Smartphone Application for Structural Health Monitoring of Stay Cables

Abstract

App4SHM is a mobile system for structural health monitoring (SHM) of bridges that aims to support routine inspections. It consists of a front-end smartphone application that is used to measure natural frequencies of vibration and to detect damage supported by a backstage server software, accessible through any internet browser. This paper focuses on the new module for stay cables, which directly converts natural frequencies into cable tension forces based on the cable's material and geometrical characteristics. The conversion uses an estimate of the forces from the taut-string theory. Regardless of the module, App4SHM works in two modes. The training mode is used to collect observations composed of natural frequencies under normal operational and environmental conditions. The observations are used to train an unsupervised machine learning algorithm to learn the structure's normal behavior. The damage detection mode collects unlabeled observations, which are tested against normal behavior to detect abnormal performance that may be indicative of damage or excessive tension. The Edgar Cardoso Bridge — a large cable-stayed bridge in Portugal, undergoing rehabilitation and stay cables replacement — is used as a case study for the measurement of cable tension forces.

Keywords

bridges / structural health monitoring / smartphones / stay cables / App4SHM / cable tension estimation

Conflict of interest

All the authors disclosed no relevant relationships.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Xia, upon reasonable request.

Acknowledgements

The authors acknowledge the support given by Pedro Cabral from Armando Rito Engenharia and Infraestruturas de Portugal, the bridge owner.

Funding

The authors acknowledge the financial support of the Foundation for Science and Technology (FCT, https://ror.org/00snfqn58) through Grant UID/6438/2025 (https://doi.org/10.54499/UID/06438/2025) of the research unit CERIS.

References

[1] Figueiredo, E.; Brownjohn, J. Three decades of statistical pattern recognition paradigm for SHM of bridges. Structural Health Monitoring 2022, 21, 3018-3054, doi:10.1177/14759217221075241.

[2] Tantaroudas, N.D.; Zamora-Sanchez, D.; Armijo, J.A.; López-Villarragut, E.; Arakistain, I.; Katika, T.; Tsimiklis, G.; Amditis, A. A crowdsensing platform for structural health monitoring of rural bridge infrastructure. Open Research Europe 2026, 6, doi:10.12688/openreseurope.22915.1.

[3] Figueiredo, E.; Moldovan, I.; Alves, P.; Rebelo, H.; Souza, L. Smartphone Application for Structural Health Monitoring of Bridges. Sensors (Basel) 2022, 22, doi:10.3390/s22218483.

[4] Patra, A.K.; Singh, A.K. Role of Smart Sensor in Internet of Things for Structural Health Monitoring of Composite Structures. In Artificial Intelligence, Geographic Information Systems, and Multi-Criteria Decision-Making for Improving Sustainable Development, 1st ed.; Auerbach Publications: New York, 2025; pp. 154-176.

[5] Li, D.; Li, B.; Wang, T.; Zhang, J. Lightweight structural health monitoring and safety evaluation: Review and case studies. Advances in Structural Engineering 2025, 28, 2157-2179, doi:10.1177/13694332251325043.

[6] Nepomuceno, D.T.; Vardanega, P.J.; Tryfonas, T.; Pregnolato, M.; Bennetts, J.; Webb, G. A survey of emerging technologies for the future of routine visual inspection of bridge structures. In Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability; CRC Press: London, 2022; pp. 846-854.

[7] Sadhu, A.; Peplinski, J.E.; Mohammadkhorasani, A.; Moreu, F. A Review of Data Management and Visualization Techniques for Structural Health Monitoring Using BIM and Virtual or Augmented Reality. Journal of Structural Engineering 2023, 149, doi:10.1061/(asce)st.1943-541x.0003498.

[8] Ozer, E.; Kromanis, R. Smartphone Prospects in Bridge Structural Health Monitoring, a Literature Review. Sensors (Basel) 2024, 24, doi:10.3390/s24113287.

[9] Matarazzo, T.; Vazifeh, M.; Pakzad, S.; Santi, P.; Ratti, C. Smartphone data streams for bridge health monitoring. X International Conference on Structural Dynamics (Eurodyn 2017) 2017, 199, 966-971, doi:10.1016/j.proeng.2017.09.203.

[10] Duan, J.; He, W.; Xu, S.; Zhong, Z.; Huang, L. Smartphone-Based and Data-Driven Superstructure State Prediction Method for Highway Bridges in Service. Sensors (Basel) 2022, 22, doi:10.3390/s22155620.

[11] Mcsweeney, N.; Ghiasi, R.; Malekjafarian, A.; Ozer, E. Extracting Bridge Modal Frequencies Using Stationary Versus Drive-By Modes of Smartphone Measurements. Infrastructures 2024, 9, doi:10.3390/infrastructures9120218.

[12] Li, Z.K.; Lan, Y.F.; Lin, W.W. Footbridge damage detection using smartphone-recorded responses of micromobility and convolutional neural networks. Automation in Construction 2024, 166, doi:10.1016/j.autcon.2024.105587.

[13] Matarazzo, T.J.; Kondor, D.; Milardo, S.; Eshkevari, S.S.; Santi, P.; Pakzad, S.N.; Buehler, M.J.; Ratti, C. Crowdsourcing bridge dynamic monitoring with smartphone vehicle trips. Communications Engineering 2022, 1, doi:10.1038/s44172-022-00025-4.

[14] Eshkevari, S.S.; Cronin, L.; Pakzad, S.; Matarazzo, T. Bridge structural health monitoring using asynchronous mobile sensing data. arXiv preprint 2020, doi:10.48550/arXiv.2007.09249.

[15] Awadallah, O.; Grolinger, K.; Sadhu, A. Augmented reality-based smart structural health monitoring system with accurate 3D model alignment. Journal of Infrastructure Intelligence and Resilience 2026, 5, doi:10.1016/j.iintel.2025.100186.

[16] Tijani, I.A.; Wakjira, T.G.; Alam, M.S.; Uddin, N. Digital Image Correlation (DIC) for Structural Health Monitoring of Bridge Systems: A State-of-the-Art Review with Future Research Directions. Archives of Computational Methods in Engineering 2025, 1-17, doi:10.1007/s11831-025-10459-6.

[17] Du, W.K.; Lei, D.; Zhu, F.P.; Bai, P.X.; Zhang, J. A non-contact displacement measurement system based on a portable smartphone with digital image methods. Structure and Infrastructure Engineering 2024, 20, 1322-1340, doi:10.1080/15732479.2022.2141268.

[18] Mousa, M.A.; Yussof, M.M.; Udi, U.J.; Nazri, F.M.; Kamarudin, M.K.; Parke, G.A.R.; Assi, L.N.; Ghahari, S.A. Application of Digital Image Correlation in Structural Health Monitoring of Bridge Infrastructures: A Review. Infrastructures 2021, 6, doi:10.3390/infrastructures6120176.

[19] Peddle, J.; Goudreau, A.; Carson, E.; Santini-Bell, E. Bridge displacement measurement through digital image correlation. Bridge Structures 2011, 7, 165-173.

[20] Sarmadi, H.; Entezami, A.; Yuen, K.V.; Behkamal, B. Review on smartphone sensing technology for structural health monitoring. Measurement 2023, 223, doi:10.1016/j.measurement.2023.113716.

[21] Figueiredo, E.; Moldovan, I.; Peres, N.; Pinto, S.; Alves, P.; Cabral, P. Smartphone application for structural health monitoring of stay cables: Edgar Cardoso Bridge. In Proceedings of the Proceedings of the EWSHM, 2024.

[22] Zhang, X.C.; Porro, R.P.; Xu, J.M.; Zhu, H.H.; Li, Z.L. A review of smartphone sensing for structural health monitoring. Journal of Civil Structural Health Monitoring 2026, 16, doi:10.1007/s13349-025-01037-2.

[23] Porto. Determinação das forças instaladas nos tirantes da Ponte Edgar Cardoso na Figueira da Foz; Porto: 2021.

[24] Rito, A.; Cabral, P.; Xavier, L.; Abecasis, T. O projecto de substituição dos tirantes da Ponte Edgar Cardoso. Reabilitar & Betão Estrutural 2020.

[25] Koščo, T.; Margetin, M.; Chmelko, V.; Šulko, M. Bridge cable tension estimation using the vibration method. Structures 2024, 63, doi:10.1016/j.istruc.2024.106332.