Fault diagnosis for high voltage circuit breaker based on Hilbert-Huang transform and support vector machine

2017 ◽  
Author(s):  
Chunguang Hou ◽  
Maoyuan Jia ◽  
Ying Han ◽  
Yundong Cao
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
High Voltage ◽  
Circuit Breaker ◽  
Support Vector ◽  
Hilbert Huang Transform ◽  
High Voltage Circuit Breaker

Research on Fault Diagnosis of High-Voltage Circuit Breaker Based on Support Vector Machine

2019 ◽  
Vol 33 (06) ◽  
pp. 1959019 ◽  
Author(s):  
Di Miao
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
High Voltage ◽  
Wavelet Packet ◽  
Circuit Breaker ◽  
Dynamic Contact ◽  
Fault System ◽  
Support Vector ◽  
High Voltage Circuit Breaker ◽  
Characteristic Value

In order to realize the diagnosis of the state of the high-voltage circuit breaker in the smart grid, the wavelet-packet technique is used to extract the characteristic value of the signal of the dynamic contact of the high-voltage circuit breaker. The characteristic value of the obtained signal is processed by fuzzy clustering, which inputs the processed feature values into the Support Vector Machine (SVM) to implement fault diagnosis. The high-voltage circuit breakers that need to be identified have the following faults: contact spring failure, trip spring shaft pinout, and trip spring failure. After the above series of processes, the paper reached the conclusion that it is feasible to use SVM to diagnose the high voltage circuit breaker fault system, which has a good diagnostic effect.

Research on Acoustic Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on Improved EEMD

2014 ◽  
Vol 687-691 ◽  
pp. 1054-1057 ◽  
Author(s):  
Xian Ping Zhao ◽  
Zhi Wan Cheng ◽  
Xiang Yu Tan ◽  
Wei Hua Niu
Keyword(s):  
Fault Diagnosis ◽  
High Voltage ◽  
Circuit Breaker ◽  
Vibration Signal ◽  
Fault Classification ◽  
Support Vector ◽  
Circuit Breakers ◽  
High Voltage Circuit Breaker ◽  
Fast Independent Component Analysis ◽  
Diagnosis Method

High voltage circuit breaker is one of the most significant devices and its health status will impact security of the power system. In this paper, the method of high voltage circuit breakers mechanical fault diagnosis is discussed, fault diagnosis method based on vibration signal is proposed. Firstly, the collected acoustic signals are proceed by blind source separation processing through fast independent component analysis. Then, the acoustic signal feature vector is extracted by improved ensemble empirical mode decomposition (EEMD) and the residual signal is filtered by fractional differential. Finally, the feature vectors are input into support vector machine (SVM) for fault diagnosis. Experiment shows that the proposed method can get more precise fault classification to high voltage circuit breakers.

scholarly journals Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Wavelet Time-Frequency Entropy and One-Class Support Vector Machine

Entropy ◽  
2015 ◽  
Vol 18 (1) ◽  
pp. 7 ◽  
Author(s):  
Nantian Huang ◽  
Huaijin Chen ◽  
Shuxin Zhang ◽  
Guowei Cai ◽  
Weiguo Li ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
High Voltage ◽  
Support Vector ◽  
Circuit Breakers ◽  
Time Frequency

scholarly journals Mechanical Fault Diagnosis for HV Circuit Breakers Based on Ensemble Empirical Mode Decomposition Energy Entropy and Support Vector Machine

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Jianfeng Zhang ◽  
Mingliang Liu ◽  
Keqi Wang ◽  
Laijun Sun
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Circuit Breaker ◽  
Vibration Signal ◽  
Ensemble Empirical Mode Decomposition ◽  
Support Vector ◽  
Time Segment ◽  
Vibration Signals ◽  
Equal Time ◽  
Mode Decomposition

During the operation process of the high voltage circuit breaker, the changes of vibration signals can reflect the machinery states of the circuit breaker. The extraction of the vibration signal feature will directly influence the accuracy and practicability of fault diagnosis. This paper presents an extraction method based on ensemble empirical mode decomposition (EEMD). Firstly, the original vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs). Secondly, calculating the envelope of each IMF and separating the envelope by equal-time segment and then forming equal-time segment energy entropy to reflect the change of vibration signal are performed. At last, the energy entropies could serve as input vectors of support vector machine (SVM) to identify the working state and fault pattern of the circuit breaker. Practical examples show that this diagnosis approach can identify effectively fault patterns of HV circuit breaker.

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