高速铁路牵引变电所健康状态评估

Assessment of health status of high speed railway traction substation

为了全面监测并评估高速铁路牵引变电所的健康状态,提出一种基于模糊灰色聚类与组合赋权相结合的健康状态评估方法,并将其应用到牵引变电所健康状态评估中。利用熵权法与层次分析法确定牵引变电所关键设备指标的权重;通过组合赋权法对指标权重进行组合;利用灰色聚类系数表示各设备的健康状态。在此基础上,采用模糊评判法实现对牵引变电所健康状态的评估。以西北某牵引变电所为例进行分析,健康状态评估结果为较好,与实际检测结果一致。研究结果表明:所提出的方法适用于牵引变电所的分层模型,能有效实现牵引变电所的健康状态评估,为智能牵引变电所的发展提供理论依据。

In order to comprehensively monitor and assess the health status of high-speed railway traction substation,a health status assessment method based on fuzzy grey clustering and combined weighting was proposed,and it was applied to the health status assessment of traction substation.Firstly,entropy weight method and analytic hierarchy process were used to determine the weight of key equipment indexes of traction substation.Secondly,the index weights were obtained by using the combined weighting method,and then the grey clustering coefficient was used for expressing the health status of each equipment.Finally,the fuzzy comprehensive evaluation method was used to evaluate the health state of traction substation.Taking a traction substation in northwest China as an example for analysis,the results of health status assessment were good and consistent with the actual test results.The research shows that the proposed method is applicable to the hierarchical model of traction substation,which can effectively realize the health evaluation of traction substation and provide theoretical basis for the development of intelligent traction substation.