A precise detection method for workpiece surface defects based on point cloud model

Abstract

The invention discloses a precise workpiece surface defect detection method based on a point cloud model, belongs to the technical field of nondestructive inspection. The method comprises the steps that a standard CAD model of a to-be-detected workpiece is discretized into a point cloud format, and normal characteristics are extracted and serve as standard point cloud data; the standard CAD modelis subjected to surface defect treatment and discretized into a point cloud format, and error characteristics are extracted and serve as defect point cloud data; actual point cloud data of the to-be-detected workpiece is obtained by using a 3D scanner; a support vector machine classifier is constructed, and the classifier is trained with the standard point cloud data and the defect point cloud data as a training data set; the obtained actual point cloud data is classified by using the trained classifier, the defect point cloud data in the actual point cloud data is determined, and the positionand the shape of a defect are identified according to the defect point cloud data; the three-dimensional size of the defect is precisely calculated by using covariance matrix 3D measurement method. By means of the method, the position and the size of the workpiece surface detect can be precisely detected.

Description

technical field [0001] The invention belongs to the technical field of non-destructive flaw detection, and in particular relates to a method for accurately detecting workpiece surface defects based on a point cloud model. Background technique [0002] Surface inspection is an indispensable link in the production process, and its efficiency and accuracy directly affect the production quality and production efficiency development of products. At present, there are many kinds of domestic parts and components with complex structures, and manual inspection of surface quality is often relied on. Low efficiency, test results affected by subjectivity and other adverse effects. The current problems put forward an urgent need to design a universal surface detection method that takes into account both efficiency and accuracy. [0003] Surface quality detection is divided into two categories: contact type and non-contact type. The contact type is represented by a mechanical three-coord...

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Problems solved by technology

[0004] In order to solve the above technical problems, the present invention provides an accurate detection method for workpiece surface defects based on a point cloud model, which aims to use the principle of binocular vision to reconstruct a three-dimensional scene in space. Compared with manual detection and contact measurement, it can quickly Obtaining data; compared with traditional vision, improving data accuracy provides the possibility to improve detection accuracy; compared with machine vision, the point cloud model stores the three-dimensional information of the workpiece and realizes the calculation of the three-dimensional size of defects

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