Condition monitoring of robot joints using statistical and nonlinear dynamics tools

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 0025-6455 (http://dx.doi.org/10.1023/A:1022802604268)

Full text not available in this repository.Request a copy

Abstract

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.

ORCID iDs

Trendafilova, I. ORCID logoORCID: https://orcid.org/0000-0003-1121-7718 and Van Brussel, H.H.;
CORE (COnnecting REpositories)