access icon free Detecting feeble position oscillations from rotary encoder signal in an industrial robot via singular spectrum analysis

© The Institution of Engineering and Technology
Received 15/05/2019, Accepted 20/11/2019, Revised 13/09/2019, Published 05/12/2019

Position signal faces several weak oscillations due to mechanical flaw and faults occurred in the systems. These oscillations can be identified by the encoders that determine the performance and health condition of the machine. Nevertheless, also the concerned oscillation, rotary encoder signal also includes some measurement noise and a significant trend. These trends are typically of several orders, greater in activities than the involved amplitude oscillations, making it tough to detect the small oscillations except deformation of the signal. In addition, the oscillations can be problematic, and magnitude adjusted in unstable conditions. Singular spectrum analysis (SSA) is proposed to overcome this issue. A numerical emulation is demonstrated to show the efficiency of the approach. It indicates that SSA outperforms ensemble empirical mode decomposition (EEMD), empirical mode decomposition, and complete EEMD with adaptive noise in ability and accuracy. Moreover, during the movement of the robotic arm, encoder signals from the robot are analysed to determine the sources of oscillations in joints. The suggested technique is proven to be reliable and feasible for an industrial robot.

Inspec keywords: condition monitoring; vibration control; industrial manipulators; oscillations; fault diagnosis; spectral analysis; position control

Other keywords: robotic arm; rotary encoder signal; industrial robot; mechanical flaw; feeble position oscillations; position signal; amplitude oscillations; health condition; measurement noise; singular spectrum analysis; faults

Subjects: Signal processing and detection; Control applications in manufacturing processes; Digital signal processing; Spatial variables control; Maintenance and reliability; Manipulators; Robot and manipulator mechanics; Control in industrial production systems; Vibrations and shock waves (mechanical engineering); Mechanical variables control

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