RESEARCH PAPER
Intelligent Forecasting of Automatic Train Protection System Failure Rate in China High-speed Railway
| 1 | State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Haidian, Beijing 100044, China |
| 2 | Signal & Communication Research Institute China Academy of Railway Sciences Haidian, Beijing 100081, China |
| 3 | Rail Transit Scientific Research Institution Nanning University Nanning 530200, Guangxi, China |
Publication date: 2019-12-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2019;21(4):567–576
KEYWORDS
intelligent maintenancehigh-speed railwayfailure rateautomatic train protection systemprediction modelchaos
ABSTRACT
Intelligent and personalized dynamic maintenance and spare parts configuration of high-speed railway have been the main trend
to guarantee the safety capability of trains. In this paper, a new Automatic Train Protection (ATP) system failure rate calculation
method is proposed, and the delay time and embedded dimension are determined by C-C algorithm. Then the phase space is reconstructed from one-dimensional time series to high-dimensional space. Based on chaotic characteristics of failure rate, a short-term
intelligent forecasting model of failure rate of ATP system is established. The actual failure statistics from 2010 to 2018 are used as
samples to train and test the validity of the model. From prediction results, it shows that the proposed chaos prediction model has
an accuracy of 99.71%, which is better than the support vector machine model. Through the intelligent prediction of failure rate,
this paper solves the maintenance inflexibility and imbalance of supply and demand of spare parts configuration.
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