An Orientation Weight Algorithm for Five-Axis OMI System

Abstract

The length of the inspection path and the number of probe orientations are two basic path planning goals. For the number of probe orientations, minimizing the number of probe orientations will cause the probe to swing too large when measuring some local measurement points. The larger the probe angle will make the fluctuation of the measurement error larger, affecting the subsequent error compensation, thereby increasing the error of the measurement. For this problem, this paper proposes an orientation weight algorithm for five-axis coordinate measuring machine to inspect path planning. The orientation weight algorithm projects all the candidate probe orientations of the measurement point onto the orientation weight map, and then selects a weight distribution to set the angle of the different probes to the vertical normal vector with the smallest measurement error. A weight that classifies the measuring points into groups by the selected orientation. The path of each point is planned using the Traveling Salesman Problem (TSP) algorithm, and then the total path is obtained by concatenating different groups. Finally, the effectiveness and characteristics of the algorithm are verified by simulation experiments. The orientation weight algorithm introduces the weight of the error influence in the case of ensuring that the number of times the probe changes orientation is small. It not only ensures the efficiency of measurement, but also the accuracy of measurement.