Thousands of kilometres of pipelines with partly very dangerous substances conveyed under high pressure are currently still completely unmonitored. A technical solution from Fraunhofer IPA enables decentralised, energy-autonomous, simple leakage detection that can be monitored centrally using a cloud solution. This makes predictive maintenance possible, which reduces the repair effort and downtime. The use of the system is comparatively inexpensive and increases safety.
If abrasive materials, e.g. powder or fly ash, are transported in pipelines, sooner or later the pipelines will be damaged due to the abrasion that occurs. This can lead to contamination of the material flows or, in the worst case, to a serious safety risk, as well as causing enormous environmental damage. The Fraunhofer IPA has developed a system solution based on a modular sensor system for integration into pipe systems. Capacitive or resistive measuring methods can be used to measure damage to or changes in the pipe and it is possible to take action before the pipe is destroyed. The energy-autonomous system consists of various sensors, energy harvesters for supply, as well as a database for measurement data acquisition and processing. The sensors can be integrated in the manufacturing process of the pipes by means of pressure methods or they can be attached to the pipes afterwards. The evaluation electronics are based on SMD components that were manufactured by the Fraunhofer IPA within the framework of a circuit Electronic components that manage with low supply voltages and are therefore supplied by energy converters can use the energy available from the environment, e.g. from air, vibrations or temperature. The remaining wall thickness of the pipe up to the point of damage is measured. The energy-autonomous sensors are connected via a microcontroller to a central cloud database in which all status values are recorded. With little development effort, the online system is able to implement predictive maintenance with automated spare parts ordering.