Implementation of a Fault Diagnosis System Using Neural Networks for Solar Panel

2019 ◽  
Vol 17 (4) ◽  
pp. 1050-1058 ◽  
Author(s):  
Hye-Rin Hwang ◽  
Berm-Soo Kim ◽  
Tae-Hyun Cho ◽  
In-Soo Lee
Keyword(s):  
Neural Networks ◽  
Fault Diagnosis ◽  
Solar Panel ◽  
Diagnosis System ◽  
Fault Diagnosis System

scholarly journals Fault Diagnosis System for Machines Using Neural Networks.

2000 ◽  
Vol 43 (2) ◽  
pp. 364-371 ◽  
Author(s):  
Toshiyuki ASAKURA ◽  
Takashi KOBAYASHI ◽  
Baojie XU ◽  
Shoji HAYASHI
Keyword(s):  
Neural Networks ◽  
Fault Diagnosis ◽  
Diagnosis System ◽  
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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