Research Article
Research on Fatigue Life Prediction Method of Ballastless Track Based on Big Data
@INPROCEEDINGS{10.1007/978-3-030-36405-2_15, author={Ailin Wang}, title={Research on Fatigue Life Prediction Method of Ballastless Track Based on Big Data}, proceedings={Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21--22, 2019, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2019}, month={11}, keywords={Big data Ballastless track Fatigue life Prediction}, doi={10.1007/978-3-030-36405-2_15} }- Ailin Wang
Year: 2019
Research on Fatigue Life Prediction Method of Ballastless Track Based on Big Data
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-36405-2_15
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.
