基于LSTM和响应分解的冲击载荷识别方法研究

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Abstract The strain produced by impact load on a structural is much greater than the static load. It is of great significance to identify the impact load accurately. The method proposed aims at the prominent contradiction of inconsistent sample length between impact load and response signal. The method was based on linear model and the experiment was carried on a steel pylon structure. Firstly, the feature extraction of vibration signals was carried out based on the impact response signal decomposition theory. Then, the load and response signal sample characteristics are mapped to realize the impact load identification based on the long short term memory neural network (LSTM). The results show that the correlation coefficients between the true and predicted load are more than 94% and the RMSE (root-mean square error) are less than 0.6.

Key words： impact load identification response decomposition extracting signal characteristic long short term memory neural network(LSTM)

Received: 15 February 2023 Published: 15 February 2023

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	HUANG Dawei
	CHEN Likun
	GAO Yadong

Cite this article:

HUANG Dawei,CHEN Likun,GAO Yadong. Impact load identification method based on LSTM and response decomposition[J]. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(3): 69-76.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2024/V43/I3/69

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