Results 21 to 30 of about 144 (95)
Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 30, Page 6201-6216, 19 December 2025.Abstract Heavy goods vehicles (HGVs) have a significant impact on road and bridge infrastructure, with overloaded vehicles accelerating structural deterioration and increasing safety risks. Bridge weigh‐in‐motion (B‐WIM) systems estimate gross vehicle weight (GVW) using strain measurements, but inaccuracies in axle configuration recognition can reduce ...
Domen Šoberl +7 more
wiley +1 more source
Low‐complexity real‐time detection Transformer for identifying bridge vehicle loads
Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 26, Page 4485-4506, 7 November 2025.Abstract Vehicle load identification (VLI) is pivotal for bridge health monitoring, safety assessment, and intelligent maintenance. However, computer vision‐based VLI is confronted by two critical challenges, that is, compromised identification accuracy under dynamic scene and computational constraints imposed by edge monitoring devices. To this end, a
Longfei Chang +7 more
wiley +1 more source
Detection of lifted axles on heavy vehicles and preservation of road infrastructures (Seto Project)
ce/papers, Volume 8, Issue 5, Page 113-119, October 2025.Abstract Detecting the use of lifted axles on heavy goods vehicles (HGV) is a major challenge to enforce weight regulation and to assess road infrastructure damages under moving loads. If some axles are lifted on HGVs, the gross vehicle mass is concentrated on less axles, which increases significantly the aggressiveness of these HGVs.
Dimitri Daucher +3 more
wiley +1 more source
Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 20, Page 2992-3012, 18 August 2025.Abstract For existing bridge weigh‐in‐motion technologies, the main challenge in accurate weight estimation is to overcome the difficulty of identifying the closely spaced axles. To do so, many field test data are generally required for each bridge in application. To address such a challenge, a novel two‐level sequential artificial neural network (ANN)
Wangchen Yan +3 more
wiley +1 more source
A vision‐based weigh‐in‐motion approach for vehicle load tracking and identification
Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 11, Page 1466-1489, 30 April 2025.Abstract With the rapid increase in the number of vehicles, accurately identifying vehicle loads is crucial for maintaining and operating transportation infrastructure systems. Existing load identification methods typically rely on collecting vehicle load data from weigh‐in‐motion (WIM) systems when vehicles pass over them.
Phat Tai Lam +6 more
wiley +1 more source
Engineering Reports, Volume 7, Issue 1, January 2025.The research framework provides a logical sequence for investigating various aspects of structural components, encompassing data processing, sub‐parameter determination, clustering analysis, threshold establishment, performance evaluation, regression analysis, and timing prediction for bridge systems.
Chengzhong Gui +5 more
wiley +1 more source
Structural Control and Health Monitoring, Volume 2025, Issue 1, 2025.In the realm of structural health monitoring (SHM) of bridge structures, the accurate reconstruction of girder‐end displacement (GED) is crucial for identifying potential structural damage and ensuring the monitoring system’s reliability. A novel fine‐grained spatial (FGS) attention mechanism, combined with efficient channel attention (ECA), has been ...
Guang Qu +4 more
wiley +1 more source
Structural Control and Health Monitoring, Volume 2025, Issue 1, 2025.Bridge structural health monitoring (BSHM) has consistently been a research hotspot in civil engineering. The field of BSHM has experienced a significant transition from traditional manual inspections to an advanced integration of artificial intelligence (AI), culminating in the current peak with data‐driven AI methodologies.
Yunchao Tang +5 more
wiley +1 more source