Assessment of Performance Degradation of Railway Catenary Based on IK-means and CHMM

Xuyong HOU

doi:10.13890/j.issn.1000-128x.2021.02.022

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Assessment of Performance Degradation of Railway Catenary Based on IK-means and CHMM

Railway Electrification | 更新时间：2021-12-09

- Assessment of Performance Degradation of Railway Catenary Based on IK-means and CHMM
- Electric Drive for Locomotives Issue 2, Pages: 140-145(2021)
- 作者机构：
  
  1.中国铁建电气化局集团第一工程有限公司，河南　洛阳　471013
- 作者简介：
- 基金信息：
- DOI：10.13890/j.issn.1000-128x.2021.02.022
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Xuyong HOU. Assessment of Performance Degradation of Railway Catenary Based on IK-means and CHMM. [J]. Electric Drive for Locomotives (2):140-145(2021)
DOI：

Xuyong HOU. Assessment of Performance Degradation of Railway Catenary Based on IK-means and CHMM. [J]. Electric Drive for Locomotives (2):140-145(2021) DOI： 10.13890/j.issn.1000-128x.2021.02.022.

摘要

了解铁路接触网的退化性能水平有助于保障机车的安全运行。为了提高传统K-means算法聚类的合理性和准确性，引入了密度值因子来提高数据聚类精度，称为IK-means算法。采用IK-means算法对高速铁路接触网进行模式划分，将铁路接触网的退化状态划分成正常状态、轻度退化、中度退化、重度退化和失效状态共5种状态，再采用隐马尔科夫(Hidden Markov Model, HMM)算法对铁路接触网的性能退化状态进行评估。仿真测试结果表明，评估精度平均高于92.67%，验证了所提方法的可靠性。

Abstract

Understanding the degradation level of railway catenary is helpful to ensure the safe operation of locomotives. In order to improve the rationality and accuracy of the traditional K-means algorithm, the density value factor was introduced to improve the precision of data clustering, which called IK-means. The IK-means algorithm was used to divide high-speed railway catenary mode,which divided a railway catenary state of degradation into five types, including normal, mild degradation, moderate degradation, and severe degradation and failure state. The condition of the railway catenary degradation was assessed through CHMM. Simulation test results showed that the assessment accuracy was higher than 92.67%, which verified the reliability of the proposed method in this paper.

关键词

高速铁路接触网性能退化IK-means算法CHMM算法评估

Keywords

high-speed railwaycatenaryperformance degradationIK-means algorithmCHMMassessment

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