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The Faults Diagnostic Analysis for Analog Circuit Faults Based on Firefly Algorithm and Extreme Learning Machine

Lingzhi Yi 1, Yongbo Sui 1, and Wenxin Yu 2
1. Hunan Province Cooperative Innovation Center for Wind Power Equipment and Energy Conversion,Xiangtan University, Ministry of Education, Xiangtan, China
2. School of Information and Electrical Engineering Hunan University of Science and Technology, Xiangtan, China
Abstract—In this paper, a novel method for analog circuit fault diagnosis based on extreme learning machine (ELM) as classifier which is optimized firefly algorithm (FA) is proposed. The feasibility and effectiveness of the proposed method are verified by the simulations of Sallen-Key low-pass filter circuit. The results show that the proposed method is effective to identify and classify faults by comparisons to other methods, which indicate feasibility and practicability of our proposed method.

Index Terms—firefly algorithm, extreme learning machine, analog circuit, fault diagnostic

Cite: Lingzhi Yi, Yongbo Sui, and Wenxin Yu, "The Faults Diagnostic Analysis for Analog Circuit Faults Based on Firefly Algorithm and Extreme Learning Machine," Jounal of Automation and Control Engineering, Vol. 4, No. 6, pp. 413-417, December, 2016. doi: 10.18178/joace.4.6.413-417
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