Makoto Abbe

Reliability on calibration of CMM

This paper presents a method which is able to describe the reliability of the parametric error as the calibration result of a CMM. The reliability range may provide uncertainty indication of the calibration. Emphasis is placed on description of expansion of the propagation of error on the linear system expressing the parametric errors of a CMM, and confirmation of the method through the simulation on the calibration performed only by linear displacement measurements.

Uncertainty estimation for coordinate metrology with effects of calibration and form deviation in strategy of measurement

Coordinate metrology utilizes complex measuring systems such as coordinate measuring machines, laser trackers and triangulation systems. Therefore, calibrating the coordinate measuring system using artifacts, e.g. the artifact calibration method, is a key technology. In this paper, methods of estimating uncertainties using the coordinate measuring system after calibration are formulated. First, a calculation method which extracts the values of kinematic parameters using the least-squares method is formulated. Second, the uncertainty of the specified measuring task is calculated using the uncertainty propagation method. A coordinate measuring system utilizing two line cameras is analyzed as an example. Moreover, the influences of the form deviations of the measured workpiece are calculated in the measurement of the features of a circle.

Geometric Calibration of CMM by Utilizing Spatial Coordinate Comparison. 1st Report. Design of Parametric Model and Its Simulation.

A series of papers presents a new calibration method particularly for up to a middle size CMM. The method is able to provide the 21 parametric errors only by performing the coordinate comparison. An automated calibration system for the production stage of CMMs is realized. The first report describes basic structure of the linear parameter model which establishes relation between spatial displacement deviation observed by the coordinate comparison and the linearly combined parametric error components of the CMM. A simulation on a simple guide way example with six independent freedoms is performed to verify functionality of the model. The result shows that 96 parameters expressing six parametric errors are possible to be handled simultaneously. It is confirmed that the parametric errors are estimated with sufficient resolution to apply the model to the calibration of CMMs.

Uncertainty Estimation Using Monte-Carlo Method Constrained by Correlations of the Data

Simple and easy uncertainty estimation method is proposed. Provided that specification or simple experimental result is available, possible variance and covariance in error are estimated and Monte-Carlo simulation reflecting constraint caused by the covariance can be performed. Comparison between uncertainties obtained by the proposed method and that by actual measurements on real CMM shows good agreement within 1 m µ over-estimation.