Research on Intelligent Monitoring Technology of Municipal Road and Bridge Engineering Construction and Quality

Abstract

Abstract This study addresses quality control challenges in municipal road and bridge construction by introducing an intelligent monitoring approach. Utilizing three-dimensional laser scanning, we monitor roadbed settlement and deformation accurately. Compaction quality is assessed through vibration acceleration metrics from milling operations, applying a compaction monitoring value. Furthermore, a combination of regression models and stochastic processes in a Kriging function model evaluates the reliability of detecting bridge steel corrosion. In J city’s political road bridge analysis, we observed a differential settlement with the least affected areas showing subsidence within 250mm. In contrast, the most impacted point, B1, recorded a settlement of 2597mm in December. Compaction quality monitoring revealed that control error margins for E and CV indicators lie between −2.65% to 2.35% and −2.7% to 2.6%, respectively, demonstrating a narrower error range for E compared to CV.