Monitoring and fault diagnosis of industrial wireless systems

Wireless systems are already used in a wide range of industrial areas – from intralogistics to assembly processes, tool control, and mobile robotics – and are rapidly becoming more widespread. Indeed, wireless communication is now considered an indispensable key technology in pioneering applications such as collaboration between mobile robots.

This increasingly important role in critical industry processes calls for wireless systems with a high degree of availability and reliability. At present, however, transmissions are often susceptible to interference due to varying propagation conditions, overloading, and neighboring wireless systems.

In this subproject, the ADA Lovelace Center is researching methods that allow reliable monitoring of wireless communication status and early detection of disruptions. Analysis is performed using machine learning methods that enable not only the continuous monitoring of wireless communications but also assessment of the status of all wireless connections. The resulting information on anomalies and faults allows connection problems to be rapidly detected and addressed.