Abstract
In the present paper, the first three modal frequencies obtained through recorded vibration signal of a steel truss bridge is investigated at three different vehicular speeds. The denoising and extraction of modal frequencies from vibration response signals of steel truss bridge is performed using Hilbert transform (HT) in combination with high-frequency resolution enhancing techniques. The modal frequency extracting techniques applied includes Fast Fourier transform (FFT), multiple signal classification (MUSIC), and estimation of signal parameters by rotational invariance technique (ESPRIT). The comparisons of the outcomes of HT-FFT, HT-root-MUSIC, and HT- ESPRIT are computed. It is observed that HT-FFT computed results with the low resolution which hindered in obtaining distinct modal frequencies while HT-MUSIC and HT-ESPRIT achieved the most denoised, robust and reliable outcomes. The HT-ESPRIT outperforms HT-MUSIC in the elimination of unwanted noise. Further, the application of the sliding window HT-ESPRIT method clearly shows the variation of modal frequencies with the change in vehicular speeds. The first three analytical modal frequencies of 4.56 Hz, 10.44 Hz and 16.66 Hz frequencies are compared with the experimental frequencies obtained through vibrations at 10 km/h, 20 km/h and 30 km/h vehicular speeds, respectively. The joints (also denoted as nodes) 6, 7, and 8 exhibited irregular behaviour with no or minimum frequency peaks due to increased flexibility of member at these locations.
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Acknowledgement
The authors would like to thank the Himachal Pradesh Public Works Department, Government of Himachal Pradesh, India for allowing the National Institute of Technology, Hamirpur to conduct the experiment on the steel truss bridge in the state. The authors also thank Dr. Suresh Kumar Walia for providing necessary experimental data for further signal processing.
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The authors declare that there is no conflict of interest in the context of the publication of this manuscript. In addition, authors have carefully observed the ethical issues of plagiarism, misconduct, data falsification, or any misconduct while developing the article.
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Sharma, A., Kumar, P., Vinayak, H.K. et al. Identification of Joint Discrepancy in Steel Truss Bridge Using Hilbert Transform with root-MUSIC and ESPRIT Techniques. Int J Civ Eng 19, 653–668 (2021). https://doi.org/10.1007/s40999-020-00597-2
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DOI: https://doi.org/10.1007/s40999-020-00597-2