PSI - Issue 64

Ayaho Miyamoto et al. / Procedia Structural Integrity 64 (2024) 464–475 Author name / Structural Integrity Procedia 00 (2019) 000–000

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the occurrence of some kind of serious damage in the target bridge, and a warning is issued so that necessary actions such as detailed inspection can be taken immediately. Actions such as detailed inspection need to be taken immediately when “characteristic deflection” has reached a criterion level on the out-bound or in-bound route of the city bus. Furthermore, thinking of bus operating conditions that may affect “characteristic deflection” during the long-term observation, as external disturbance factors, the author tried to quantify the correlations between the bus operating conditions, namely weather, number of oncoming vehicles, number of persons on the vehicle and vehicle speed, and the “characteristic deflection” by using the first 5 years available data. Although certain degrees of influence of external disturbance factors (bus operating conditions described above) can be seen, it is yet not possible to quantify such influence in the absence of a clear tendency or a strong correlation (Yabe et al. (2015)) . As a result, it was concluded that at present it is not possible to reflect their correlations in conversion (correction) factors applicable to the bus operating conditions. It was therefore thought that the moving average method mentioned before would be useful in treating the influences of the external disturbance factors on the “characteristic deflection” as variances. 4. Usage for bridge maintenance strategies In order to realize a “Smart City” project (VTT Technical Research Centre of Finland Ltd. (2015)) in the future, the bus-based monitoring system conjunction with e-bus (Kostiainen et al. (2019)) will be able to become one of the key technologies for an innovative remote-based health monitoring system using of sensors attached to heavy transportation vehicles (i.e. buses) which is on one hand assess the condition of the road surface (i.e. bus vibration-response to road surface condition), and on the other the condition of the bridge (i.e. bridge vibration due to heavy dynamic load from bus). The data from these sensors is wirelessly stored into a cloud computer and a data analysis software is used to define a road surface index and a bridge deflection index such as “characteristic deflection”. Based on the calculated indices and how they vary with time, crucial data is generated to support the decision-making process with regards to maintenance actions. If we consider that all buses could easily and inexpensively be fitted with such a remote system and that driving bus routes several times a day and many days a year, an enormous amount of data is generated on the performance on the infrastructure through time. This situation compared to expensive periodic visual inspection of a select few infrastructure shows the double benefit such a system would provide the owners of infrastructure. Fig. 8 shows an image of how to use the bus-based monitoring system for road infrastructure management including the existing bridges on a bus route combined with the latest information processing technologies. In here, the project would also develop standard procedures for the assessment and prediction of road infrastructure performance, degradation and risk of structural damage based on the monitoring data. The project works in collaboration with multidisciplinary approach such as ICT, sensors, materials, mechanics, structural systems, etc., and focuses on the condition of road pavements and bridge structures. As shown in Fig. 8, for development of the long-term remote monitoring system for road infrastructure management/maintenance, the bus-based monitoring system would allow the real-time monitoring both of the condition of the road surface and the integrity of bridge for short and medium span bridges (shorter than 30 m span length) on the bus routes, perform necessary data analysis, and provide real-time indications on the needs for maintenance actions. On the other hand, to formulate standard procedures for the bridge assessment and prediction of its performance based on the monitoring data, load tests and inspection reports with the utilization of FEM, BIM and LCA methods, it needs to integrate the above-mentioned concept into the “smart city” such as integrating BIM and GIS into CityGML. 5. Conclusions The major results of this paper are summarized as follows: 1) The proposed method which is a new long-term monitoring method for short and medium span bridges using public buses as part of a public transit system (called bus-based monitoring system) with a safety index “characteristic deflection” was applied to an actual bus (bridge) network in Ube City area, Japan for more than 10 years as a specific example to verify its effectiveness. As the results, it will be able to make a rational long-term health monitoring system for existing short and medium span bridges, then the method helps bridge administrators to establish the rational maintenance strategies. 2) In order to observe long-term changes of “characteristic deflection” based on the accumulated monitoring data (big data) for 3 existing bridges on the in-service municipal bus network of Ube City, it has been proposed that