基于改进ELM-Markov Model的建筑结构稳定性监测算法

doi:10.13229/j.cnki.jdxbgxb.20230783

Abstract

Abstract:

A building structure stability monitoring algorithm based on the improved ELM-Markov Model is proposed to address the direct impact of structural stability on building safety. Firstly， the time-frequency map of the building structure acceleration signal is obtained through the S-transform， and the texture features of the acceleration signal time-frequency map are obtained using the gray level co-occurrence matrix. Sensitive feature vectors are extracted by combining the intra class and inter class scatter matrices， Then， ELM Markov Model is constructed by combining Extreme learning machine （ELM） and Markov Model， and the fitting error of ELM is divided into Markov state and predicted by error， and the predicted value of ELM is revised. Then， the improved gray wolf algorithm is introduced to optimize the state number of ELM Markov Model. Finally， the sensitive feature vector is input into the optimized ELM Markov Model to realize the stability monitoring of building structures. The experimental results show that the proposed method has small monitoring error， strong robustness， and high efficiency.

Key words: extreme learning machine, Markov model, building structure, stability monitoring, S transformation

CLC Number:

TP312

Yi-yan LIU,Xing LIU,Fang-fang LIU,Jie DAI. Building structure stability monitoring algorithm based on improved ELM-Markov Model[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(11): 3351-3357.

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参数	梁	柱
材质	空钢管	薄钢板
截面尺寸/mm	25×25×2.5	25×4.5
体密度度/（kg·m^-3）	7 850	7 850
杨氏模量/Pa	206×10⁹	206×10⁹
惯性矩/m⁴	2.17×10^-8	2.03×10^-8

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Building structure stability monitoring algorithm based on improved ELM-Markov Model

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