A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring
Among all the aspects that are linked to a structural health monitoring (SHM) system, algorithms, strategies, or methods for damage detection are currently playing an important role in improving the operational reliability of critical structures in several industrial sectors. This paper introduces a...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2015/648097 |
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| _version_ | 1832559384165613568 |
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| author | Maribel Anaya Diego A. Tibaduiza Francesc Pozo |
| author_facet | Maribel Anaya Diego A. Tibaduiza Francesc Pozo |
| author_sort | Maribel Anaya |
| collection | DOAJ |
| description | Among all the aspects that are linked to a structural health monitoring (SHM) system, algorithms, strategies, or methods for damage detection are currently playing an important role in improving the operational reliability of critical structures in several industrial sectors. This paper introduces a bioinspired strategy for the detection of structural changes using an artificial immune system (AIS) and a statistical data-driven modeling approach by means of a distributed piezoelectric active sensor network at different actuation phases. Damage detection and classification of structural changes using ultrasonic signals are traditionally performed using methods based on the time of flight. The approach followed in this paper is a data-based approach based on AIS, where sensor data fusion, feature extraction, and pattern recognition are evaluated. One of the key advantages of the proposed methodology is that the need to develop and validate a mathematical model is eliminated. The proposed methodology is applied, tested, and validated with data collected from two sections of an aircraft skin panel. The results show that the presented methodology is able to accurately detect damage. |
| format | Article |
| id | doaj-art-e96b6840d73e4cb089050117412fc51d |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-e96b6840d73e4cb089050117412fc51d2025-02-03T01:30:11ZengWileyShock and Vibration1070-96221875-92032015-01-01201510.1155/2015/648097648097A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health MonitoringMaribel Anaya0Diego A. Tibaduiza1Francesc Pozo2CoDAlab, Department of Applied Mathematics III, Universitat Politècnica de Catalunya (UPC), 08036 Barcelona, SpainFaculty of Electronic Engineering, Universidad Santo Tomás, Bogotá, ColombiaCoDAlab, Department of Applied Mathematics III, Escola Universitària d’Enginyeria Tècnica Industrial de Barcelona (EUETIB), Universitat Politècnica de Catalunya (UPC), Comte d’Urgell 187, 08036 Barcelona, SpainAmong all the aspects that are linked to a structural health monitoring (SHM) system, algorithms, strategies, or methods for damage detection are currently playing an important role in improving the operational reliability of critical structures in several industrial sectors. This paper introduces a bioinspired strategy for the detection of structural changes using an artificial immune system (AIS) and a statistical data-driven modeling approach by means of a distributed piezoelectric active sensor network at different actuation phases. Damage detection and classification of structural changes using ultrasonic signals are traditionally performed using methods based on the time of flight. The approach followed in this paper is a data-based approach based on AIS, where sensor data fusion, feature extraction, and pattern recognition are evaluated. One of the key advantages of the proposed methodology is that the need to develop and validate a mathematical model is eliminated. The proposed methodology is applied, tested, and validated with data collected from two sections of an aircraft skin panel. The results show that the presented methodology is able to accurately detect damage.http://dx.doi.org/10.1155/2015/648097 |
| spellingShingle | Maribel Anaya Diego A. Tibaduiza Francesc Pozo A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring Shock and Vibration |
| title | A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring |
| title_full | A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring |
| title_fullStr | A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring |
| title_full_unstemmed | A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring |
| title_short | A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring |
| title_sort | bioinspired methodology based on an artificial immune system for damage detection in structural health monitoring |
| url | http://dx.doi.org/10.1155/2015/648097 |
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