Trendafilova, I. and Van Brussel, H.H. (2003) Condition monitoring of robot joints using statistical and nonlinear dynamics tools. Meccanica, 38 (2). pp. 283-295. ISSN 0025-6455Full text not available in this repository. (Request a copy from the Strathclyde author)
This paper considers the problem for condition monitoring of robot joints employing measured acceleration signals. The study aims at (1) Determining features, to be extracted directly from the measured acceleration signals, to detect defects in robot joints and at (2) Finding features dependent on the size of the fault in order to quantify the present defects. The signals coming from intact robot joints and from joints containing backlash or clearance are analyzed using nonlinear dynamics as well as statistical tools. A method for defect detection that employs nonlinear autoregressive (AR) modeling of the acceleration signals is successfully applied to detect backlash and clearance in robot joints. Two procedures for defect quantification are considered - one of them based on the AR modeling and the other employing nonlinear dynamics and statistical features. The problems are considered in the context of a pattern recognition paradigm.
|Keywords:||condition monitoring, nonlinear dynamics, pattern recognition, signal processing, mechanical engineering, Mechanical engineering and machinery, Mechanics of Materials, Mechanical Engineering, Condensed Matter Physics|
|Subjects:||Technology > Mechanical engineering and machinery|
|Department:||Faculty of Engineering > Mechanical and Aerospace Engineering|
|Depositing user:||Strathprints Administrator|
|Date Deposited:||20 Dec 2007|
|Last modified:||22 Mar 2017 09:36|