Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter |
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Affiliation: | 1. Shanghai Maritime University, China;2. Ecole polytechnique Université de Nantes, L?Institut d?Electronique et de Télécommunications de Rennes, UMR CNRS 6164, France;1. College of Electrical Engineering, Henan University of Technology, Zhengzhou 450001, PR China;2. College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, PR China;3. Huazhong University of Science and Technology, Wuhan 430074, PR China;1. Department of Electrical Engineering, Northwestern Polytechnical University, Xi’an 710072, China;2. State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an, China;1. FCLAB (Fuel Cell Lab) Research Federation, FR CNRS 3539, rue Thierry Mieg, 90010 Belfort Cedex, France;2. FEMTO-ST (UMR CNRS 6174), ENERGY Department, UFC/UTBM/ENSMM, France;3. Laboratoire des Sciences de l’Information et des Systemes (LSIS), University of Aix-Marseille, France;4. CEA/LIST, 91191 Gif-sur-Yvette Cedex, France;5. CEA/LITEN, 38054 Grenoble, France |
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Abstract: | Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. |
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Keywords: | Fault diagnosis Fast Fourier Transform Relative principal component analysis Support Vector Machine Cascaded-Multilevel Inverter Wind turbine |
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