Building Vibration Prediction Induced by Moving Train with Random Forest

Autor: Jinbao Yao, Lei Fang
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Journal of Advanced Transportation, Vol 2021 (2021)
Druh dokumentu: article
ISSN: 0197-6729
2042-3195
DOI: 10.1155/2021/6642071
Popis: This paper adopts a combination of numerical simulation, field test, and Random Forest to predict the building vibration induced by moving train. First, a three-dimensional finite element model based on train-track-site soil-building system is established, and the track dynamic reaction force calculated by the train-track model is applied as an excitation to the site. On the soil-building model, this paper analyzes the influence of train speed, axle load, site soil characteristics, and distance from the building on the vibration of the building caused by the train. With the Random Forest, these different influencing factors are used as inputs, and the building vibration is the output. Thus, the prediction model of the building vibration caused by moving train is established. The prediction accuracy can be tested with the measured data. The results show that this prediction method can provide a higher prediction accuracy with the maximum error (less than 6.41%) and the average error (less than 2.29%). This method overcomes the shortcomings of traditional prediction methods and improves the accuracy of vibration prediction.
Databáze: Directory of Open Access Journals
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