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1716408PublishedVol 9 · Issue 10

System Identification of Truss Bridge Using Phyphox Mobile Application and Analytical Modeling in CSI Bridge

Kamal Prasad Bajagain Govinda Khatri

Subject area: Science,Engineering and Technology  ·  Area of research: Structural Health Monitoring of bridges.

DOI: https://doi.org/10.64388/IREV9I10-1716408

Abstract

This study presents an ambient vibration–based dynamic assessment of the Ghatte Khola steel truss bridge using a smartphone accelerometer and advanced vibration-based system identification techniques. Acceleration data were collected through the Phyphox mobile application under natural excitations such as vehicular traffic and wind. The recorded responses were analyzed in both time and frequency domains to extract key modal parameters, including natural frequencies, mode shapes, and damping ratios. To ensure accuracy and reliability, multiple system identification methods—Peak Picking (PP), Enhanced Frequency Domain Decomposition (EFDD), Autoregressive Moving Average (ARMA), and Stochastic Subspace Identification (SSI)—were employed, and their results showed strong consistency. A finite element model of the bridge was developed in CSI Bridge to simulate its dynamic behavior, and the numerical results were compared with experimental findings. The comparison revealed good agreement, with natural frequency discrepancies within 10%, indicating that the model effectively represents the actual structural behavior. The estimated damping ratios were approximately 3%, which is consistent with the typical range for steel truss bridges and reflects realistic energy dissipation characteristics. Overall, the findings demonstrate that smartphone-based vibration monitoring, when combined with robust modal identification techniques, provides a reliable, efficient, and cost-effective approach for structural health monitoring. This method is particularly beneficial for resource-limited regions like Nepal, offering a practical solution for bridge assessment and establishing a foundation for future development of low-cost structural monitoring systems.

Keywords

Smartphone Accelerometer, Fast Fourier Transform, System Identification, Finite Element Method

How to cite this paper

Kamal Prasad Bajagain, Govinda Khatri "System Identification of Truss Bridge Using Phyphox Mobile Application and Analytical Modeling in CSI Bridge" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 1738-1746 https://doi.org/10.64388/IREV9I10-1716408
Kamal Prasad Bajagain, Govinda Khatri "System Identification of Truss Bridge Using Phyphox Mobile Application and Analytical Modeling in CSI Bridge" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026, doi: https://doi.org/10.64388/IREV9I10-1716408
Kamal Prasad Bajagain, Govinda Khatri (2026). System Identification of Truss Bridge Using Phyphox Mobile Application and Analytical Modeling in CSI Bridge. Iconic Research And Engineering Journals, 9(10). doi: https://doi.org/10.64388/IREV9I10-1716408
Kamal Prasad Bajagain, Govinda Khatri "System Identification of Truss Bridge Using Phyphox Mobile Application and Analytical Modeling in CSI Bridge" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026. Crossref, https://doi.org/10.64388/IREV9I10-1716408
@article{1716408,
      author = {Kamal Prasad Bajagain, Govinda Khatri},
      title = {System Identification of Truss Bridge Using Phyphox Mobile Application and Analytical Modeling in CSI Bridge},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {1738-1746},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716408.pdf},
      abstract = {This study presents an ambient vibration–based dynamic assessment of the Ghatte Khola steel truss bridge using a smartphone accelerometer and advanced vibration-based system identification techniques. Acceleration data were collected through the Phyphox mobile application under natural excitations such as vehicular traffic and wind. The recorded responses were analyzed in both time and frequency domains to extract key modal parameters, including natural frequencies, mode shapes, and damping ratios. To ensure accuracy and reliability, multiple system identification methods—Peak Picking (PP), Enhanced Frequency Domain Decomposition (EFDD), Autoregressive Moving Average (ARMA), and Stochastic Subspace Identification (SSI)—were employed, and their results showed strong consistency. A finite element model of the bridge was developed in CSI Bridge to simulate its dynamic behavior, and the numerical results were compared with experimental findings. The comparison revealed good agreement, with natural frequency discrepancies within 10%, indicating that the model effectively represents the actual structural behavior. The estimated damping ratios were approximately 3%, which is consistent with the typical range for steel truss bridges and reflects realistic energy dissipation characteristics. Overall, the findings demonstrate that smartphone-based vibration monitoring, when combined with robust modal identification techniques, provides a reliable, efficient, and cost-effective approach for structural health monitoring. This method is particularly beneficial for resource-limited regions like Nepal, offering a practical solution for bridge assessment and establishing a foundation for future development of low-cost structural monitoring systems.},
      keywords = {Smartphone Accelerometer, Fast Fourier Transform, System Identification, Finite Element Method},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716408}
  }