Dislocated Time Series Convolutional Neural Architecture: An Intelligent Fault Diagnosis Approach for Electric Machine

2017 ◽  
Vol 13 (3) ◽  
pp. 1310-1320 ◽  
Author(s):  
Ruonan Liu ◽  
Guotao Meng ◽  
Boyuan Yang ◽  
Chuang Sun ◽  
Xuefeng Chen
Measurement ◽  
2020 ◽  
Vol 165 ◽  
pp. 108129 ◽  
Author(s):  
Xiancheng Ji ◽  
Yan Ren ◽  
Hesheng Tang ◽  
Chong Shi ◽  
Jiawei Xiang

2014 ◽  
Vol 889-890 ◽  
pp. 929-932
Author(s):  
Zi Qian Cui ◽  
Min Qiang Xu ◽  
Ri Xin Wang

This article presents a SSDG---based intelligent fault diagnosis method. This method uses five signed threshold value modes to define nodes for carrying quantified information. This method establishes the SDGs of the system and its components, uses the based on rules method to diagnosis, then expands the diagnosing rule bank with logical operators to construct the diagnosing rule bank of the system. Applying in satellite battery system, this method can diagnosis the multiple fault, and batter explain, reworked and faster diagnosis.


2018 ◽  
Vol 8 (6) ◽  
pp. 906 ◽  
Author(s):  
Zenghui An ◽  
Shunming Li ◽  
Jinrui Wang ◽  
Weiwei Qian ◽  
Qijun Wu

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