Integrated Sensors for Intelligent Large-Size Bearings (ISiG)

• Applicants: Professor Dr.-Ing. Max Marian; Professor Dr.-Ing. Bernhard Wicht; Professor Dr.-Ing. Marc Christopher Wurz
• Subject Area: Engineering Design, Machine Elements, Product Development ; Microsystems
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 466778958

In the context of advancing digitalization, mechanical components and systems are being further developed into intelligent, mechatronic systems. These combine sensors, actuators and information processing with predictive, networked and self-acting components. In addition to the planning of maintenance or repair intervals, this enables self-diagnosis and self-regulation as well as the autonomous, demand- and energy-efficient control of unsteady processes. The reliable recording of meaningful process and status data by suitable sensors, on the basis of which decisions are made for the system, is of great importance. As part of the DFG priority program 2305 "Sensor-integrating machine elements", the potential of digitalization is to be made accessible. In addition to sensor integration, energy generation concepts, data processing and signal transmission are also to be solved. The overall aim of the planned project is to develop an intelligent, sensor-integrated slewing bearing that detects impending damage at an early stage so that downtimes can be avoided, maintenance intervals optimized and the operating parameters adapted to the measured load spectrum. To this end, the findings of the sensor-integrated axial cylindrical roller bearing prototype from the first funding period are to be transferred to a large radial roller bearing (NU 256), which is used in wind turbines, for example. Sensor integration by means of direct deposition of thin-film strain gages and temperature sensors on the surfaces of the bearing rings, including electronics integrated in the large radial roller bearing, creates a condition monitoring system that records forces, temperature and rotational speed without increasing the installation space. By using the evaluation electronics, the data is pre-processed and compressed using suitable algorithms, which significantly reduces the energy requirement. The data is then transmitted wirelessly to a server through the housing via a Bluetooth interface. Existing over-the-air update protocols (OTA) for Bluetooth Low Energy 5.0 are used to update the integrated sensor system, enabling wireless firmware updates. The energy self-sufficiency of the electronics is ensured with the help of an inductive energy harvester in the slewing bearing. The sensor-integrated radial slewing bearing is integrated into the test bench for functional tests. The system is subjected to load collectives and long-term tests in order to optimize the reliability of the sensor technology, the evaluation electronics and the energy harvesting. In the future, sensor-integrated rolling bearings can be manufactured and used energy self-sufficiently in wind turbines, for example, in order to increase safety through intelligent condition monitoring and minimize downtimes through operating parameter control.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2305: Sensor-Integrated Machine Elements pave the way for Widespread Digitalization
• Co-Investigators: Dr.-Ing. Florian Pape; Professor Dr.-Ing. Gerhard Poll