IFDS: An Intelligent Fault Diagnosis System with Multi-source Unsupervised Domain Adaptation for Different Working Conditions

2021 ◽  
pp. 1-1
Author(s):  
Danya Xu ◽  
Yibin Li ◽  
Yan Song ◽  
Lei Jia ◽  
Yanjun Liu
Keyword(s):  
Fault Diagnosis ◽  
Working Conditions ◽  
Domain Adaptation ◽  
Intelligent Fault Diagnosis ◽  
Diagnosis System ◽  
Unsupervised Domain Adaptation ◽  
Fault Diagnosis System

Design and Analysis of Fault Diagnosis System of Electrohydraulic Servo Valve Based on ANN

2013 ◽  
Vol 785-786 ◽  
pp. 1380-1383
Author(s):  
Yao Li ◽  
Jian Gang Yi
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Fault Diagnosis ◽  
Servo System ◽  
Intelligent Fault Diagnosis ◽  
Diagnosis System ◽  
Servo Valve ◽  
Pressure Characteristic ◽  
Fault Diagnosis System ◽  
Electrohydraulic Servo System

It is a difficulty to combine artificial neural networks (ANN) with the fault diagnosis of electrohydraulic servo valve. To slolve this problem, the fault diagnosis mechanism of electrohydraulic servo system is analysed, the effecitveness of fault diagnosis based on ANN is verified, and the pressure characteristic data are used to construct ANN samples. Finally, the algorithms of RBF, BP and Elman are compared with the built system and sampled. The results show the RBF algorithm is more rapid and accurate and the proposed intelligent fault diagnosis system of electrohydraulic servo valve is valuable.

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