{"id":494,"date":"2021-07-14T22:00:00","date_gmt":"2021-07-14T20:00:00","guid":{"rendered":"https:\/\/www.extende.com\/blog\/damage-monitoring-with-civa-shm\/"},"modified":"2025-06-24T18:52:17","modified_gmt":"2025-06-24T16:52:17","slug":"damage-monitoring-with-civa-shm","status":"publish","type":"post","link":"https:\/\/www.extende.com\/fr\/blog\/damage-monitoring-with-civa-shm\/","title":{"rendered":"Damage monitoring with CIVA SHM"},"content":{"rendered":"<p>When designing and qualifying <span class=\"g-color2\">Structural Health Monitoring<\/span> (SHM) and predictive maintenance strategies, it is important to know for which defect size and location the system will be able to detect the damage. Experimentally, it is really difficult and costly to test lots of scenarios since this requires production of many mock-ups with different defects, and to implement all of them with embedded sensors.<\/p>\n<\/p>\n<p>\u00a0<\/p>\n<\/p>\n<p><span class=\"g-color1\">CIVA SHM<\/span> enables the <span class=\"g-color2\">simulation of Guided Waves monitoring<\/span>, and includes imaging tools that can characterize a defect signature with a visible indication. It is very easy to define variable parameters with simulation. Thanks to <span class=\"g-color2\">metamodels<\/span> available in <span class=\"g-color1\">CIVA<\/span> software, modelling becomes even more powerful as you will be able to produce a continuum of results to fully explore the impact of different variable parameters.<\/p>\n<\/p>\n<p>\u00a0<\/p>\n<\/p>\n<p>Our <a class=\"youtube\" href=\"https:\/\/www.youtube.com\/watch?v=uPoEjgezJ04\" target=\"_blank\" title=\"(Nouvelle fen\u00eatre)\">video of CIVA SHM<\/a> introduces one simulation example with a monitored aluminum plate. One defect is included, and the defect size and location are defined as variable parameters. Thanks to the <span class=\"g-color1\">CIVA<\/span> metamodel, you can visualize all possible defect indications obtained in the range of variation defined, and then predict the situations where the system will be able to detect the flaw.<\/p>\n<\/p>\n<p>This <span class=\"g-color1\">CIVA<\/span> example only required 4 hours of computation on a simple computer!<\/p>\n<\/p>\n<p>Feel free to <a class=\"lien\" href=\"https:\/\/www.extende.com\/contact\" target=\"_self\">contact us<\/a> if you need more information about <a class=\"lien\" href=\"https:\/\/www.extende.com\/civa-ndt-simulation-software\/modules-available-in-civa\/structural-health-monitoring-with-civa\/\" target=\"_blank\" title=\"(Nouvelle fen\u00eatre)\">CIVA SHM<\/a> and metamodels.<\/p>\n<\/p>\n<p>The <span class=\"g-color1\">EXTENDE<\/span> team.<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>When designing and qualifying Structural Health Monitoring (SHM) and predictive maintenance strategies, it is important to know for which defect size and location the system will be able to detect the damage. Experimentally, it is really difficult and costly to test lots of scenarios since this requires production of many mock-ups with different defects, and [&hellip;]<\/p>\n","protected":false},"author":0,"featured_media":493,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[378],"tags":[],"class_list":["post-494","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-civa-software"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/posts\/494","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/comments?post=494"}],"version-history":[{"count":1,"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/posts\/494\/revisions"}],"predecessor-version":[{"id":5772,"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/posts\/494\/revisions\/5772"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/media\/493"}],"wp:attachment":[{"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/media?parent=494"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/categories?post=494"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.extende.com\/fr\/wp-json\/wp\/v2\/tags?post=494"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}