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Zhang Xunjie,Zhang Min,Xiang Zaiyu,Mo Jiliang

Funder

Sichuan Province Science and Technology Support Program

China Postdoctoral Science Foundation

Southwest Jiaotong University

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference48 articles.

1. Braking pad-disc system: wear mechanisms and formation of wear fragments;Verma;Wear,2015

2. An investigation into the failure mechanism of severe abrasion of high-speed train brake discs on snowy days;Wu;Eng. Fail. Anal.,2019

3. Multidimensional feature fusion and ensemble learning-based fault diagnosis for the braking system of heavy-haul train;Liu;IEEE Trans. Ind. Inf.,2021

4. Brake fault diagnosis using clonal selection classification algorithm (CSCA)–a statistical learning approach;Jegadeeshwaran;Eng. Sci. Technol. Int. J.,2015

5. A SVM framework for fault detection of the braking system in a high speed train;Liu;Mech. Syst. Sig. Process.,2017

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