Approximate models of CMM behaviour and point cloud uncertainties. (December 2021)

• Record Type: Journal Article
• Authors: Forbes, Alistair
• Is Part Of: Measurement. Volume 18(2021)
• Publication Date: 2021-12
• Subjects: Coordinate metrology -- Spatial correlation -- Statistical models -- Uncertainty evaluation; Detectors -- Periodicals; Measurement -- Periodicals; 530.7
• DOI: 10.1016/j.measen.2021.100304
• Languages: English
• ISSNs: 2665-9174

Abstract

Abstract: Coordinate metrology can be thought of as a two-stage process, the first stage using a coordinate measuring system to gather coordinate data – point clouds – related to a workpiece surface, the second extracting a set of parameters or characteristics from the data. In this paper, we describe a range of straightforward, approximate models of CMM behaviour that can be used to generate variance matrices associated with point clouds. In particular, we describe models that incorporate spatial correlation to capture the smooth departure of CMM behaviour from ideal geometry. We also discuss how variance matrices associated with point clouds can be propagated through to variance matrices associated with derived features.