Augmented reality facilitates field maintenance
To avoid unwanted standstill of machines in production environments, the industry developed the concept of ‘predictive maintenance’. Within this concept, wirelessly connected sensors help to identify faulty parts before they actually fail. They measure and transmit data that enable maintenance people to draw conclusions if gear wheels are ground down, ball bearings show unevenness or pipes are blocked. KIT scientist Matthias Berning now developed a concept that enables efficient fault diagnostics on the spot. His development visualises sensor measurement values such as vibration frequency, shock, or temperature of a component on the screen of a mobile computer or tablet.
The data are superimposed to the camera image of that machine. Connecting lines are showing the spot on the machine where the data have been measured and move around in the screen according to the moves of the tablet. A fingertip turns the figures into a graphical representation like charts or diagrams; in addition it is possible to drill down to get more information as needed. Typically, the data of several measurement points in complex equipment configurations need to be aligned to track down the cause of a problem. The direct spatial representation of the measurement data spares the user from laboriously associating sensors and components by means of part numbers or index characters.
The development, Bernings’ doctoral thesis at the KIT chair of Pervasive Computing Systems, gyrates around the question "How can the data gathered be utilised in the Human Machine Interface in a way that humans can interpret them?" The work has been conducted along with an industry partner, the ABB Research Centre. "The prototypes show clearly that utilising the data by linking them to camera images makes sense", Berning says. Since the Internet of Things generates huge amounts of data which are difficult to handle, it is essential to present a filtered subset of that data, where the filtering mechanism depends on the respective task, he added.
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German sensor industry bets hopes on IoT
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