Building an expert system for diagnosing traction electric motors of rolling stock

被引：0

作者：

Shkodun, P. K. ^{[1
]}

Dolgova, A., V ^{[2
]}

机构：

[1] Omsk State Transport Univ, Dept Elect Machines & Gen Elect Engn, 35 Marksa Pr, Omsk, Russia

[2] Omsk State Transport Univ, Dept Comp Sci Appl Math & Mech, 35 Marksa Pr, Omsk, Russia

来源：

MECHANICAL SCIENCE AND TECHNOLOGY UPDATE (MSTU 2019) | 2019年 / 1260卷

关键词：

D O I：

10.1088/1742-6596/1260/5/052029

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This article is devoted to the development of an expert system for diagnosing traction electric motors of rolling stock. The article describes the process of selecting diagnostic parameters, allowing to assess the quality of machining and assembly of the traction motor. The process of formation of a fuzzy model of diagnosing a traction motor based on the Takagi-Sugeno algorithm is shown. Selected diagnostic parameters are taken as input linguistic variables of a fuzzy model. As an output linguistic variable, a complex indicator of the quality of mechanical processing of the collector of a traction motor was adopted. The article presents the membership functions for the input and output linguistic variables and the rules for fuzzy products for the model being implemented. The hypersurface of the output linguistic variable in the space of various attributes is shown. Based on a fuzzy model, a neural fuzzy network has been developed, which allows to evaluate the quality of mechanical processing of a collector of a traction motor, and presents the results of its training. The developed neural fuzzy network is recommended to be used as one of the components of a comprehensive expert system for diagnosing traction electric motors of rolling stock.

引用

页数：6

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