Abstract
This paper proposes to establish a model of wavelet neural network to diagnose and predict the health of the tunnel structure. First, the dynamic response signal of the tunnel structure can be collected by wavelet transform, so the feature that best reflects the defect structure can be extracted. The node coefficient of wavelet packet can be used as the feature input vector of the neural network structure. Establish a wavelet neural network model, adjust the MSE value of the model by adjusting the relevant network and setting parameters, get the optimal model, and finally, use the trained neural network model to simulate effectively. The results show that this method has a good effect on the health diagnosis of the tunnel structure, and it can be used in subsequent engineering practice to be popularized.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zeng, D.J., Liu, W., Du, Y.B.: Study on prediction model for deformation of unsymmetrical loading tunnel in bedding strata based on artificial neural network. Subgrade Eng. 3, 170–174 (2020) [in Chinese]
Zhao, X.P., Sun, H.M., Zhang, S.X., Zhang, B.: Application of BP neural network in predicting ground settlement in urban shield tunneling. Subgrade Eng. 4, 170–175 (2020) [in Chinese]
Li, R.J., Bai, R.S., Ma, J.S., Hu, J.L.: Application of stress wave reflection method in the non-destructive testing of wooden structure. Archit. Technol. 8, 752–754 (2015) [in Chinese]
Wang, X.C., Shi, F., Yu, L.: Analysis of 43 cases of MATLAB neural network. Beijing University of Aeronautics and Astronautics Press, Beijing (2019) [in Chinese]
Acknowledgements
This work was financially supported by Zhangjiakou Science and Technology Bureau and Hebei Education Department (ZC2021224).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Li, R., Shi, Y. (2022). Research on Intelligent Health Diagnosis of Tunnel Structure System Based on Wavelet Neural Network. In: Jain, L.C., Kountchev, R., Hu, B., Kountcheva, R. (eds) Smart Communications, Intelligent Algorithms and Interactive Methods. Smart Innovation, Systems and Technologies, vol 257. Springer, Singapore. https://doi.org/10.1007/978-981-16-5164-9_17
Download citation
DOI: https://doi.org/10.1007/978-981-16-5164-9_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-5163-2
Online ISBN: 978-981-16-5164-9
eBook Packages: EngineeringEngineering (R0)