In the Industry 4.0 environment, condition monitoring and predictive maintenance have become central pillars of an increasingly efficient and resource-saving production system. These processes involve frequent measurements of vibrations (structure-borne sound), as well as oil particles, temperatures, and other physical parameters. As far as structure-borne sound waves are concerned, existing techniques are almost entirely restricted to the range of audible sound. The partners involved in the Sonorion project hope to address this issue, significantly expanding the frequency range detected by this technology. Ultimately, their goal is to cover and analyze the entire frequency range from 20 Hz to several hundred kHz.
The project will aim to meet the demand for various developments in sensor technology in the Industry 4.0 environment, including extremely broadband integrated sensors allowing straightforward deployment in industrial production thanks to the use of self-learning algorithms. Another goal is to strengthen the European microelectronics industry by employing semiconductor technologies developed and produced in Germany for the development of the sensors.
Extremely broadband sensor technology in conjunction with an adaptable yet cost-effective microelectronics solution will pave the way for successful accomplishment of the project goals. Specifically, the project partners are working on:
- sensor modules with sensor-oriented intelligence,
- condition monitoring systems for automation components,
- and new, flexible methods for the development of integrated circuit components.
To this end, they will focus on the creation of a scalable, simple to operate, cost-effective, versatile hardware platform in combination with an easily adaptable software framework for extremely broadband structure-borne sound monitoring. In contrast to solutions for special frequency ranges, a versatile combination of sensor technology and electronics will tackle complex problems across a previously unattainable frequency range.
Furthermore, the project will explore a condition-monitoring strategy focusing on simultaneous monitoring of an extremely broad frequency range for vibration signals, and the associated complexity of the subsequent signal analysis. A system of this sort is subject to very different requirements depending on the use case. Accordingly, the sensor front end must be able to react dynamically to the use case and, where required, adjust parameters such as resolution or speed while maintaining the same level of precision.