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In this paper, a data-driven based structural-response reconstruction approach by generating response data via a convolutional process is proposed. A conditional generative adversarial network (cGAN) is employed to establish the spatial relationship between the global and local response in the form of a response nephogram. In this way, the reconstruction process will be independent of the physical modeling of the engineering problem. The validation via experiment of a steel frame in the lab and an in situ bridge test reveals that the reconstructed responses are of high accuracy. Theoretical analysis shows that as the sensor quantity increases, reconstruction accuracy rises and remains when the optimal sensor arrangement is reached.<\/jats:p>","DOI":"10.3390\/s23156750","type":"journal-article","created":{"date-parts":[[2023,7,28]],"date-time":"2023-07-28T07:58:52Z","timestamp":1690531132000},"page":"6750","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Data-Driven Based Response Reconstruction Method of Plate Structure with Conditional Generative Adversarial Network"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2168-0503","authenticated-orcid":false,"given":"He","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China"},{"name":"Center for Balance Architecture, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Chengkan","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Jiqing","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Zhejiang University City College, Hangzhou 310015, China"}]},{"given":"Jiangpeng","family":"Shu","sequence":"additional","affiliation":[{"name":"College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Liangfeng","family":"Sun","sequence":"additional","affiliation":[{"name":"The Architectural Design & Research Institute of Zhejiang University Co., Ltd., Hangzhou 310028, China"}]},{"given":"Zhicheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,28]]},"reference":[{"key":"ref_1","first-page":"567","article-title":"A review on deep learning-based structural health monitoring of civil infrastructures","volume":"24","author":"Ye","year":"2019","journal-title":"Smart Struct. 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