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Fault Monitoring Technology of Electrical Automation Equipment Based on Decision Tree Algorithm

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Application of Intelligent Systems in Multi-modal Information Analytics (ICMMIA 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 138))

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Abstract

With the continuous progress and development of human economy and society, the demand of human society for the stability of the power system is also increasing. The occurrence of sudden failures in the power system will cause significant economic losses and bad social consequences. Therefore, it is necessary to monitor the status of all electrical equipment in the entire power system in real time, and fully grasp the working status of electrical equipment at all times. This paper aims to study the fault monitoring technology of electrical automation equipment based on the decision tree algorithm. Based on the analysis of the basic process of data mining, the comparison of decision tree algorithms and the system performance requirements, a fault diagnosis method based on the C4.5 algorithm is proposed. The fault monitoring system of electrical automation equipment is designed. Experiments show that the algorithm can improve the classification accuracy, so to a certain extent the effectiveness of the algorithm in fault monitoring is proved.

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Author information

Authors and Affiliations

  1. School of Electrical and Information Engineering, Liaoning Institute of Science and Technology, Benxi, 117004, Liaoning, China

    Lu Zhou

  2. Siemens Ltd., Beijing, 110000, China

    Yu Cui

  3. Department of Civil Engineering, Faculty of Engineering and Technology, Madhyanchal Professional University, Bhopal, India

    Amar Jain

Authors
  1. Lu Zhou
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  2. Yu Cui
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  3. Amar Jain
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Corresponding author

Correspondence to Lu Zhou .

Editor information

Editors and Affiliations

  1. School of Business Administration, Oakland University, Rochester, MI, USA

    Vijayan Sugumaran

  2. Amrita School of Engineering, Chennai, Tamil Nadu, India

    A. G. Sreedevi

  3. Shanghai Polytechnic University, Shanghai, China

    Zheng Xu

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Zhou, L., Cui, Y., Jain, A. (2022). Fault Monitoring Technology of Electrical Automation Equipment Based on Decision Tree Algorithm. In: Sugumaran, V., Sreedevi, A.G., Xu , Z. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. ICMMIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 138. Springer, Cham. https://doi.org/10.1007/978-3-031-05484-6_5

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