Experimental and simulative investigation of an energy-autarkic, temperature field-based Sensor-integrating Plain Bearing focusing transient operating conditions

Abstract Increased usage of hydrodynamic plain bearings is being encountered in applications that require traversing the mixed friction area, such as in wind turbines gearboxes or heavy-duty drivetrains. These operating conditions are not covered by the established design standards. Condition monitoring systems (CMS) can detect such critical operating conditions—e.g. start-up procedures—and enable timely, condition-based maintenance to prevent damage. In hydrodynamic plain bearings, the lubrication gap height and the bearing temperature are key parameters for detecting failure-critical conditions. The research project “Auto-informative Plain Bearings” uses temperature field monitoring to detect critical conditions. Previous work showed that Gümbel-curve’s relation to the temperature field allows the lubrication gap height determination in fluid friction. In this work it will be proven that the developed CMS approach allows online detection of mixed friction. This paper outlines the CMS design process, focusing on testing under transient conditions and lubricant failure. Consequently, the CMS’s ability to identify critical events will be verified. Sensor-integrating Machine Elements (SiME) need to fulfill the characteristic of energy autarky. The energy harvestable in thermal equilibrium by utilizing the waste heat using a plain bearing integrated thermogenerator (TEG) is determined. The harvestable energy budget is in the range of the non-optimized demand of the Sensor-integrating Plain Bearing (SiPB)-prototype. Finally, measures are derived to achieve permanent autarkic operation of the SiPB.