Automatic Prediction Model of Ground Vibration for High-Speed Trains

Yit Jin Chen; Chi Jim Chen

doi:10.4028/www.scientific.net/AMM.764-765.644

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 764-765Automatic Prediction Model of Ground Vibration for...

Automatic Prediction Model of Ground Vibration for High-Speed Trains

Abstract:

This paper presents an automatic prediction model for ground vibration induced by Taiwan high-speed trains on embankment structures. The prediction model is developed using different field-measured ground vibration data. The main characteristics that affect the overall vibration level are established based on the database of measurement results. The influence factors include train speed, ground condition, measurement distance, and supported structure. Support vector machine (SVM) algorithm, a widely used prediction model, is adopted to predict the vibration level induced by high-speed trains on embankments. The measured and predicted vibration levels are compared to verify the reliability of the prediction model. Analysis results show that the developed SVM model can reasonably predict vibration level with an accuracy rate of 72% to 84% for four types of vibration level, including overall, low, middle, and high frequency ranges. The methodology in developing the automatic prediction system for ground vibration level is also presented in this paper.

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Periodical:

Applied Mechanics and Materials (Volumes 764-765)

Pages:

644-648

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.764-765.644

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Online since:

May 2015

Authors:

Yit Jin Chen*, Chi Jim Chen

Keywords:

Embankment, Environmental Vibration, Ground Vibration Measurement, High-Speed Trains, Prediction Model, Support Vector Machine (SVM)

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* - Corresponding Author

References

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