Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis-Reference-Cited by-同舟云学术

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Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis

Published:2015-11 Issue: Volume:168 Page:119-127
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Li Chuan,Sanchez René-Vinicio,Zurita Grover,Cerrada Mariela,Cabrera Diego,Vásquez Rafael E.

Funder

Prometeo Project of the Secretariat for Higher Education, Science, Technology and Innovation of the Republic of Ecuador

National Natural Science Foundation of China

Chongqing Innovation Team in University

Youth Science and Technology Talents Project of Chongqing

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference43 articles.

1. Application of wavelet energy and Shannon entropy for feature extraction in gearbox fault detection under varying speed conditions;Bafroui;Neurocomputing,2014

2. Condition monitoring and fault diagnosis of planetary gearboxes: a review;Lei;Measurement,2014

3. Multi-fault diagnosis for rotating machinery based on orthogonal supervised linear local tangent space alignment and least square support vector machine;Su;Neurocomputing,2015

4. Separation of vibration-induced signal of oil debris sensor for vibration monitoring;Li;Smart Mater. Struct.,2011

5. Fault diagnosis of rolling element bearing with intrinsic mode function of acoustic emission data using APF-KNN;Pandya;Expert Syst. Appl.,2013

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