American Journal of Electrical and Electronic Engineering
ISSN (Print): 2328-7365 ISSN (Online): 2328-7357 Website: Editor-in-chief: Naima kaabouch
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American Journal of Electrical and Electronic Engineering. 2017, 5(3), 102-107
DOI: 10.12691/ajeee-5-3-5
Open AccessArticle

The Faults Diagnostic Analysis for Analog Circuit Faults Based on Cuckoo Search Algorithm and BP Neural Network

LingZhi Yi1, 2, Yue Liu1, 2, , WenXin Yu3 and Weihong Xiao1, 2

1Key Laboratory of Intelligent Computing & Information Processing Ministry of Education, Xiangtan University, XiangTan, China

2Wind power equipment and power conversion 2011 Collaborative Innovation Center, Xiangtan University, XiangTan, China

3School of Information and Electrical Engineering Hunan University of Science and Technology, XiangTan, China

Pub. Date: June 02, 2017

Cite this paper:
LingZhi Yi, Yue Liu, WenXin Yu and Weihong Xiao. The Faults Diagnostic Analysis for Analog Circuit Faults Based on Cuckoo Search Algorithm and BP Neural Network. American Journal of Electrical and Electronic Engineering. 2017; 5(3):102-107. doi: 10.12691/ajeee-5-3-5


Neural networks have many advantages, such as parallel processing, self-suit, associated memory and classify ability strongly which can be used to analog circuit fault diagnosis. But it is very easy to trap the local minimum if the initial network weights are randomly generated. To solve this problem, the cuckoo search algorithm is used to optimize the initial weights of the neural network. A novel method for analog circuit fault diagnosis is proposed in this paper, based on BP neural network as classifier optimized by cuckoo search algorithm. The feasibility and effectiveness of the proposed method are verified by the simulations of Sallen-Key low-pass filter circuit. Compared with other methods, the results show that the proposed method is effective to identify and classify faults.

BP neural network (BP) cuckoo search algorithm (CS) analog circuit fault diagnosis

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