An experimental study on dynamic response of cement concrete pavement under vehicle load using IoT MEMS acceleration sensor network

Abstract

Understanding the dynamic response of pavements is crucial for comprehending pavement deformation and interaction mechanisms under vehicle load. There is a notable absence of monitoring systems that involve the in-situ embedding of acceleration sensors within full-scale cement concrete pavement slabs. This research introduces an IoT system designed for the monitoring of pavement vibration responses, with its deployment and installation executed within a field engineering project. By collecting and analyzing the pavement vibration responses to vehicle loads, the study investigates the time–frequency characteristics of vibration signals across various vehicle speeds, sensor depths, and lateral distances. The findings reveal that both the amplitude and main frequency of the vibration signal escalate with vehicle speed, whereas the embedding depth of the sensor impacts only the amplitude, leaving the main frequency unaffected. Through statistical analysis, it was determined that effective sensor spacing on cement concrete pavements should not exceed 120 cm to avoid significant signal attenuation, which on average reaches 50 % at a sensor spacing of 90 cm. These insights offer critical guidance for optimizing sensor layouts on cement concrete pavements and lay the foundation for future research on vibration-based damage detection and vehicle information analysis.