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Cable risk assessment visualization based on combination weighting |
DONG Zhang, LI Siyao, CHEN Yani, LIU Hui, HE Ming |
Luohu Power Supply Bureau, Shenzhen Power Supply Bureau Co., Ltd, Shenzhen, Guangdong 518000 |
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Abstract In this paper, a cable risk assessment method that employs a combination weighting approach is proposed for evaluating the risk associated with the present operational condition of the cable. Based on the assessment findings, the corresponding warning level is set and feedback is given, and the risk level is visualized. First, the indicators that affect the operating status of the cable are selected to establish a risk assessment system. Secondly, the reference range of the state value of the cable under different operating conditions is established. Thirdly, according to the comparison between the real-time data of cable operation and the reference range of state quantity under different operating conditions, the possibility that the cable belongs to a certain state is calculated, and the fuzzy evaluation matrix is formed. Fourthly, the combination weighting methodology is utilized to determine the relative importance of each state variable in the context of different fault states. The resulting weights are subsequently incorporated into the fuzzy evaluation matrix, yielding the final evaluation matrix based on the principle of maximum membership degree. Then, the severity of the consequences caused by different fault states of the cable is scored by expert scoring. Finally, based on the expert’s scoring and the probability of failure, the current operating risk value of the cable is calculated, the risk level of the cable is evaluated, and the risk warning level is visualized. The proposed method can evaluate the risk level of the cable, visualize the risk level, predict the possible occurrence of the current risk level and give preventive suggestions.
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Received: 10 April 2023
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Cite this article: |
DONG Zhang,LI Siyao,CHEN Yani等. Cable risk assessment visualization based on combination weighting[J]. Electrical Engineering, 2023, 24(6): 57-63.
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URL: |
http://dqjs.cesmedia.cn/EN/Y2023/V24/I6/57
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