| Title |
Extraction of Foundational Data for Database Construction in Overloaded Vehicle Monitoring |
| Authors |
방건혁(Bang, GeonHyeok);이재훈(Lee, JaeHoon);전승곤(Jeon, SeungGon);허광희(Heo, GwangHee) |
| DOI |
https://doi.org/10.12652/Ksce.2026.46.1.0029 |
| Keywords |
과중차량 모니터링; 관리정보; 과중차량; 데이터베이스 Overloaded vehicle monitoring; Management information; Overloaded vehicle; Database |
| Abstract |
In this study, management information was extracted from overweight vehicles crossing an in-service bridge with the aim of establishing a database for long-term overweight vehicle monitoring. The target vehicles were limited to 3-axle and 4-axle freight trucks whose load distribution characteristics are similar to those of the standard design truck load (KL-510) specified in the Korean design code. The management information was defined as fundamental vehicle-level data that can be calculated and stored for overweight vehicle management, and includes the number of axles, traveling speed, individual axle loads, gross vehicle weight, and axle spacing. To ensure stable extraction of the management information, an overweight vehicle detection criterion based on axle-number-dependent load distribution characteristics was established. This criterion was employed as a primary filtering step to identify vehicles with a high likelihood of being subject to management among continuously passing traffic. Through this process, responses induced by passenger cars and light- to medium-duty vehicles were effectively excluded, enabling the systematic extraction of management information for
overweight vehicles traveling in real time on the in-service bridge. The proposed management information extraction method was validated under a specific bridge type and strain measurement environment, and its capability to reliably reflect the operational characteristics of overweight vehicles was confirmed. However, rather than presenting a universally applicable detection criterion for all vehicle types and bridge conditions, the results of this study should be interpreted as a case study that experimentally demonstrates the feasibility of structuring overweight vehicle management information from a database construction perspective under similar conditions. The management information obtained in this study is expected to serve as fundamental data for future applications such as bridge fatigue damage assessment, overweight and overspeed enforcement, and the development of an overweight vehicle management database. |