Research on the earthquake damage level prediction of mega-sub isolation system based on machine learning

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (20) : 40-47.

LI Xiangxiu1，SONG Xiaoyan2，LI Xiaojun1,2，LI Yi2，LIU Aiwen1

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Abstract

The finite element model of the mega-sub isolation system was established in this paper. Incremental dynamic time history analyses of the mega-sub isolation system considering different corrosion states was carried out by inputting 20 actual ground motion records with amplitude modulation on the peak ground acceleration (PGA). 240 sets of seismic responses samples were obtained, and the effect of steel corrosion on the seismic performance of the mega-sub isolation system was discussed. Using machine learning method to correlate structural information, ground motion information, and structural damage level, the prediction results of six machine learning algorithms on the damage level of the mega-sub isolation system were given. The overall prediction accuracy of extreme gradient boosting tree, gradient boosting tree, random forest, and decision tree reached more than 80%. The extreme gradient boosting tree algorithm performed the best, with an accuracy rate of 86.6% and a higher prediction accuracy for different damage states. The prediction accuracy of the support vector machine algorithm was the lowest, with an accuracy rate of 60.3%.

Key words

mega-sub isolation system / machine learning / damage level / corrosion / seismic performance / IDA

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LI Xiangxiu1，SONG Xiaoyan2，LI Xiaojun1,2，LI Yi2，LIU Aiwen1. Research on the earthquake damage level prediction of mega-sub isolation system based on machine learning[J]. Journal of Vibration and Shock, 2023, 42(20): 40-47

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