{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T19:13:37Z","timestamp":1784142817097,"version":"3.55.0"},"reference-count":33,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T00:00:00Z","timestamp":1683849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CDTI","award":["CER-20190001"],"award-info":[{"award-number":["CER-20190001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Virtual sensing is the process of using available data from real sensors in combination with a model of the system to obtain estimated data from unmeasured points. In this article, different strain virtual sensing algorithms are tested using real sensor data, under unmeasured different forces applied in different directions. Stochastic algorithms (Kalman filter and augmented Kalman filter) and deterministic algorithms (least-squares strain estimation) are tested with different input sensor configurations. A wind turbine prototype is used to apply the virtual sensing algorithms and evaluate the obtained estimations. An inertial shaker is installed on the top of the prototype, with a rotational base, to generate different external forces in different directions. The results obtained in the performed tests are analyzed to determine the most efficient sensor configurations capable of obtaining accurate estimates. Results show that it is possible to obtain accurate strain estimations at unmeasured points of a structure under an unknown loading condition, using measured strain data from a set of points and a sufficiently accurate FE model as input and applying the augmented Kalman filter or the least-squares strain estimation in combination with modal truncation and expansion techniques.<\/jats:p>","DOI":"10.3390\/s23104706","type":"journal-article","created":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T09:56:18Z","timestamp":1683885378000},"page":"4706","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Strain Virtual Sensing for Structural Health Monitoring under Variable Loads"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2174-5103","authenticated-orcid":false,"given":"Bartomeu","family":"Mora","sequence":"first","affiliation":[{"name":"Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), 20500 Arrasate-Mondragon, Spain"},{"name":"Faculty of Engineering in Bilbao, University of the Basque Country (UPV\/EHU), 48013 Bilbao, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jon","family":"Basurko","sequence":"additional","affiliation":[{"name":"Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), 20500 Arrasate-Mondragon, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4444-5549","authenticated-orcid":false,"given":"Iman","family":"Sabahi","sequence":"additional","affiliation":[{"name":"KU Leuven, Department of Mechanical Engineering, Celestijnenlaan 300, B-3001 Leuven, Belgium"},{"name":"Flanders Make@KU Leuven, B-3001 Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4913-6438","authenticated-orcid":false,"given":"Urko","family":"Leturiondo","sequence":"additional","affiliation":[{"name":"Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), 20500 Arrasate-Mondragon, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4516-694X","authenticated-orcid":false,"given":"Joseba","family":"Albizuri","sequence":"additional","affiliation":[{"name":"Faculty of Engineering in Bilbao, University of the Basque Country (UPV\/EHU), 48013 Bilbao, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,12]]},"reference":[{"key":"ref_1","first-page":"552","article-title":"Data Fusion Approaches for Structural Health Monitoring and System Identification: Past, Present, and Future","volume":"19","year":"2018","journal-title":"SAGE Struct. 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