PSI - Issue 64

Kun Feng et al. / Procedia Structural Integrity 64 (2024) 596–603 Kun Feng et al. / Structural Integrity Procedia 00 (2019) 000 – 000

602

7

Fig. 6. Damage scenario located at 5 m, (a) ODS, (b) squared errors.

To evaluate the precision of the proposed algorithm in localizing damage, Fig. 7 displays the squared errors for damage scenarios located at 1/3, 1/2, and 2/3 of the span, corresponding to 5 m 7.5 m, and 10 m, respectively. The results, as illustrated in Fig. 7, demonstrate commendable performance, with relative errors of 7.3%, -3.5%, and -0.9% for the 7.5 m location, and 7.8%, 8.8%, and 0.6% for the 10 m location, across the 10%, 20%, and 30% crack damage levels, as detailed in Fig. 7(b) and Fig. 7(c). The findings from Fig. 7 affirm the potential of the proposed algorithm to accurately locate bridge damage, showcasing its practical viability.

Fig. 7. Squared errors for damage scenarios, located at (a) 5 m, (b) 7.5 m, (c) 10 m.

5. Conclusions This paper introduces a novel approach: the bus network-based drive-by fleet monitoring framework for bridge health assessment. The effectiveness of this proposed method in identifying and localizing bridge damage has been explored, with preliminary findings demonstrating significant accuracy in detecting and acceptable accuracy in localizing the site of crack damage. While experimental validation using field data is currently in progress, future research will address challenges related to modelling inaccuracies within the vehicle fleet. Additionally, attention will be given to refining the techniques for extracting responses at contact points and mitigating the adverse effects of measurement noise on the drive-by data. Acknowledgements This research is supported by the Engineering and Physical Sciences Research Council (EPSRC) Prosperity Partnerships. EPSRC Reference: EP/S036695/1; Title: Roadmaps to Zero Net Emissions in Urban Public Transport.