Fault diagnosis for hydraulic system on a modified multi-sensor information fusion method

2013 ◽  
Vol 18 (1) ◽  
pp. 34 ◽  
Author(s):  
Zengshou Dong ◽  
Xujing Zhang ◽  
Jianchao Zeng
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Hydraulic System ◽  
Fusion Method ◽  
Sensor Information

Application of Multi-Sensor Information Fusion Technology in the Fault Diagnosis of Transformer

2013 ◽  
Vol 385-386 ◽  
pp. 601-604
Author(s):  
Han Min Ye ◽  
Zun Ding Xiao
Keyword(s):  
Neural Networks ◽  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
State Parameter ◽  
Accurate Diagnosis ◽  
Fusion Method ◽  
Fusion Technology ◽  
Sensor Information ◽  
Transformer Fault

The information fusion method is introduced into the transformer fault diagnosis. Through the sensor acquire transformer in operation of each state parameter, using two parallel BP neural networks to local diagnosis, with D-S evidence theory to global fuse the local diagnostic results. It realized the accurate diagnosis when transformer comes out one or a variety of faults at the same time. The experiments demonstrate that the credibility of diagnosis results are improved significantly, uncertainties are obviously reduced, which fully shows that the method is effective.

Test Points Optimal Design for Hydraulic System MSIF Fault Diagnosis

2012 ◽  
Vol 241-244 ◽  
pp. 119-124
Author(s):  
Han Qing Zhu ◽  
Zhen Shu Ma ◽  
Hua Gong Sun
Keyword(s):  
Fault Diagnosis ◽  
Optimal Design ◽  
Directed Graph ◽  
Information Fusion ◽  
Information Entropy ◽  
Information Acquisition ◽  
Hydraulic System ◽  
Dependency Matrix ◽  
Sensor Information ◽  
Test Points

An intelligent method based on multi-sensor information fusion is put forward to resolve the problem lay in hydraulic system fault diagnosis. Determining how to choose sensors used for information acquisition is the main objective. Test signal directed graph and dependency matrix model are established to realize optimal design oriented by the maximum failure information entropy.

Fault Classification of Hydroelectric Generating Unit Based on Improved Evidence Theory

2014 ◽  
Vol 7 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Jiatang Cheng ◽  
Li Ai ◽  
Zhimei Duan ◽  
Yan Xiong
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fault Classification ◽  
Fusion Method ◽  
Inconsistent Result ◽  
High Conflict

Aiming at the problem of the conventional vibration fault diagnosis technology with inconsistent result of a hydroelectric generating unit, an information fusion method was proposed based on the improved evidence theory. In this algorithm, the original evidence was amended by the credibility factor, and then the synthesis rule of standard evidence theory was utilized to carry out information fusion. The results show that the proposed method can obtain any definitive conclusion even if there is high conflict evidence in the synthesis evidence process, and may avoid the divergent phenomenon when the consistent evidence is fused, and is suitable for the fault classification of hydroelectric generating unit.

scholarly journals Fault Diagnosis of Bearings Based on Multi-Sensor Information Fusion and 2D Convolutional Neural Network

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 23717-23725
Author(s):  
Jiaxing Wang ◽  
Dazhi Wang ◽  
Sihan Wang ◽  
Wenhui Li ◽  
Keling Song
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
Information Fusion ◽  
Sensor Information

scholarly journals Application of Multi-sensor Information Fusion Technology on Fault Diagnosis of Electrical System

2017 ◽  
Vol 11 ◽  
pp. 05003
Author(s):  
Ling-Wen Meng ◽  
Ji-Pu Gao ◽  
Ming-Yong Xin ◽  
Jin-Mei Xiong ◽  
Guo Rui
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Fusion Technology ◽  
Electrical System ◽  
Sensor Information
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