In the research project "Microelectronics-based Universal Sensor Interface with Artificial Intelligence for Industry 4.0" (AI-MUSIC 4.0), the project partners are developing innovative approaches to process acoustic sensor data with AI. Among other things, the sensors can "hear" leaks and detect vibrations as structure-borne sound. In this way, they can provide important data for assessing the condition of the machine.
The collected sensor data will be directly analyzed in innovative chips using signal preprocessing and AI. In this way, each sensor unit could send condensed information on the status of the component to a controller or gateway: These would, for example, only receive the message that there is or is not a leak. This would save bandwidth and speed up condition monitoring. Intelligence would thus move even further in the direction of the components.
Recommendations for action could be derived from the analyzed data, for example, if the process quality is no longer being maintained and the plant should be stopped. This could lead to a new generation of intelligent, autonomous production systems.
Festo has the role of the user in the research project. Using various test setups and integrated sensor technology, we collect the data needed to teach the AI to detect leaks.