A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Monitoring structural health status of asphalt pavement using intelligent sensing technology
Highlights A method for estimating the global pavement health based on partial data is proposed. A new indexe is developed to accurately characterize the damage degree of pavement. SmartRock sensor can be used to monitor the stress changes within the cement mortar.
Abstract Pavement health monitoring (PHM) based on intelligent sensing technology is of great significance for road maintenance and management. This paper proposes a method for local damage monitoring and global health evaluation of pavement based on embedded wireless sensors. Firstly, 3D finite element (FE) models are employed to investigate the response characteristics of healthy and degraded pavement structures under moving loads, whereby an index DI is proposed to quantitatively evaluate the damage characteristics. In addition, three-point bending (TPB) fracture tests are carried out on cement mixture to investigate the effectiveness of Smartrock in monitoring crack propagation, and the results show that the stresses recorded by the sensors can be used to characterize the different stages of crack propagation. Further, a method for estimating the global stress distribution in pavement structure using the monitoring data obtained from a limited number of sensors is developed based on Kriging method. The test results show that the prediction accuracy decreases as the number of training sets decreases, but when the training sets account for 50% of the total, the correlation coefficient R2 between the predicted and true values is still more than 0.9 and the average relative error (ARRE) is less than 10%, and demonstrate that the interpolation method proposed in this paper can accurately evaluate the global stress distribution based on the monitoring data obtained from a limited number of sensors.
Monitoring structural health status of asphalt pavement using intelligent sensing technology
Highlights A method for estimating the global pavement health based on partial data is proposed. A new indexe is developed to accurately characterize the damage degree of pavement. SmartRock sensor can be used to monitor the stress changes within the cement mortar.
Abstract Pavement health monitoring (PHM) based on intelligent sensing technology is of great significance for road maintenance and management. This paper proposes a method for local damage monitoring and global health evaluation of pavement based on embedded wireless sensors. Firstly, 3D finite element (FE) models are employed to investigate the response characteristics of healthy and degraded pavement structures under moving loads, whereby an index DI is proposed to quantitatively evaluate the damage characteristics. In addition, three-point bending (TPB) fracture tests are carried out on cement mixture to investigate the effectiveness of Smartrock in monitoring crack propagation, and the results show that the stresses recorded by the sensors can be used to characterize the different stages of crack propagation. Further, a method for estimating the global stress distribution in pavement structure using the monitoring data obtained from a limited number of sensors is developed based on Kriging method. The test results show that the prediction accuracy decreases as the number of training sets decreases, but when the training sets account for 50% of the total, the correlation coefficient R2 between the predicted and true values is still more than 0.9 and the average relative error (ARRE) is less than 10%, and demonstrate that the interpolation method proposed in this paper can accurately evaluate the global stress distribution based on the monitoring data obtained from a limited number of sensors.
Monitoring structural health status of asphalt pavement using intelligent sensing technology
Wang, Ning (author) / Han, Tao (author) / Cheng, Hao (author) / Li, Tailin (author) / Fu, Jikai (author) / Ma, Tao (author) / Fu, Yongqiang (author) / Chen, Feng (author) / Zhang, Yang (author)
2022-08-29
Article (Journal)
Electronic Resource
English
Self-sensing intelligent conductive asphalt pavement material
| European Patent Office | 2021
Continuous health monitoring of pavement systems using smart sensing technology
| Online Contents | 2016
Continuous health monitoring of pavement systems using smart sensing technology
| British Library Online Contents | 2016
Continuous health monitoring of pavement systems using smart sensing technology
| British Library Online Contents | 2016