Sensor integrating plain bearings: design of an energy-autonomous, temperature-based condition monitoring system

Plain bearings are increasingly being used under mixed friction, resulting in a higher risk of wear-induced failure. Therefore, the relevance of condition monitoring is increasing, which can enable the early detection of wear inducing conditions. The presented work focuses on the development of an energy-autonomous, temperature-based condition monitoring system for plain bearings. The components of the condition monitoring system are to be integrated directly into the machine element and operating data to be transmitted wirelessly.The fundamental monitoring approach pursued, is the in-operando calculation of the lubrication gap height via the standardized Gümbel-curve based on the temperature map in the plain bearing. If the gap height undercuts a critical threshold, the plain bearing will operate in mixed friction. Thus, representing a potentially wear-causing operating point. The energy required for operating the system is harvested thermoelectrically within the plain bearing via thermo-generators, which use the temperature gradients in the plain bearing during operation.In this work, the simulative evaluation of the harvestable energy will be presented. The usable temperature difference will be determined for varying positioning of the energy harvester. The results obtained allow the subsequent manufacture of a first Sensor integrating Machine Element (SiME)-prototype. In this context a feasible setup regarding the types and number of sensors as well as a microcontroller for processing the measured data will be defined with respect to the harvestable energy. Furthermore, the principle for temperature-based gap height determination will be introduced, applied for different operating points and compared to simulative results.