Sensor Integration in Asphalt for Data-Based Degradation Monitoring

In the research project presented here, the focus was on the design, manufacture, and incorporation of a hybrid fabric made of natural fibers, which can detect changes in the condition of the surrounding components by means of integrated sensor technology. The aim was to incorporate the functionalized fabric into the asphalt base layer of road pavements in order to detect structural damage to the layer. At the core of the fabric is a sensor material that is stretched by stresses and the electrical resistance is changed. The data obtained from the road is interpreted with the help of sensored test specimens loaded under laboratory conditions. In this way, signals and patterns can be assigned to the respective type of damage and its severity. This enables a statement to be made about the fatigue condition of the asphalt base layer without having to take samples on site. Furthermore, the condition can now be monitored continuously and over a large area. To this end, a software solution was developed that uses adapted machine learning methods to learn the relationship between an electrical voltage measured in the fabric and the condition of the asphalt base layer determined by load tests. With the aid of this software, the degradation state can then be interpreted exclusively from the data measured in the fabric and presented in the form of a few key figures. From this, appropriate recommendations for rehabilitation work can be derived directly in practical use.