Abstract
Automatic fitting of an arc center and radius is a quality problem frequently encountered when manufacturing a mechanical component. Due to the complexity of the measurement, validating each manufactured component via inspection is not feasible or economical. This paper introduces a new validation procedure for measuring arcs from distributed sensors. The goal of this proposed measurement process is to improve measurement throughput (i.e., parts measured per unit of time) and reduce measurement errors associated with hardware and algorithms. This proposed model develops a three-point inverse kinematic algorithm (TPIK) accompanied by a calibration master to obtain the relative location of the measurement system by solving a set of six non-linear equations. This technique allows deployment of a high accuracy gauge systems that in general, reduces machine and algorithm errors. The direct fitting is validated by using mathematical, CAD, and experimental models. Furthermore, a modified definition for the roundness index is introduced based on the proposed forward and inverse algorithms. The simulations examine the roundness index in relation to the measurement precision, sampling angle, nominal radius, and part variation. A benefit of this proposed method is accurate and rapid inspection of the radii and elimination of the human error associated with part loading variation during conventional radii measurement. The rapid, accurate inspection and corresponding reduction in human error make this method an excellent process for inspection of large quantities of components.
Highlights
Fitting surface geometry to a part is the process of estimating the interpolated geometry between the real data points collected using metrology instruments on real components
The new proposed three-point inverse kinematic algorithm (TPIK) algorithm provides a calibration mechanism that resets the measurement error resulting from machine and human errors by computing the location of distributed gauges in reference to a global Cartesian coordinate
The solution was investigated based on iterative optimization techniques that depend on an initial estimation
Summary
Fitting surface geometry to a part is the process of estimating the interpolated geometry between the real data points collected using metrology instruments on real components. This method is an efficient way to develop a geometric model of the feature. To determine the diameter of a cylinder, a CMM is programmed to acquire points on the surface and optimize the parameters for best-fit geometry. This type of measurement can be affected
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