Simulation on Fault Detection Optimization Model of Large Intelligent Electronic Inverter

Chun Ping Huang

doi:10.4028/www.scientific.net/AMR.986-987.1587

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Research on the Optimization Model of Fault Detection for Large-Scale Electronic Circuit
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Research on the Winding Deformation Testing System for Transformers Based on the FRA
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 986-987Simulation on Fault Detection Optimization Model...

Simulation on Fault Detection Optimization Model of Large Intelligent Electronic Inverter

Abstract:

When a fault of power system occurs in grid-connected point, a serious impact is added to electronic inverter in photovoltaic micro-network internal including current, voltage and phase, the appropriate control strategies for completing fault detection of large-scale intelligent electronic inverter, is one of the currently hotspot difficulties. An engine fault diagnosis method based on PSO-SVM is proposed. Particle swarm method is used to search engine fault signals in designated space, so as to obtain optimal particle and provide the basis for an engine fault diagnosis. Support vector machine (SVM) method is applied to classify engine failure signal to complete the engine fault diagnosis. Experimental results show that the proposed algorithm for the engine fault diagnosis, can greatly improve the accuracy of diagnosis, so as to meet the needs of actual production, life, and achieve satisfactory results.

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Energy Research and Power Engineering 2014

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Periodical:

Advanced Materials Research (Volumes 986-987)

Pages:

1587-1590

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.986-987.1587

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Online since:

July 2014

Authors:

Chun Ping Huang*

Keywords:

Electronic Inverter, Fault Detection, Particle Swarm

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* - Corresponding Author

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