Research on fault prediction method of power electronic circuits based on least squares support vector machine

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1 ELECTRI C MACHINES AND CONTROL Vol. 15 No. 8 Aug LS-SVM least squares support vector machine LS-SVM Buck LS-SVM LS-SVM 2% TP 206 A X Research on fault prediction method of power electronic circuits based on least squares support vector machine JIANG Yuan-yuan 1 2 WANG You-ren 1 CUI Jiang 1 SUN Feng-yan 1 1. College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China 2. College of Electric and Information Engineering Anhui University of Science and Technology Huainan China Abstract Aiming at the issue of fault prediction technique of power electronic circuits a method based on characteristic parameter data and least squares support vector machine LS-SVM for the prediction of power electronic circuits was proposed. Taking the Buck converter circuit as an example the fault prediction of power electronic circuits was achieved. Firstly the output voltage was selected as monitoring signal and then the average voltage and ripple voltage were extracted as characteristic parameters. Lastly LS-SVM algorithm was used to predict Buck converter circuit. The experimental results show that the LS- SVM algorithm is especially accurate in predicting the average voltage and ripple voltage with the relative error less than 2%. The new method can trace the characteristic parameters trend and can be effectively applied in fault prediction of power electronic circuits. Key words power electronic circuits fault prediction characteristic parameter data driving least squares support vector machine LS-SVM ZD52045 CXLX NS

2 8 LS-SVM Buck Fig. 1 Buck converter circuit 1 Buck DC-DC Buck Buck 2 a u o U o N u o i i U o = 1 u least squares support N N o i 1 i = 1 vector machine LS-SVM b - LS-SVM - Δu LS - SVM SVM support vector machine regression SVR LS-SVM 1 x Buck Hilbert 1 MOSFET IRF151 SVM f = 50 khz D = L = 43 μh f x = w T x + b w R n b R 2 D1 MUR405 C = 220 μf ESR R L = Ω 1. 2 LS-SVM f x

3 66 15 x w w T w b R n n R support vector SV 7 2 minj w e = 1 w b e 2 w 2 + γ n e 2 i } i = Buck S. t. y i = w T x i + b + e i Pspice e i γ x i x = u o x 1 x i x n i y i y = Matlab7. 6 y 1 y i y n i Lagrange Lagrange α i L w e b α = J w e - n i = 1 α i w T x i + b + e i - y i 4 Karush-Kuhn-Tucker LS- SVM f x = n i = 1 α i K x i x + b 5 K x y = x y Mercer Sigmoid 1. 3 LS-SVM 2 2 Fig. 2 Flowchart of the fault prediction Buck 1 h 5 h 24 h C 6 LS-SVM 2 LS-SVMlab Buck ESR L MOSFET R ds 3 V th g m Buck 5 LS-SVM 2

4 8 LS-SVM 67 Table 1 1 Buck LS-SVM The parameters of the components in Buck Buck /h C /μf R ESR /mω L /μh R ds /mω V th /V g m /μ Table 3 3 Prediction results of characteristic parameters Table 2 2 The characteristic parameters data /h /V /V Fig. 3 3 Prediction curves of average voltage 2. 2 LS-SVM ~ ~ LS-SVM 2 Buck gam = Buck LS-SVM Buck 2% U o Δu ~ 6 7 ~ V Fig. 4 4 Predicted curves of ripple voltage 0. 5 V 10% 1 V

5 V V 1 V 4 h 3 SVM SVM SVM March gam 2 gam sig2 RBF tana USA Table 4 4 Prediction effect of different kernel function % % gam = gam = gam = 100 sig2 = 10 gam = 1000 sig2 = and Decision LALL P HANDE M BHAT C et al. Prognostics health monitoring PHM for prior-damage assessment in electronics equipment under thermo-mechanical loads C / /Proceedings of Electronic ference and Exposition February 25 - March LS- USA. IEEE SVM Buck mode power converters J tronics Components and Technology Conference May 29 - June New York USA MA Zhangshan. A new life system approach to the prognostic and health management PHM with survival analysis dynamic hybrid fault models evolutionary game theory and three-layer survivability analysis C / /Proceedings of IEEE Aerospace Conference 2009 Big Sky Montana USA ORSAGH R BROWN D ROEMER M. Prognostic health management for avionics system power supplies C / /Proceedings of IEEE Aerospace Conference March Big Sky Mon-. AR J LV Kehong QIU Jing LIU Guanjun. Research on life prognosis method for electronics based on dynamic damage and optimization AR model J. Acta Armamentarii BP J ZOU Xinyao YAO Ruohe. Life prediction of electronic devices based on forecast system of back propagation neural network J. Microelectronics and Computer LS-SVM J JIANG Tianhan ShU Jiong. Multi-step prediction of chaotic time series using the least squares support vector machine J. Control 7 AMARAL A CARDOSO A. Use of ESR to predict failure of output filtering capacitors in boost converters C / /Proceedings of IEEE International Symposium on Industrial Electronics May New York USA. IEEE IMAM A DIVAN D HABETLER T et al. Real-time condition monitoring of the electrolytic capacitors for power electronics applications C / /Proceedings of IEEE Applied Power Electronics Con- New York 9 CHEN Yaow-Ming CHOU Hsu-Wei LEE Kungyen. Online failure prediction of the electrolytic capacitor for LC filter of switching-. IEEE Transactions on Industrial Elec-. J

6 LIU Jun HUANG Mengzhi WANG Yang. Research on vectorcontrol system of PMSM based on internal model control of current loop C / /Second International Workshop on Computer Science and Engineering Octorber Qingdao China. IEEE LENNART Harnefors HANS Peter Nee SHARMA C. Modelbased current control of AC machines using the internal model control method J. IEEE Transactions on Industry Applications J ZHU Xirong ZHOU Yuanshen FU Xiao. Three-degree-freedom internal model dynamic decoupling control of synchronous motor J. Electric Machines and Control H J LI Hua HOU Yansong. Design of internal model control feedback filter by H optimization J. Electric Machines and Control 檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪檪 68 CUI Jiang WANG Youren LIU Quan. The technique of power electronic circuit fault diagnosis based on higher-order spectrum analysis and support vector machines J. Proceedings of the Chinese Society for Electrical Engineering MULLER K SMOLA A RATSCH G et al. Predicting time series with support vector machines C / /Proceedings of International Conference on Artificial Neural Networks October Berlin Germany. Springer MOSFET J WANG Cailin SUN Cheng. Analysis of high characteristics and SOA of power MOSFET J. Power Electronics

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