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Sensors 2016, 16(11), 1887; doi:10.3390/s16111887

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier

1
School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
2
State Grid Jibei Electric Power Co., Ltd. Maintenance Branch, Beijing 102488, China
*
Author to whom correspondence should be addressed.
Academic Editor: Gangbing Song
Received: 12 August 2016 / Revised: 16 October 2016 / Accepted: 6 November 2016 / Published: 10 November 2016
(This article belongs to the Section Physical Sensors)
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Abstract

Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF6 HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods. View Full-Text
Keywords: mechanical fault diagnosis; high voltage circuit breakers; acceleration sensor; variational mode decomposition; local singular value; one-class support vector machines mechanical fault diagnosis; high voltage circuit breakers; acceleration sensor; variational mode decomposition; local singular value; one-class support vector machines
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MDPI and ACS Style

Huang, N.; Chen, H.; Cai, G.; Fang, L.; Wang, Y. Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier. Sensors 2016, 16, 1887.

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