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Wind and Structures Volume 37, Number 5, November 2023 , pages 383-397 DOI: https://doi.org/10.12989/was.2023.37.5.383 |
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Simulation combined transfer learning model for missing data recovery of nonstationary wind speed |
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Qiushuang Lin, Xuming Bao, Ying Lei and Chunxiang Li
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| Abstract | ||
| In the Structural Health Monitoring (SHM) system of civil engineering, data missing inevitably occurs during the data acquisition and transmission process, which brings great difficulties to data analysis and poses challenges to structural health monitoring. In this paper, Convolution Neural Network (CNN) is used to recover the nonstationary wind speed data missing randomly at sampling points. Given the technical constraints and financial implications, field monitoring data samples are often insufficient to train a deep learning model for the task at hand. Thus, simulation combined transfer learning strategy is proposed to address issues of overfitting and instability of the deep learning model caused by the paucity of training samples. According to a portion of target data samples, a substantial quantity of simulated data consistent with the characteristics of target data can be obtained by nonstationary wind-field simulation and are subsequently deployed for training an auxiliary CNN model. Afterwards, parameters of the pretrained auxiliary model are transferred to the target model as initial parameters, greatly enhancing training efficiency for the target task. Simulation synergy strategy effectively promotes the accuracy and stability of the target model to a great extent. Finally, the structural dynamic response analysis verifies the efficiency of the simulation synergy strategy. | ||
| Key Words | ||
| missing data recovery; nonstationary simulation; nonstationary wind speed; simulation synergy strategy; transfer learning | ||
| Address | ||
| Qiushuang Lin:1)College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China 2)Henan New Environmentally-Friendly Civil Engineering Materials Engineering Research Center, Xinyang Normal University, Xinyang 464000, China Xuming Bao:1)Institute of Structural Engineering, Zhejiang University, Hangzhou 310058, China 2)School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, China Ying Lei:School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China Chunxiang Li:School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, China | ||