Avendano, J., Otero, L., & Otero, C. (2021). Optimization of Sensor Placement in a Bridge Structural Health Monitoring System. in 2021 IEEE International Systems Conference (SysCon) (pp. 1-5). IEEE.
Balageas, D., Fritzen, C.-P., & Güemes, A. (2010). Structural health monitoring. John Wiley & Sons.
Bullock, R., & Foltz, S. (1995). REMR Management Systems-Navigation and Reservoir Structures, Condition Rating Procedures for Concrete in Gravity Dams, Retaining Walls, and Spillways. CHAMPAIGN, IL: CONSTRUCTION ENGINEERING RESEARCH LAB (ARMY).
Chen, G.-W., Omenzetter, P., & Beskhyroun, S. (2021). Modal systems identification of an eleven-span concrete motorway off-ramp bridge using various excitations. Engineering Structures, 229.
Comisu, C.-C., Taranu, N., Boaca, G., & Scutaru, M.-C. (2017). Structural health monitoring system of bridges. Procedia Engineering, 199, 2054-2059.
Doebling, S., Farrar, C., Prime, M., & Shevitz, D. (1996). Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review.
Dorafshan, S., Campbell, L., Maguire, M., & Connor, R. (2021). Benchmarking Unmanned Aerial Systems-Assisted Inspection of Steel Bridges for Fatigue Cracks. Transportation Research Record, 2675(9), 154-166.
Farrar, C., S. W., D., & Nix, D. (2001). Vibration–based structural damage identification. In Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences (Vol. 359, pp. 131-149).
Flah, M., Nunez, I., Chaabene, W., & Nehdi, M. (2021). Machine learning algorithms in civil structural health monitoring: A systematic review. Archives of Computational Methods in Engineering, 28(4), 2621-2643.
Han, Q., Ma, Q., Xu, J., & Liu, M. (2021). Structural health monitoring research under varying temperature condition: a review. Journal of Civil Structural Health Monitoring, 11(1), 149-173.
Huang, H.-B., Yi, T.-H., Li, H.-N., & Liu, H. (2020). Strain-based performance warning method for bridge main girders under variable operating conditions. Journal of Bridge Engineering, 25(4).
Lin, J., Ibrahim, A., Sarwade, S., & Golparva, M. (2021). Bridge inspection with aerial robots: Automating the entire pipeline of visual data capture, 3D mapping, defect detection, analysis, and reporting. Journal of Computing in Civil Engineering, 35(2).
Modena, C., Tecchio, G., Pellegrino, C., da porto, F., Donà, M., Zampieri, P., & Zanini, M. (2015). Reinforced concrete and masonry arch bridges in seismic areas: typical deficiencies and retrofitting strategies. Structure and Infrastructure Engineering, 11(4), 415-442.
Moodi, F. (2001). Development of a knowledge-based system for the repair and maintenance of concrete structures. Newcastle university.
Obiechefu, C., & Kromanis, R. (2021). Damage detection techniques for structural health monitoring of bridges from computer vision derived parameters. Structural Monitoring and Maintenance, 8(1).
Quirk, L., Matos, J., Murphy, J., & Pakrashi, V. (2018). Visual inspection and bridge management. Structure and Infrastructure Engineering, 14(3), 320-332.
Reagan, D., Sabato, A., & Niezrecki, C. (2018). Feasibility of using digital image correlation for unmanned aerial vehicle structural health monitoring of bridges. Structural Health Monitoring, 17(5), 1056-1072.
Rizzo, P., & Enshaeian, A. (2021). Challenges in bridge health monitoring: A review. Sensors, 21(13).
Saleem, M., Park, J.-W., Lee, J.-H., Jung, H.-J., & Sarwar, M. (2021). Instant bridge visual inspection using an unmanned aerial vehicle by image capturing and geo-tagging system and deep convolutional neural network. Structural Health Monitoring, 20(4), 1760-1777.
Secretary of Transportation. (2004). National bridge inspection standards (NBIS). Washington D.C.: FHWA.
Vagnoli, M., Remenyte-Prescott, R., & Andrews, J. (2018). Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges. Structural Health Monitoring, 17(4), 971-1007.
Wang, X., Gao, Q., & Liu, Y. (2020). Damage detection of bridges under environmental temperature changes using a hybrid method. Sensors, 20(14).
Zanini, M., Faleschini, F., & Pellegrino, C. (2017). Bridge residual service-life prediction through Bayesian visual inspection and data updating. Structure and Infrastructure Engineering, 13(7), 906-917.
Zhu, Y., Ni, Y.-Q., Jesus, A., Liu, J., & Laory, I. (2018). Thermal strain extraction methodologies for bridge structural condition assessment. Smart Materials and Structures, 27(10).
