Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications
The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/3/733 |
| _version_ | 1811300119857856512 |
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| author | Diego A. Tibaduiza Burgos Ricardo C. Gomez Vargas Cesar Pedraza David Agis Francesc Pozo |
| author_facet | Diego A. Tibaduiza Burgos Ricardo C. Gomez Vargas Cesar Pedraza David Agis Francesc Pozo |
| author_sort | Diego A. Tibaduiza Burgos |
| collection | DOAJ |
| description | The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification. |
| first_indexed | 2024-04-13T06:46:34Z |
| format | Article |
| id | doaj.art-579cc243c2ec40e489d260947fd1c637 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:46:34Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-579cc243c2ec40e489d260947fd1c6372022-12-22T02:57:33ZengMDPI AGSensors1424-82202020-01-0120373310.3390/s20030733s20030733Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven ApplicationsDiego A. Tibaduiza Burgos0Ricardo C. Gomez Vargas1Cesar Pedraza2David Agis3Francesc Pozo4Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Cra 45 No. 26-85, Bogotá 111321, ColombiaDepartamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Cra 45 No. 26-85, Bogotá 111321, ColombiaDepartamento de Ingeniería de Sistemas e Industrial, Universidad Nacional de Colombia, Cra 45 No. 26-85, Bogotá 111321, ColombiaControl, Modeling, Identification and Applications (CoDAlab), Departament de Matemàtiques, Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Campus Diagonal-Besòs (CDB), Eduard Maristany, 16, 08019 Barcelona, SpainControl, Modeling, Identification and Applications (CoDAlab), Departament de Matemàtiques, Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Campus Diagonal-Besòs (CDB), Eduard Maristany, 16, 08019 Barcelona, SpainThe damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.https://www.mdpi.com/1424-8220/20/3/733data-driven algorithmsdamage identificationstructural health monitoringsensors |
| spellingShingle | Diego A. Tibaduiza Burgos Ricardo C. Gomez Vargas Cesar Pedraza David Agis Francesc Pozo Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications Sensors data-driven algorithms damage identification structural health monitoring sensors |
| title | Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications |
| title_full | Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications |
| title_fullStr | Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications |
| title_full_unstemmed | Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications |
| title_short | Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications |
| title_sort | damage identification in structural health monitoring a brief review from its implementation to the use of data driven applications |
| topic | data-driven algorithms damage identification structural health monitoring sensors |
| url | https://www.mdpi.com/1424-8220/20/3/733 |
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