A Fractional Steepest Ascent Morlet Wavelet Transform-based Transient Fault Diagnosis Method for Traction Drive Control System

2020 ◽  
pp. 1-1
Author(s):  
Chao Yang ◽  
Zhiliang Wu ◽  
Tao Peng ◽  
Hongqiu Zhu ◽  
Chunhua Yang
Keyword(s):  
Control System ◽  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Morlet Wavelet ◽  
Transient Fault ◽  
Traction Drive ◽  
Steepest Ascent ◽  
Drive Control ◽  
Diagnosis Method ◽  
Morlet Wavelet Transform

scholarly journals Adaptive Reinforced Empirical Morlet Wavelet Transform and Its Application in Fault Diagnosis of Rotating Machinery

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 65150-65162 ◽  
Author(s):  
Yu Xin ◽  
Shunming Li ◽  
Zongzhen Zhang ◽  
Zenghui An ◽  
Jinrui Wang
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Morlet Wavelet ◽  
Rotating Machinery ◽  
Morlet Wavelet Transform

339 Morlet wavelet transform in EEG during perceptuo-motor tasks

1998 ◽  
Vol 30 (1-2) ◽  
pp. 131-132
Author(s):  
S. Slobounovl ◽  
R. Tutwiler ◽  
E. Slobounova
Keyword(s):  
Wavelet Transform ◽  
Morlet Wavelet ◽  
Motor Tasks ◽  
Morlet Wavelet Transform

scholarly journals Synthesis of the asynchronous traction drive control system by the ACOR method

2017 ◽  
Vol 1 (1) ◽  
pp. 11-15
Author(s):  
Valentin Noskov ◽  
Maksym Lipchanskyi ◽  
Gennadij Gejko
Keyword(s):  
Control System ◽  
Traction Drive ◽  
Drive Control

The Application of Improved SVM in Mixed Circuit

2012 ◽  
Vol 224 ◽  
pp. 493-496 ◽  
Author(s):  
Huai Long Wang ◽  
Qiang Pan ◽  
Hong Liu
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Small Samples ◽  
Lifting Wavelet Transform ◽  
Fault Features ◽  
Diagnosis Method ◽  
Lifting Wavelet ◽  
Current Characteristics ◽  
Mixed Circuit ◽  
Better Than

In order to improve the speed and the rate of fault diagnosis in mixed circuit, this paper introduces a new fault diagnosis method. Through extracting fault features of current characteristics effectively and applying to Improved SVM, the ability of pattern recognition will be better than the traditional BP Neural Network and Single SVM, especially in small samples or non-linear cases. Meanwhile, this paper presents the lifting wavelet transform in order to obtain the feature information accurately. The accuracy of fault diagnosis can greatly enhance by discussing the Improved SVM combined with lifting wavelet transform in a specific monostable trigger. That points out a new direction for the fault diagnosis of mixed circuit.

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