Predictive Analysis of Robotic Manipulators Through Inertial Sensors and Pattern Recognition

Abstract

Industrial robotics is constantly evolving, with installation forecast of about 2 million new robots in 2020. The predictive maintenance focused on industrial robots is beginning to be applied more, but its possibilities have not yet been fully exploited. The present study focuses on the applications offered by inertial sensors in the field of industrial robotics, specifically the possibility of measuring the “real” rotation angle of a robotic arm and comparing it with its own system of measure. The study will focus on the measurement of the backlash existing in the gearbox of the axis of a robot. Data received from the sensor will be analysed using the wavelet transform, and the mechanical state of the system could be determined. The introduction of this sensing system is safe, dynamic, and non-destructive, and it allows one to perform the measurement remotely, in the own installation of the robot and in working conditions. These features allow one to use the device in different predictive functions.