Model-based fault simulation and detection for gauge-sensorized strain wave gears

Abstract

Strain wave gears (SWG) are important parts to drive robots. Yet, they are susceptible to wear and degradation carrying high risk for malfunction of the robot. Hence, the detection of faults in SWGs is of great interest for the robot’s safe operation. In this paper, the capability of a simulation chain is shown to generate faulty SWGs’ signals of strain gauge sensors mounted on the back of their flex spline with qualitatively similar behavior to real-world measurement signals. Furthermore, the simulated sensor signals are used for a data-driven detection of faults in measurement data showing the practicality of this approach for real-world applications.