{"id":12998,"date":"2021-07-04T12:32:03","date_gmt":"2021-07-04T12:32:03","guid":{"rendered":"https:\/\/www.vesamgroup.com\/?p=12998"},"modified":"2025-11-11T12:15:54","modified_gmt":"2025-11-11T12:15:54","slug":"application-of-machine-learning-in-monitoring-systems-of-civil-engineering-structures_en","status":"publish","type":"post","link":"https:\/\/www.vesamgroup.com\/en\/application-of-machine-learning-in-monitoring-systems-of-civil-engineering-structures_en\/","title":{"rendered":"Application of machine learning in monitoring systems of civil structures"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"12998\" class=\"elementor elementor-12998\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c5005d4 elementor-section-full_width elementor-section-height-default elementor-section-height-default qodef-elementor-content-no\" data-id=\"c5005d4\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a477b09\" data-id=\"a477b09\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f84cf33 elementor-widget elementor-widget-text-editor\" data-id=\"f84cf33\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>StrStructural Health Monitoring (SHM) aims primarily to accurately identify the current state of a structure, assessing damage levels and eventually allowing to predict its future performance. In civil engineering structures, SHM is often responsible for ensuring public safety while handling with large and complex data. Such monitoring problems can be difficult to solve by conventional computing techniques alone, as they require the acquisition of large data sets that need to be thoroughly and carefully analyzed. This yields big data opportunities to use artificial intelligence methodologies.<\/p><p>This paper presents the integration of machine learning (ML) techniques for pattern recognition in SHM systems of civil engineering structures. The developed SHM consists of data acquisition both from time series of values observed at regular intervals and from structurally relevant measured values, called events, where specific data are collected.<\/p><p>ML is used in the development of statistical models for feature discrimination. Events are classified into different clusters in a semi-supervised learning procedure, which is an extension of an unsupervised learning to allow their identification. A real-world SHM implementation is presented as a case study of the ML application. It consists of an industrial steel tower structure, containing several mechanical equipment with different loads, which operate at various frequencies.<\/p><p>A sensor network is installed, acquiring data on strains, accelerations, and weather conditions. A visualization user interface is provided to access all data through a user friendly and accessible tool. The paper presents the main results obtained and illustrates the potentialities of the applied ML methodology.<\/p><p><span style=\"font-weight: var( --e-global-typography-text-font-weight );\">\u00a0<\/span><\/p><p><b>AUTHORS\u00a0|<\/b><span style=\"font-weight: var( --e-global-typography-text-font-weight );\">\u00a0Jo\u00e3o Zeferino\u00aa, Eduardo Gon\u00e7alves\u00aa, Paulo Carapito<\/span><span style=\"background-color: #ffffff; color: var( --e-global-color-text ); font-weight: var( --e-global-typography-text-font-weight );\">\u00aa<\/span><span style=\"font-weight: var( --e-global-typography-text-font-weight );\">, <\/span><span style=\"font-weight: var( --e-global-typography-text-font-weight );\">Filipe Santos<\/span><span style=\"background-color: #ffffff; color: var( --e-global-color-text ); font-weight: var( --e-global-typography-text-font-weight );\">\u00aa<\/span><\/p><p>VESAM Engenharia S.A., Zona Industrial de Cantanhede, Lote 69, 3060-197 Cantanhede, Portugal<\/p><p>\u00a0<\/p><p><strong>Paper presented at the 10th Edition of the International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 10), June 30 to July 2, 2021, Porto, Portugal<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-176a79b elementor-widget elementor-widget-stal_core_button\" data-id=\"176a79b\" data-element_type=\"widget\" data-widget_type=\"stal_core_button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<a class=\"qodef-shortcode qodef-m  qodef-button qodef-layout--splitted  qodef-html--link\" href=\"https:\/\/www.vesamgroup.com\/wp-content\/uploads\/2021\/11\/Application-of-machine-learning-in-monitoring-systems-of-civil-structures.pdf\" target=\"_self\"  >\n    <span class=\"qodef-m-text\">\n        See article        <svg class=\"qodef-m-arrowline\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" x=\"0px\" y=\"0px\" viewBox=\"0 0 63 20\" xml:space=\"preserve\">\n                            <line x1=\"61.6\" y1=\"10\" x2=\"61.6\" y2=\"10\"\/>\n                            <line x1=\"62\" y1=\"10\" x2=\"61.6\" y2=\"10\"\/>\n                            <line x1=\"61.6\" y1=\"10\" x2=\"1\" y2=\"10\"\/>\n                            <path d=\"M61.6,10\"\/>\n                            <line x1=\"61.6\" y1=\"10\" x2=\"61.6\" y2=\"10\"\/>\n                            <line class=\"arrow-up\" x1=\"56.7\" y1=\"5.1\" x2=\"61.6\" y2=\"10\"\/>\n                            <path d=\"M61.6,10\"\/>\n                            <line x1=\"61.6\" y1=\"10\" x2=\"61.6\" y2=\"10\"\/>\n                            <line class=\"arrow-down\" x1=\"61.6\" y1=\"10\" x2=\"56.7\" y2=\"14.9\"\/>\n                        <\/svg>    <\/span>\n    <span class=\"qodef-m-split qodef-split--up\"><\/span>\n    <span class=\"qodef-m-split qodef-split--down\"><\/span>\n<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Paper presented at the 10th Edition of the International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 10), June 30 to July 2, 2021, Porto, Portugal<\/p>\n","protected":false},"author":4,"featured_media":13016,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[100],"tags":[],"class_list":["post-12998","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-article"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - 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