Currently, the only factor that determines when a road needs new asphalt is the condition of the road surface itself. However, the condition of the asphalt layer underneath it is also an important indicator that has not been sufficiently considered so far. To assess it, only indirect measurement methods are available, which either only measure the surface or damage the road by drilling into it. A new monitoring system by Fraunhofer researchers and partners detects damage at an early stage and continuously monitors the condition of the underlying asphalt layer, comprehensively and without causing damage.
Sensors in the asphalt
The main component of the new solution is a network of sensors in the asphalt. AI algorithms to analyse the data are also part of the system. The researchers hope that the interaction between sensors and AI will help assess the condition of road structures in real time in the future.
Damage in asphalt caused by traffic and environmental factors
Roads are heavily stressed by traffic and environmental factors. In the long run, these factors lead to cracks and other defects in the asphalt. However, micro-cracks and damage to deeper layers cannot be observed with the naked eye. The current process for assessing the structural condition of the asphalt underlayer involves drilling a core sample. This is a destructive, time-consuming measurement method that further damages the road and requires road closures. This method is also limited to very localised use. In some cases, it leads to lengthy and ineffective repairs, as the full extent of damage is often not detected in time.
Smart measurement and analysis system
With all these factors at play, how can the road resurfacing planning process be made more sustainable and cost-effective, with longer-lasting results and less traffic disruption? Researchers from the Fraunhofer-Institut für Holzforschung, Wilhelm-Klauditz-Institut, WKI have teamed up with partners in the SenAD2 project to meet this challenge. They are developing a smart measurement and analysis system. The system can be used to monitor the condition of the asphalt underlayer in a non-destructive way, over a large area and on a continuous basis. This will enable planners to better address road surface renewal.
Determining and predicting wear on asphalt
The aim is that in the future, the system will make it possible to determine and predict the degree of wear of asphalt roads. "Our aim is to be able to plan over a longer period of time, continuously monitor changes in road condition and make forecasts based on these and integrate them into maintenance management," says Christina Haxter, research scientist at Fraunhofer WKI. "This will not make the roads last longer, but it will improve the monitoring of their condition."
Flax fibre interwoven with electrically conductive wire
The main component of the system is a fabric made of flax fibres and sensor components that is cheap to produce, so it can be used over large areas. The sensor wire has a diameter of less than a millimetre. It is incorporated directly into the natural fibre fabric during the weaving process, which is highly resistant to shifting or displacement. Thick, heavy yarns and wide gaps stabilise the material.
Tough conditions
"It must be designed in such a way that the structure in the asphalt is not affected. The sensors must also not be damaged during the weaving process or when the fabric is applied in the roadbed," Haxter explains. In addition, the fabric must be able to withstand the weight of trucks and asphalt pavers during construction work. The sensor fabric is produced using a double gripper loom from Fraunhofer WKI. The fabric is produced in a width of 50 centimetres, in any desired length. "The fabric is designed to withstand harsh conditions during installation and environmental conditions, as our initial tests have shown," Haxter explains.
Continuously measuring status of asphalt
Once embedded in the asphalt, the sensor fabric has the task of taking continuous measurements to draw conclusions about the internal condition of the asphalt underlay. The loads applied to roads create stress on the asphalt base layer, which also causes changes in the state of the electrically conductive sensors. As the sensor material expands, its electrical resistance also changes. This can be measured and the change in resistance can be related to damage to the asphalt base layer or to the condition of the road. The sensor wire is connected to a measuring unit at the roadside that stores the data and transmits the information to the analysis software.
Testing in industrial areas: As a first step, the sensor fabric is installed across the entire width of the road surface. (Photo: Fraunhofer WKI)
Digitalisation, sensors and AI for road maintenance
Another innovation of the project lies in the AI methods used to analyse asphalt underlay data. New calculation methods developed for this purpose determine the current condition of the road surface. They also predict the expected progression of damage. On this basis, road authorities can take the necessary road maintenance measures at an early stage. The data are visualised using an internet platform with a dashboard. This has also been developed as part of the project. The intention is to use the platform to prepare and make available all relevant information to government agencies, local residents, businesses, road users and other persons and entities affected by construction and maintenance works.
Tests in industrial area
After a successful first series of feasibility tests in the laboratory, tests are now being carried out with a demonstration model on a flat test track in an industrial area. The sensors are installed across the full width of the road surface. Measurement and analysis nodes record changes in resistance in the sensors when a vehicle passes over the demonstrator.
Opening photo: Once embedded in the asphalt, the sensor fabric is tasked with taking continuous measurements to draw conclusions about the internal condition of the asphalt underlayer. (Photo: © Fraunhofer WKI)
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