Signal decomposition and fault diagnosis of a SCARA robot based only on tip acceleration measurement

Abstract

A new online fault diagnosis method for a SCARA robot is presented in this paper. This approach is based on separating of the tip acceleration signal into program related acceleration (PRA) and transmission related acceleration (TRA). Unlike existing methods mounting varies sensors at every joints, the proposed technique applies only one accelerometer mounted at the tip of the robot. An advanced detrending algorithm has been developed to extract PRA and TRA signals from the measured acceleration signals. Based on dynamic analysis of the robot, the theoretical acceleration profile of the programmed motion is obtained, which is compared with the PRA signals measured during working. Typical FFT-based spectrum analysis is applied for analyzing the detrended TRA signal for fault diagnosis. The effectiveness of the proposed approach has been verified with experiments conducted on a 4DOFs SCARA manipulator.