Complex curved surface part matching detection method based on extranuclear electron probability density distribution

Abstract

The invention belongs to the technical field of precision machining and measurement, and discloses a complex curved surface part matching detection method based on extranuclear electron probability density distribution. The complex curved surface part matching detection method includes the steps: scanning a part to be detected in a non-contact manner to obtain scanned point clouds and forming matched comparison objects with design point clouds; transforming two point clouds into the same three-dimensional coordinate system, taking each point as an atomic nucleus, taking a neighborhood point of the atomic nucleus as an extranuclear electron, traversing all points and calculating electron probability density distribution values corresponding to the points; determining errors of two models based on the calculated electron probability density distribution values, performing rough matching and precise matching for measured point cloud until meeting terminal conditions when current errors do not meet the terminal conditions. The complex curved surface part matching detection method can effectively solve the technical problem that existing non-contact matching detection technology is sensitive to a model geometric structure and an initial position and easily run into partial optimization.

Description

Technical field [0001] The present invention belongs to the technical field of precision machining error detection. More specifically, it relates to a method for matching and detecting complex curved surface parts based on the probability density distribution of out-of-core electrons, which is suitable for obtaining higher-precision detection results in a non-contact manner and has an algorithm. High efficiency, good robustness and not easy to fall into local optimum. Background technique [0002] The coordinate measuring machine has a wide range of applications in the field of precision parts processing and inspection. Due to the use of contact probes for point measurement, for some complex curved parts, the coordinate measuring machine has problems such as difficulty in taking points and low measurement efficiency. With the development of machine vision and pattern recognition technology, non-contact measurement technology has been widely used in the field of precision machinin...

AI Technical Summary

Problems solved by technology

[0002] Three-coordinate measuring machines are widely used in the field of precision parts processing and testing. Due to the use of contact probes for point measurement, for some complex curved surface parts, three-coordinate measuring machines have problems such as difficulty in point selection and low measurement efficiency.

However, since the general model has tens of thousands or even millions of points, and the geometric structure of the part and the initial position of the two point clouds are relatively complex, in the process of point cloud matching, it is necessary to accurately find out the correspondence between the two point clouds. The relationship is a difficult and complex problem in the non-contact measurement process

[0003] In the prior art, iterative closest point algorithm (Iterative Closest Point, ICP) is usually used to process point cloud matching. For example, some commercial software Geomagic Qualify and Imageware have adopted this algorithm; but this method needs to use the shortest Euclidean distance between points To determine the corresponding relationship of point clouds, there are certain operational defects, and this method requires two point clouds to have a good initial position. If the model structure is complex and the distance is far away, this method is easy to fall into local optimum. Therefore, wrong detection results are obtained. In addition, this method is sensitive to abnormal points in the point cloud

[0004] In addition, a further search found that CN104180789A disclosed a blade detection method based on a graphic matching algorithm. This method uses a contact three-coordinate measuring machine to obtain blade measurement data with low detection efficiency, and uses the shortest Euclidean distance as the corresponding point. The algorithm It belongs to the classic ICP algorithm, and there are still some defects in actual operation; CN103279765A discloses a method for detecting damage on the surface of steel wire rope based on image matching, which locates the damage by extracting the key frame of the steel wire rope video or image gray level difference. The two-dimensional image processing technology is essentially different from the present invention; CN105005993A discloses a fast and accurate three-dimensional terrain matching method based on heterogeneous projections. The method first uses the method of combining linear features and point features to match the projection maps, and then The transformation parameters are used for matching between three-dimensional terrains, but this method will cause the loss of part of the topographic map information during the conversion process from topographic maps to projection maps; CN104406538A discloses a three-dimensional matching of marker points and The scanning method, which requires more overlapping points in the two point clouds, is essentially a rough matching method, which is not suitable for the size matching detection of precision parts

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