Laurent, Philippe ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Systèmes microélectroniques intégrés ; Department of Electrical Engineering and Computer Science, Microsys Laboratory, University of Liè,ge, Liè,ge, Belgium
Bellier, Pierre ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Systèmes microélectroniques intégrés ; Department of Electrical Engineering and Computer Science, Microsys Laboratory, University of Liè,ge, Liè,ge, Belgium
Dupont, François ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Systèmes microélectroniques intégrés ; Department of Electrical Engineering and Computer Science, Microsys Laboratory, University of Liè,ge, Liè,ge, Belgium
Redouté, Jean-Michel ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Systèmes microélectroniques intégrés ; Department of Electrical Engineering and Computer Science, Microsys Laboratory, University of Liè,ge, Liè,ge, Belgium
Language :
English
Title :
Autonomous and wireless accelerometers for monitoring bridge stay cables
Publication date :
2026
Journal title :
IEEE Sensors Journal
ISSN :
1530-437X
eISSN :
1558-1748
Publisher :
Institute of Electrical and Electronics Engineers (IEEE)
Wu, Z., Nagayama, T., Dang, J., & Astroza, R. Experimental Vibration Analysis for Civil Engineering Structures. 2021
Abdulkarem, M., Samsudin, K., Rokhani, F. Z., & A Rasid, M. F. (2020). Wireless sensor network for structural health monitoring: A contemporary review of technologies, challenges, and future direction. Structural health monitoring, 19(3), 693-735.
Saidin, S. S., Jamadin, A., Abdul Kudus, S., Mohd Amin, N., & Anuar, M. A. (2022). An overview: The application of vibration-based techniques in bridge
Plevris, V., & Papazafeiropoulos, G. (2024). AI in Structural Health Monitoring for Infrastructure Maintenance and Safety. Infrastructures, 9(12), 225.
Biondi, F., Addabbo, P., Clemente, C., & Orlando, D. (2021, March). A new paradigm to observe early warning faults of critical infrastructures by micro-motion estimation from satellite SAR observations. Application to pre-collapse damage assessment of the Morandi bridge in Genoa (Italy). In EUSAR 2021; 13th European Conference on Synthetic Aperture Radar (pp. 1-5). VDE.
Long, A. E., Basheer, P. A. M., Taylor, S. E., Rankin, B. G., & Kirkpatrick, J. (2008, December). Sustainable bridge construction through innovative advances. In Proceedings of the Institution of Civil Engineers-Bridge Engineering (Vol. 161, No. 4, pp. 183-188). Thomas Telford Ltd.
Kamariotis, A., Chatzi, E., & Straub, D. (2023). A framework for quantifying the value of vibration-based structural health monitoring. Mechanical Systems and Signal Processing, 184, 109708.
He, Z., Li, W., Salehi, H., Zhang, H., Zhou, H., & Jiao, P. (2022). Integrated structural health monitoring in bridge engineering. Automation in construction, 136, 104168.
Wu, W. H., Chen, C. C., Lin, S. L., & Lai, G. (2023). A Real‐Time Monitoring System for Cable Tension with Vibration Signals Based on an Automated Algorithm to Sieve Out Reliable Modal Frequencies. Structural Control and Health Monitoring, 2023(1), 9343343.
Tsuchimoto, K., Narazaki, Y., Hoskere, V., & Spencer, B. F. (2021). Rapid postearthquake safety evaluation of buildings using sparse acceleration measurements. Structural Health Monitoring, 20(4), 1822-1840.
Zarbaf, S. E. H. A. M., Norouzi, M., Allemang, R., Hunt, V., Helmicki, A., & Venkatesh, C. (2018). Vibration-based cable condition assessment: A novel application of neural networks. Engineering Structures, 177, 291-305.conditions in cables. Journal of Sound and Vibration, 511, 116326.
“Uplift of the Lixhe bridge”, Bureau Greisch, Seraing, Liege, Belgium, 2018, Available: https://www.greisch.com/en/uplift-ofthe-lixhe-bridge-bureau-greisch-busy-to-analyse-the-stability-ofthe-structure/
Geuzaine, M., Foti, F., & Denoël, V. (2021). Minimal requirements for the vibration-based identification of the axial force, the bending stiffness and the flexural boundary
Kim, B. H., & Park, T. (2007). Estimation of cable tension force using the frequency-based system identification method. Journal of sound and Vibration, 304(3-5), 660-676.
Weng, J., Chen, L., Sun, L., Zou, Y., Liu, Z., & Guo, H. (2023). Fully automated and non-contact force identification of bridge cables using microwave remote sensing. Measurement, 209, 112508.
Ni, Y. Q., Wang, X. Y., Chen, Z. Q., & Ko, J. M. (2007). Field observations of rain-wind-induced cable vibration in cable-stayed Dongting Lake Bridge. Journal of Wind Engineering and Industrial Aerodynamics, 95(5), 303-328.
Sun, L., Chen, L., & Huang, H. (2022). Stay cable vibration mitigation: A review. Advances in Structural Engineering, 25(16), 3368-3404.
Jiang, C., Wu, C., Cai, C. S., & Xiong, W. (2020). Fatigue analysis of stay cables on the long-span bridges under combined action of traffic and wind. Engineering Structures, 207, 110212.
Guo, J., & Zhu, X. (2020). Field monitoring and analysis of the vibration of stay cables under typhoon conditions. Sensors, 20(16), 4520.
Bono, F. M., Polinelli, A., Radicioni, L., Benedetti, L., Castelli-Dezza, F., Cinquemani, S., & Belloli, M. (2025). Wireless Accelerometer Architecture for Bridge SHM: From Sensor Design to System Deployment. Future Internet, 17(1), 29.
Nguyen, K. D., Kim, J. T., & Park, Y. H. (2013). Long-term vibration monitoring of cable-stayed bridge using wireless sensor network. International Journal of Distributed Sensor Networks, 9(11), 804516.
Jana, D., Nagarajaiah, S., Yang, Y., & Li, S. (2022). Real-time cable tension estimation from acceleration measurements using wireless sensors with packet data losses: Analytics with compressive sensing and sparse component analysis. Journal of Civil Structural Health Monitoring, 1-19.
Giammarini, M., Isidori, D., Concettoni, E., Cristalli, C., Fioravanti, M., & Pieralisi, M. (2015, April). Design of wireless sensor network for real-time structural health monitoring. In 2015 IEEE 18th International Symposium on Design and Diagnostics of Electronic Circuits & Systems (pp. 107-110). IEEE.
Kurata, M., Kim, J., Lynch, J. P., Van Der Linden, G. W., Sedarat, H., Thometz, E., ... & Sheng, L. H. (2013). Internet-enabled wireless structural monitoring systems: development and permanent deployment at the New Carquinez Suspension Bridge. Journal of structural engineering, 139(10), 1688-1702.
Jeong, S., Lee, Y. J., Shin, D. H., & Sim, S. H. (2019). Automated real-time assessment of stay-cable serviceability using smart sensors. Applied Sciences, 9(20), 4469.
Zanelli, F., Castelli-Dezza, F., Tarsitano, D., Mauri, M., Bacci, M. L., & Diana, G. (2021). Design and field validation of a low power wireless sensor node for structural health monitoring. Sensors, 21(4), 1050.
López-Castro, B., Haro-Baez, A. G., Arcos-Aviles, D., Barreno-Riera, M., & Landázuri-Avilés, B. (2022). A systematic review of structural health monitoring systems to strengthen post-earthquake assessment procedures. Sensors, 22(23), 9206.
Sivagami, A., Jayakumar, S., & Kandavalli, M. A. (2020, October). Structural health monitoring using smart sensors. In AIP Conference Proceedings (Vol. 2281, No. 1). AIP Publishing.
Sonbul, O. S., & Rashid, M. (2023). Towards the structural health monitoring of bridges using wireless sensor networks: A systematic study. Sensors, 23(20), 8468.
Sazonov, E., Li, H., Curry, D., & Pillay, P. (2009). Self-powered sensors for monitoring of highway bridges. IEEE Sensors Journal, 9(11), 1422-1429.
Palagummi, S. V., & Yuan, F. G. (2017). An enhanced performance of a horizontal diamagnetic levitation mechanism–based vibration energy harvester for low frequency applications. Journal of Intelligent Material Systems and Structures, 28(5), 578-594.
Liu, Y., Voigt, T., Wirström, N., & Höglund, J. (2018). Ecovibe: On-demand sensing for railway bridge structural health monitoring. IEEE Internet of Things Journal, 6(1), 1068-1078.
Chen, Y., Qin, L., Zou, Y., Sun, L., Chen, L., & Chen, S. (2025). Simplification and improvement of cable tension identification based on effective vibration length estimated from multiple sensors located near one support. Measurement, 242(A), 115755.
Joris, L., Dupont, F., Laurent, P., Bellier, P., Stoukatch, S., & Redouté, J. M. (2019). An autonomous sigfox wireless sensor node for environmental monitoring. IEEE Sensors Letters, 3(7), 01-04.
Augustin, A., Yi, J., Clausen, T., & Townsley, W. M. (2016). A study of LoRa: Long range & low power networks for the internet of things. Sensors, 16(9), 1466.
Petajajarvi, J., Mikhaylov, K., Roivainen, A., Hanninen, T., & Pettissalo, M. (2015, December). On the coverage of LPWANs: range evaluation and channel attenuation model for LoRa technology. In 2015 14th international conference on its telecommunications (itst) (pp. 55-59). IEEE.
Texas Instruments, "Monopole PCB Antenna with Single or Dual Band Option" Application Report SWRA227E, 2017. [Online]. Available: https://www.ti.com/lit/an/swra227e/swra227e.pdf
Kummu, M., & Varis, O. (2011). The world by latitudes: A global analysis of human population, development level and environment across the north–south axis over the past half century. Applied geography, 31(2), 495-507.
European Commission, “PHOTOVOLTAIC GEOGRAPHICAL INFORMATION SYSTEM”, [Online]. Available:https://re.jrc.ec.europa.eu/pvg_tools/en/