{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T10:14:53Z","timestamp":1782209693535,"version":"3.54.5"},"reference-count":37,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T00:00:00Z","timestamp":1657584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51775401"],"award-info":[{"award-number":["51775401"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.<\/jats:p>","DOI":"10.3390\/s22145203","type":"journal-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T23:02:01Z","timestamp":1657666921000},"page":"5203","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Improved Adaptive Multi-Objective Particle Swarm Optimization of Sensor Layout for Shape Sensing with Inverse Finite Element Method"],"prefix":"10.3390","volume":"22","author":[{"given":"Xiaohan","family":"Li","sequence":"first","affiliation":[{"name":"Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi\u2019an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengtao","family":"Niu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi\u2019an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Bao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi\u2019an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naigang","family":"Hu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi\u2019an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4221","DOI":"10.3390\/s21124221","article-title":"Crack-Length Estimation for Structural Health Monitoring Using the High-Frequency Resonances Excited by the Energy Release during Fatigue-Crack Growth","volume":"21","author":"Roshan","year":"2021","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"108533","DOI":"10.1016\/j.measurement.2020.108533","article-title":"Performance of swarm intelligence based chaotic meta-heuristic algorithms in civil structural health monitoring","volume":"169","author":"Das","year":"2021","journal-title":"Measurement"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.3390\/s22041692","article-title":"Methodology for Detecting Progressive Damage in Structures Using Ultrasound-Guided Waves","volume":"22","author":"Gerardo","year":"2022","journal-title":"Sensors"},{"key":"ref_4","first-page":"256","article-title":"Research on Real-time Signal Stability of Computer Monitoring Bridge Structure Health Sensor","volume":"4","author":"Guo","year":"2022","journal-title":"Sci. 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