Dynamic fault diagnosis on reconfigurable hardware

2003 ◽  
Author(s):  
F. Kocan ◽  
D.G. Saab
Keyword(s):  
Fault Diagnosis ◽  
Reconfigurable Hardware ◽  
Dynamic Fault Diagnosis

scholarly journals Optimization of a Dynamic Fault Diagnosis Model Based on Machine Learning

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 65065-65077 ◽  
Author(s):  
Shigang Zhang ◽  
Xu Luo ◽  
Yongmin Yang ◽  
Long Wang ◽  
Xiaofei Zhang
Keyword(s):  
Machine Learning ◽  
Fault Diagnosis ◽  
Model Based ◽  
Diagnosis Model ◽  
Dynamic Fault Diagnosis

scholarly journals A Dynamic Integrated Fault Diagnosis Method for Power Transformers

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Wensheng Gao ◽  
Cuifen Bai ◽  
Tong Liu
Keyword(s):  
Fault Diagnosis ◽  
Working Conditions ◽  
Failure Modes ◽  
Selection Process ◽  
Power Transformers ◽  
Diagnosis Method ◽  
One Step ◽  
Diagnosis Model ◽  
Transformer Fault ◽  
Dynamic Fault Diagnosis

In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified.

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