一种用于钢轨电位评估的回归建模方法

doi:10.19595/j.cnki.1000-6753.tces.L90002

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Abstract Rail potential is one of the safety operation indexes of metro. The evaluation of rail potential level has always been a difficult problem in calculation of power supply simulation. There exists a large error when apply the traditional algorithm in power supply simulation quantitatively. Therefore, it cannot be applied to the actual train timetable. Firstly, this paper established the equivalent diagram model for rail reflux system; then through analyzing the characteristics of power supply system, the mathematical model of rail potential was divided into constant parameters and variable factors, and furthermore the relation between rail potential and variable factors was given. Based on the relation, the feasibility and applicability of regression modeling for rail potential was analyzed. The regression model of rail potential of substation was established with actual measured data and BP neural network algorithm. The result shows that error of model meets the needs of practical engineering. In addition, a practical application example of the model in operation scenario is given, which shows that the model can be well embedded in current system of power supply simulation system.

Key words： Rail potential nonlinear parameters regression analysis BP neural network

Received: 28 February 2020

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TM922

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	Articles by authors
	Zhang Zheng
	Yang Shaobing
	Wu Mingli
	Ye Jingjing

Cite this article:

Zhang Zheng,Yang Shaobing,Wu Mingli等. A Method of Regression Modeling for Rail Potential Evaluation[J]. Transactions of China Electrotechnical Society, 2021, 36(zk1): 31-39.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.L90002 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/Izk1/31

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