Abstract
In order to improve the precision of fatigue life prediction of ballastless track, a method for predicting fatigue life of ballastless track based on big data is proposed. The big data model is constructed to analyze the fatigue life cycle of ballastless track. Big data mining and feature extraction are used to extract the fatigue life cycle of ballastless track. Combining with the particle swarm optimization method, the feature classification of the failure state trend of ballastless track construction is carried out, and the information fusion is carried out according to the characteristic parameters of the failure state of ballastless track construction. The expert system model for predicting fatigue life of ballastless track construction is established and the fatigue life of ballastless track is predicted by association rule mining method. The simulation results show that the precision of fatigue life prediction of ballastless track is high, and the strength and life cycle of ballastless track are analyzed.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Wang, A. (2019). Research on Fatigue Life Prediction Method of Ballastless Track Based on Big Data. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-030-36405-2_15
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DOI: https://doi.org/10.1007/978-3-030-36405-2_15
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