Method for quickly detecting normal vector of large-curvature-radius curved surface

Abstract

The invention discloses a method for quickly detecting the normal vector of a large-curvature-radius curved surface in the technical field of optical measurement. The method comprises the following steps of: intersecting two mutually-vertical surfaces with a workpiece curved surface to obtain two coordinate curves of curved surface points; and respectively detecting micro curve tangential vectorscentered on the curved surface points on the two coordinate curves to obtain the normal vector of a curved surface data point. In the invention, the conventional curved surface normal detection three-dimensional problem is transformed into a two-time two-dimensional curve detection problem, so that the method is convenient, low in cost and easy to operate and makes data processing simple, the requirement of real-time detection during curved surface machining is met, and the quality and the efficiency of the curved surface machining are improved.

Description

technical field [0001] The invention relates to a method in the technical field of optical measurement, in particular to a method for quickly detecting the normal vector of a curved surface with a large curvature radius. Background technique [0002] In most cases, the processing of curved surface workpieces needs to be carried out on the normal vector of the workpiece, such as drilling, riveting and so on. In the actual detection process, due to the existence of manufacturing errors, the actual curved surface of the measured workpiece does not coincide with the theoretical surface in the digital model, and the actual measurement point (that is, the contact point between the probe and the workpiece or the tool and the workpiece to be processed The normal vector of the point) does not necessarily coincide with the normal vector passing through the point, which brings the detection error and processing error of the curved surface. At present, the traditional surface normal ve...

AI Technical Summary

Problems solved by technology

However, this detection method is difficult to collect large-scale workpiece data, the amount of data collection is large, the post-processing of the data is complicated, time-consuming, and costly, and it can only detect the normal vector of the surface point under a certain static state, which affects the processing accuracy and Processing efficiency cannot meet the needs of real-time detection of surface point normal vectors during surface processing

[0003] After searching the existing technical literature, it was found that the spherical approximation algorithm proposed by Xie Youjin et al. in "Research on the Algorithm for Solving the Normal Vector of Deformed Surface" (Modern Manufacturing Engineering. 2010, 7) can solve the problem of real-time Solve the surface point normal vector problem, but this measurement method, like the traditional detection method, has the disadvantages of high requirements for detection equipment, large amount of data collection, complex and time-consuming data processing, etc.

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