Abdollahzadeh, Mohammad Amin and Kömürcü, Emre and Yıldız, Mehmet and Kefal, Adnan (2025) Displacement monitoring and damage diagnosis of a composite suspension control arm using inverse finite element method. IEEE Transactions on Instrumentation and Measurement, 74 . ISSN 0018-9456 (Print) 1557-9662 (Online)
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Official URL: https://dx.doi.org/10.1109/TIM.2025.3604915
Abstract
The intermediate link that connects the chassis of a car to the body is called the 'control arm'. This component ensures the safety of the front suspension of motor vehicles, which is why monitoring its structural condition is a must. In this study, displacement monitoring (also known as 'shape sensing') and damage detection and localization of a twist beam are performed to ensure the high structural health of automotive components during operation. For this purpose, we use a superior sensing algorithm based on sensor data, the inverse finite element method (iFEM), which can predict shape changes in real time and perform damage diagnosis in the entire structural domain. The iFEM formulation is based on the most widely used inverse element in this field, the inverse four-node shell (iQS4). First, the sensor placement model of the composite control arm is investigated by numerical iFEM/iQS4 analysis to embed the fiber Bragg grating sensors at optimal positions in the laminate. Then an experimental iFEM analysis (with physical sensor data) is performed to verify the numerical iFEM results, and a damage identification analysis is performed with the verified numerical strain data. In the final step, the numerical and experimental results are compared holistically to investigate the applicability of iFEM for vehicle components. The results of this comparison show the high precision of the real-time iFEM / iQS4 deformation reconstruction of the control arm and demonstrate the superior capabilities of damage detection and localization.
Item Type: | Article |
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Uncontrolled Keywords: | Composite Structures; Control Arm; Damage Detection; inverse finite element method; Shape Sensing; Structural Health Monitoring |
Divisions: | Faculty of Engineering and Natural Sciences Integrated Manufacturing Technologies Research and Application Center |
Depositing User: | Adnan Kefal |
Date Deposited: | 24 Sep 2025 14:37 |
Last Modified: | 24 Sep 2025 14:37 |
URI: | https://research.sabanciuniv.edu/id/eprint/52316 |