TY - JOUR
T1 - Computer image analysis of wear particles in three-dimensions for machine condition monitoring
AU - Peng, Z.
AU - Kirk, Brett
PY - 1998
Y1 - 1998
N2 - Six common types of metallic wear particles, i.e., cutting, spherical, rubbing, laminar, fatigue chunk and severe sliding particles, have been studied in this paper based on the features of their boundary morphology and surface topography. Certain numerical descriptors, such as area, fibre ratio, height aspect ratio and fractal dimension, have been chosen to describe the characteristics of the boundary profiles of the wear debris. Since boundary parameters are insufficient to distinguish certain types of wear debris, several surface parameters extracted from the amplitude and spatial properties of the particles have been applied to investigate the surface roughnesses and textures of laminar, fatigue chunk and severe sliding wear debris. The study shows that classifying wear debris by studying the combined properties of their boundary profiles, surface roughnesses and textures can identify these six types of wear particles. Furthermore, nine parameters have been selected as criteria for wear particle analysis, and can be used to develop automatic computer wear particle analysis systems based on numerical descriptors. (C) 1998 Published by Elsevier Science S.A. All rights reserved.
AB - Six common types of metallic wear particles, i.e., cutting, spherical, rubbing, laminar, fatigue chunk and severe sliding particles, have been studied in this paper based on the features of their boundary morphology and surface topography. Certain numerical descriptors, such as area, fibre ratio, height aspect ratio and fractal dimension, have been chosen to describe the characteristics of the boundary profiles of the wear debris. Since boundary parameters are insufficient to distinguish certain types of wear debris, several surface parameters extracted from the amplitude and spatial properties of the particles have been applied to investigate the surface roughnesses and textures of laminar, fatigue chunk and severe sliding wear debris. The study shows that classifying wear debris by studying the combined properties of their boundary profiles, surface roughnesses and textures can identify these six types of wear particles. Furthermore, nine parameters have been selected as criteria for wear particle analysis, and can be used to develop automatic computer wear particle analysis systems based on numerical descriptors. (C) 1998 Published by Elsevier Science S.A. All rights reserved.
U2 - 10.1016/S0043-1648(98)00280-4
DO - 10.1016/S0043-1648(98)00280-4
M3 - Article
VL - 223
SP - 157
EP - 166
JO - Wear
JF - Wear
SN - 0043-1648
ER -