Sensor-integrating elastomer bearing (SiEla) with combined sensor-generator-system

• Applicants: Professor Dr.-Ing. Jürgen Maas; Professor Dr.-Ing. Merten Stender
• Subject Area: Engineering Design, Machine Elements, Product Development
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 578410237

Despite advances in the digitalization of machine systems, integrated data collection remains a challenge. In this context, sensor-integrated machine elements (SiMe) and IoT technologies allow the wireless acquisition of condition data in real time. This research project aims to integrate an energy self-sufficient sensor system with wireless communication into standardized hollow elastomer bearings in order to record vibration variables of the overall system to be supported. The aim is to seamlessly integrate energy-autonomous sensor systems with communication capabilities into these bearings to transmit sensor data wirelessly even under harsh operating conditions. The focus here is on the development and system integration of an inductive measuring system that estimates the dynamic deformation of the bearing in combined sensor-generator mode and simultaneously harvests energy from the movement. The functionality of the sensor component has already been proven, so the fundamentally new aspect is the combination in sensor-generator mode, which requires a pareto-optimal weighting of energy generation versus sensing quality. The scientific aims focus on autonomous operation, energy management, signal processing and feature extraction, and wireless data transmission and update capability, without restricting the primary function of the machine element. The project aims to experimentally proof of a SiEla prototype’s reliability in mechatronic systems under temperature influence. The anticipated benefits of this technology are considered significant. The resulting sensor-integrated elastomer bearings (SiEla) offer a simple and minimally invasive retrofitting option for IoT sensor technology in various fields such as production technology, materials handling, machine support, and transportation. Subsequent data analysis promises extended operating times, reduced maintenance costs, and a contribution to the digitization of machine elements. The interdisciplinary research team contributes the necessary expertise and resources to successfully execute the project. The location of both applicants at TU Berlin promotes interdisciplinary exchange and minimizes implementation risks.

• DFG Programme: Research Grants