Open-circuit Fault Diagnosis of Traction Inverter Based on Compressed Sensing Theory*

doi:10.23919/CJEE.2020.000004

Chinese Journal of Electrical Engineering ›› 2020, Vol. 6 ›› Issue (1): 52-60.doi: 10.23919/CJEE.2020.000004

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Open-circuit Fault Diagnosis of Traction Inverter Based on Compressed Sensing Theory^*

Yongqi Cheng^1,2, Weiguang Dong^1,*, Fengyang Gao¹, Guoqing Xin¹

1. School of Electrical Engineering and Automation, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730070, China

Online:2020-03-25 Published:2020-04-09
Contact: *Email: dongwg@mail.lzjtu.cn
About author:Yongqi Cheng received his bachelor's degree from Lanzhou Institute of Technology in 2017. He is now taking up his master’s degree in Electrical Engineering in Lanzhou Jiaotong University. His main research interests include compressed sensing and traction inverter fault diagnosis.
Weiguang Dong received his master's degree from Lanzhou University of Technology in 2005 and his doctor's degree from Northwest Polytechnical University in 2009. He is now an associate professor in Lanzhou Jiaotong University, majoring in the application of compressed sensing in power systems.
Fengyang Gao is a professor-level senior engineer, a master tutor, and an expert of the railway construction project bid evaluation of the National Railway Administration. He graduated from Southwest Jiaotong University with a master's degree in engineering. His main research interest includes high-power power supply.
Guoqing Xin is now taking up his master’s degree in Electrical Engineering in Lanzhou Jiaotong University. His main research directions are the extraction of subharmonic signals and early warning of faults in electrified railways.

Abstract

Abstract: This study proposes a new method of fault diagnosis based on the least squares support vector machine with gradient information (G-LS-SVM) to solve the insulated-gate bipolar transistor(IGBT) open-circuit failure problem of the traction inverter in a catenary power supply system. First, a simulation model based on traction inverter topology is built, and various voltage fault signal waveforms are simulated based on the IGBT inverter open-circuit fault classification. Second, compressive sensing theory is used to sparsely represent the voltage fault signal and make it a fault signal. The new method has a high degree of sparseness and builds an overcomplete dictionary model containing the feature vectors of voltage fault signals based on a double sparse dictionary model to match the sparse signal characteristics. Finally, the space vector transform is used to represent the three-phase voltage scalar in the traction inverter as a composite quantity to reduce the redundancy of the fault signals and data-processing capabilities. A G-LS-SVM fault diagnosis model is then built to diagnose and identify the voltage fault signal feature vector in an overcomplete dictionary. The simulation results show that the accuracy of this method for various types of IGBT tube fault diagnosis is over 98.92%. Moreover, the G-LS-SVM model is robust and not affected by Gaussian white noise.

Key words: Traction inverter, voltage fault signal, compressed sensing, over-complete dictionary, G-LS-SVM, fault diagnosis

Yongqi Cheng, Weiguang Dong, Fengyang Gao, Guoqing Xin. Open-circuit Fault Diagnosis of Traction Inverter Based on Compressed Sensing Theory^*[J]. Chinese Journal of Electrical Engineering, 2020, 6(1): 52-60.

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Open-circuit Fault Diagnosis of Traction Inverter Based on Compressed Sensing Theory^*

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