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Fault Classification of Power Transmission Lines Using Fuzzy Reasoning Spiking Neural P Systems

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Book cover Bio-inspired Computing – Theories and Applications (BIC-TA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 681))

Abstract

This paper presents an approach for classifying different types of faults occurring in power transmission lines by integrating Fuzzy Reasoning Spiking Neural P Systems (FRSNPS) with wavelet transform and singular value decomposition. This is the first attempt to extend the application of FRSNPS from fault section identification to fault classification. The effectiveness of the introduced method is verified by various cases of fault types in power transmission lines.

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Acknowledgment

This work is supported by the National Natural Science Foundation of China (61672437, 61373047).

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Authors and Affiliations

  1. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 610031, People’s Republic of China

    Kang Huang, Gexiang Zhang, Xiaoguang Wei, Haina Rong, Yangyang He & Tao Wang

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  1. Kang Huang
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  2. Gexiang Zhang
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  3. Xiaoguang Wei
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  4. Haina Rong
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  5. Yangyang He
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  6. Tao Wang
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Corresponding author

Correspondence to Gexiang Zhang .

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Editors and Affiliations

  1. Xidian University, Xi’an, China

    Maoguo Gong

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. China University of Petroleum, Qingdao, China

    Tao Song

  4. Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Kuching, China

    Gexiang Zhang

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© 2016 Springer Nature Singapore Pte Ltd.

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Huang, K., Zhang, G., Wei, X., Rong, H., He, Y., Wang, T. (2016). Fault Classification of Power Transmission Lines Using Fuzzy Reasoning Spiking Neural P Systems. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 681. Springer, Singapore. https://doi.org/10.1007/978-981-10-3611-8_12

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  • DOI: https://doi.org/10.1007/978-981-10-3611-8_12

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  • Publisher Name: Springer, Singapore

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  • Online ISBN: 978-981-10-3611-8

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