Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers
This study evaluates input error function observers for tracking of stiffness variation in real-time. The input error function is an Analytical Redundancy (AR)-based diagnosis method and necessitates a mathematical model of the system and system identification techniques. In practice, mathematical m...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/24/11857 |
| _version_ | 1827674267631747072 |
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| author | Prasad Dharap Satish Nagarajaiah |
| author_facet | Prasad Dharap Satish Nagarajaiah |
| author_sort | Prasad Dharap |
| collection | DOAJ |
| description | This study evaluates input error function observers for tracking of stiffness variation in real-time. The input error function is an Analytical Redundancy (AR)-based diagnosis method and necessitates a mathematical model of the system and system identification techniques. In practice, mathematical models used during numerical simulations differ from the actual status of the structure, and thus, accurate mathematical models are rarely available for reference. Noise is an unwanted signal in the input–output measurements but unavoidable in real-world applications (as in long span bridge trusses) and hard to imitate during numerical simulations. Simulation data from the truss system clearly indicates the effectiveness of the proposed structural damage detection method for estimating the severity of the damage. Optimization of the input error function can further automate the stiffness estimation in structural members and address critical aspects such as system uncertainties and the presence of noise in input–output measurements. Stiffness tracking in one of the planar truss members indicates the potential of optimization of the input error function for online structural health monitoring and implementing condition-based maintenance. |
| first_indexed | 2024-03-10T04:38:07Z |
| format | Article |
| id | doaj.art-edceaf0848d749209897692e567f73cb |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:38:07Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-edceaf0848d749209897692e567f73cb2023-11-23T03:39:27ZengMDPI AGApplied Sciences2076-34172021-12-0111241185710.3390/app112411857Tracking of Stiffness Variation in Structural Members Using Input Error Function ObserversPrasad Dharap0Satish Nagarajaiah1Complementary Visiting Scholar, Department of Civil and Environmental Engineering, Rice University, Houston, TX 77005, USAProfessor, Department of Civil and Environmental Engineering, Department of Mechanical Engineering, Department of Material Science and Nano Engineering, Rice University, Houston, TX 77005, USAThis study evaluates input error function observers for tracking of stiffness variation in real-time. The input error function is an Analytical Redundancy (AR)-based diagnosis method and necessitates a mathematical model of the system and system identification techniques. In practice, mathematical models used during numerical simulations differ from the actual status of the structure, and thus, accurate mathematical models are rarely available for reference. Noise is an unwanted signal in the input–output measurements but unavoidable in real-world applications (as in long span bridge trusses) and hard to imitate during numerical simulations. Simulation data from the truss system clearly indicates the effectiveness of the proposed structural damage detection method for estimating the severity of the damage. Optimization of the input error function can further automate the stiffness estimation in structural members and address critical aspects such as system uncertainties and the presence of noise in input–output measurements. Stiffness tracking in one of the planar truss members indicates the potential of optimization of the input error function for online structural health monitoring and implementing condition-based maintenance.https://www.mdpi.com/2076-3417/11/24/11857real-time structural damage detectioninput error functionoptimizationanalytical redundancysystem uncertaintyinteraction matrix |
| spellingShingle | Prasad Dharap Satish Nagarajaiah Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers Applied Sciences real-time structural damage detection input error function optimization analytical redundancy system uncertainty interaction matrix |
| title | Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers |
| title_full | Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers |
| title_fullStr | Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers |
| title_full_unstemmed | Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers |
| title_short | Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers |
| title_sort | tracking of stiffness variation in structural members using input error function observers |
| topic | real-time structural damage detection input error function optimization analytical redundancy system uncertainty interaction matrix |
| url | https://www.mdpi.com/2076-3417/11/24/11857 |
| work_keys_str_mv | AT prasaddharap trackingofstiffnessvariationinstructuralmembersusinginputerrorfunctionobservers AT satishnagarajaiah trackingofstiffnessvariationinstructuralmembersusinginputerrorfunctionobservers |