INTELLIGENT JOINT FAULT DIAGNOSIS OF INDUSTRIAL ROBOTS

✍ Scribed by M.-C. Pan; H. Van Brussel; P. Sas

• Book ID: 102616347
• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 320 KB
• Volume: 12
• Category: Article
• ISSN: 0888-3270
• DOI: 10.1006/mssp.1997.0124

✦ Synopsis

The dynamic behaviour of high-performance mechanical systems such as robots is strongly influenced by the characteristics of the link joints. Joint backlash as a result of wear due to severe stress imposed on the transmission system degrades the robot performance. This paper presents a systematic methodology to diagnose the joint-backlash of a robot by monitoring its vibration response during normal operations. To indicate the reversal of motion of a robot link, and to characterise the spectral patterns of vibration signatures, non-stationary time-frequency analysis algorithms have been employed, which illustrate the signature in a simultaneous time-frequency plane. Significant features are extracted from time domain analysis (probability density moments), and from time-frequency domain analysis (local energy calculations). Artificial neural networks are used as tools for pattern recognition. Experimental results show that the proposed techniques can analyse single-joint backlash quantitatively. Moreover, the described methods also allow to single out backlash in the individual joints in case of multiple-joint backlash.