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Modal Identification of a Bridge Using the Vibration Response of a Passing Vehicle Combining VMD and TKEO
https://orcid.org/http://orcid.org/0000-0003-2684-6082
The majority of the vibration-based structural health monitoring techniques require modal parameter estimation. Recently, modal identification using indirect measurements is being developed and investigated as it avoids elaborate and laborious tasks associated with placing sensors on the structure and data acquisition systems and thereby reducing initial as well as recurring costs. Apart from this, multiple bridges can be scanned using the instrumented vehicle in a shorter time, saving considerable time in the modal parameter estimation of bridges. However, it is extremely challenging to estimate the modal parameters using the vibration responses from the vehicle moving over the bridge. The measured dynamic responses from the instrumented vehicle include components associated with the bridge, vehicle as well as driving frequencies apart from the disturbances associated with the bridge surface roughness. Therefore, isolating the bridge frequencies from the mix of all these frequency components is rather difficult. In this paper, efforts are made to devise a new modal parameter estimation technique using the combination of variational mode decomposition with the Teager–Kaiser energy operator. The vehicle-bridge interaction system employed in the present investigations idealizes the vehicle as a quarter car and the bridge as a beam. Parametric studies have been carried out to test the sensitivity of the proposed algorithm to the measurement noise, vehicle speed, and road surface roughness during signal decomposition as well as modal identification. The studies presented in this paper confirm that the proposed method can identify bridge mode shapes and frequencies with good accuracy by extracting bridge-related components from the instrumented vehicle body responses.
Modal Identification of a Bridge Using the Vibration Response of a Passing Vehicle Combining VMD and TKEO
https://orcid.org/http://orcid.org/0000-0003-2684-6082
The majority of the vibration-based structural health monitoring techniques require modal parameter estimation. Recently, modal identification using indirect measurements is being developed and investigated as it avoids elaborate and laborious tasks associated with placing sensors on the structure and data acquisition systems and thereby reducing initial as well as recurring costs. Apart from this, multiple bridges can be scanned using the instrumented vehicle in a shorter time, saving considerable time in the modal parameter estimation of bridges. However, it is extremely challenging to estimate the modal parameters using the vibration responses from the vehicle moving over the bridge. The measured dynamic responses from the instrumented vehicle include components associated with the bridge, vehicle as well as driving frequencies apart from the disturbances associated with the bridge surface roughness. Therefore, isolating the bridge frequencies from the mix of all these frequency components is rather difficult. In this paper, efforts are made to devise a new modal parameter estimation technique using the combination of variational mode decomposition with the Teager–Kaiser energy operator. The vehicle-bridge interaction system employed in the present investigations idealizes the vehicle as a quarter car and the bridge as a beam. Parametric studies have been carried out to test the sensitivity of the proposed algorithm to the measurement noise, vehicle speed, and road surface roughness during signal decomposition as well as modal identification. The studies presented in this paper confirm that the proposed method can identify bridge mode shapes and frequencies with good accuracy by extracting bridge-related components from the instrumented vehicle body responses.
Modal Identification of a Bridge Using the Vibration Response of a Passing Vehicle Combining VMD and TKEO
https://orcid.org/http://orcid.org/0000-0003-2684-6082
The majority of the vibration-based structural health monitoring techniques require modal parameter estimation. Recently, modal identification using indirect measurements is being developed and investigated as it avoids elaborate and laborious tasks associated with placing sensors on the structure and data acquisition systems and thereby reducing initial as well as recurring costs. Apart from this, multiple bridges can be scanned using the instrumented vehicle in a shorter time, saving considerable time in the modal parameter estimation of bridges. However, it is extremely challenging to estimate the modal parameters using the vibration responses from the vehicle moving over the bridge. The measured dynamic responses from the instrumented vehicle include components associated with the bridge, vehicle as well as driving frequencies apart from the disturbances associated with the bridge surface roughness. Therefore, isolating the bridge frequencies from the mix of all these frequency components is rather difficult. In this paper, efforts are made to devise a new modal parameter estimation technique using the combination of variational mode decomposition with the Teager–Kaiser energy operator. The vehicle-bridge interaction system employed in the present investigations idealizes the vehicle as a quarter car and the bridge as a beam. Parametric studies have been carried out to test the sensitivity of the proposed algorithm to the measurement noise, vehicle speed, and road surface roughness during signal decomposition as well as modal identification. The studies presented in this paper confirm that the proposed method can identify bridge mode shapes and frequencies with good accuracy by extracting bridge-related components from the instrumented vehicle body responses.
Modal Identification of a Bridge Using the Vibration Response of a Passing Vehicle Combining VMD and TKEO
J. Inst. Eng. India Ser. A
Srinivas, A. (author) / Lakshmi, K. (author)
Journal of The Institution of Engineers (India): Series A ; 105 ; 603-618
2024-09-01
16 pages
Article (Journal)
Electronic Resource
English
Bridge modal identification from ambient vibration measurements
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