Fault Diagnosis of Grounding Grid Based on Principal Component Analysis and Fuzzy Clustering

Abstract:

The problem of grounding grid fault causes great economic losses, so accurate and efficient fault location is becoming more important. This paper puts forward a new method of fault diagnosis for grounding network.Taking voltage values of test point as fault characteristics and making use of principal component analysis extract fault features from training and test samples, which can eliminate the correlation between the fault symptoms.Taking fuzzy clustering for the samples after feature extraction can get clustering center. By testing sample membership of each sample and each cluster center can diagnose the fault. The outcomes verify that utilizing principal component analysis and fuzzy clustering to solving the fault location of grounding network has good diagnostic effectiveness and efficiency.

• Periodical: Advanced Materials Research (Volume 787)
• Pages: 881-885
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.787.881
• Online since: September 2013
• Authors: Ke Xin Zhao, Min Fang Peng, Hu Tan, Shu Di He, Mei E Shen, Jian Biao He
• Keywords: Fault Diagnosis, Fuzzy Clustering, Grounding Grid, Principal Component Analysis (PCA)

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