A high-precision parts deviation detection system based on 3D vision algorithm

Abstract

The invention relates to a high-precision part deviation detection system based on 3D vision algorithm, which includes: a detection box, a supporting round table, an ultrasonic detector, a guide rail, a camera, a searchlight and a central controller, through which the above-mentioned components are accurately Control, adjust the control parameters, reduce the difference caused by the difference of the part body; the central controller adjusts the brightness of the light, the shooting angle of the searchlight and the position of the searchlight on the guide rail according to the detection of whether there is reflection in the captured image, and the central controller according to the 3D The algorithm establishes the model coordinate data, and judges the completeness of the obtained data, and performs defect detection on the qualified part data, which improves the defect detection accuracy. Internal defects improve the application range of the present invention and the accuracy of detecting defects of different parts.

Description

technical field [0001] The field of the invention is a part deviation detection system, specifically a high-precision part deviation detection system based on a 3D vision algorithm. Background technique [0002] With the development of computer science, there are more and more applications of computers in the industrial field. Artificial intelligence, computer vision algorithms, and neural network algorithms have gradually matured, making their application prospects more and more broad. The 3D camera can collect every The 3D coordinate information of the point is restored intelligently to obtain 3D stereoscopic imaging through 3D vision algorithm, which will not be easily affected by the external environment and complex light, and the technology is more stable, which can solve the problems of poor two-dimensional experience and security in the past, and Widely used in the fields of face recognition and 3D modeling; in the development of industry, traditional part defect dete...

AI Technical Summary

Problems solved by technology

[0003] 1. Manual identification is time-consuming and laborious, and is affected by human factors such as fatigue and personal cognitive factors;

[0004] 2. For the detection of high-precision parts, the requirements are relatively high, and the error of traditional detection methods is relatively large;

[0005] 3. For the detection of high-precision parts, the requirements for the detection scene are high, such as the control of the intensity of light irradiation; for small defects, the high light intensity will cause the part to reflect and cover the defect, which is too small and difficult to identify. The traditional detection method has no effect on the above problems. precise control;

[0006] 4. For the detection of high-precision parts, its internal defects are difficult to detect, and the traditional detection equipment does not have the function of identifying the type of parts, and it is impossible to implement different detection methods for different parts

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