Sensor systems for more efficiency on rail networks
Digital twins offer great opportunities for many areas of rail traffic. The realistic simulation of operational processes enables railway undertakings to become more efficient and customer-friendly. Smart sensor systems with their enormous computing capacities create the basic conditions for the use of digital twins.
The sensor systems from ASC GmbH in Pfaffenhofen, Bavaria, have been specifically developed for intelligent monitoring solutions such as condition monitoring and predictive maintenance in rail traffic. The main feature of these smart sensor systems is their ability to evaluate the collected data and to extract predefined feature vectors from them. In this way, such systems can make decisions and predictions on their own. Real-case simulations For rail transport, digital twins of trains, track layouts or buildings harbour a huge potential. Among other things they can generate physically correct live simulations of a railway system. In this way, they can, for example, calculate an optimised timetable or an ideal diversion route in the event of a traffic disruption. Moreover, digital twins can also be used to simulate the effects of changed routings. In this way, planners can anticipate any adverse effect on local residents and adjust routes accordingly. High computing power allows for operational optimisation Digital twins can furthermore help to optimise the maintenance of railway infrastructure. The enormous computing capacity of ASC’s smart sensor systems allows trains and tracks to be monitored in real time. As a result, any risk component can be detected and replaced before it is damaged – thus saving time and money. Simulation based on digital twins also has the advantage that different scenarios can be simulated in time-lapse and critical resources are thus saved in the process. As they can be perfectly adapted to any application, smart sensor systems are extremely powerful and will therefore provide the basis for these and other future-oriented applications.