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Large wallboard class part digitized quality detection method

A quality inspection method and technology for large-scale wall panels, which are applied to measurement devices, instruments, optical devices, etc., can solve the problems of incomplete data collection and low detection efficiency, and achieve the advantages of strong operability, simple method, and increased data collection volume. Effect

Active Publication Date: 2013-12-11
BEIHANG UNIV
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AI Technical Summary

Problems solved by technology

[0018] (1) Purpose: The purpose of this invention is to provide a digital quality detection method for large wall panel parts in the process of using laser tracker alone to detect the problems of incomplete data collection and low detection efficiency , through the joint measurement method of laser tracker and articulated arm, the above-mentioned defects of the prior art are improved

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  • Large wallboard class part digitized quality detection method
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  • Large wallboard class part digitized quality detection method

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Embodiment Construction

[0060] The present invention is a digital quality inspection method for large-scale siding parts. The steps of the method are shown in figure 1 , See the measurement process figure 2 , The specific steps are as follows:

[0061] Step 1: Perform the initialization operation before measurement, including: fixing the wallboard parts to be tested, dividing the scanning area for the wallboard parts to be tested, arranging the position of the laser tracker and the position of the articulated arm.

[0062] The position of the laser tracker is fixed during the measurement. When dividing the scanning area of ​​wallboard parts, pay attention to the common overlapping area between different areas. This overlapping area is used to arrange the splicing points. Choose a wall panel with a length of 2.8m and a width of 0.8m as the inspection object. The scanning range of the articulated arm is a spherical measurement space with a radius of 2.5m, so it is only necessary to divide the wall panel i...

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Abstract

A large wallboard class part digitized quality detection method includes the steps of firstly, conducting initialization operation before measurement, namely, fixing a wallboard class part to be measured, arranging the position of a laser tracker and the position of an articulated arm and conducting scanning region partition on the wallboard class part to be measured; secondly, arranging wallboard positioning points and point cloud registration points and recording the positions of the points through the laser tracker; thirdly, obtaining point cloud data and registration point coordinates in each region through the articulated arm; fourthly, obtaining a point cloud of a whole wallboard; fifthly, comparing the point cloud with a model and outputting the detection result. When detection is conducted on the large wallboard class part through the method, the accuracy is high, the operation is simple, and the use effect is good.

Description

Technical field [0001] The invention relates to a digital quality inspection method for large-scale wallboard parts. It is a method for detecting large-scale wallboard parts by using multiple digital equipment. It can be used for the quality of large-scale wallboard parts in the aerospace and automobile industries. Detection belongs to the field of digital measurement and computer integrated manufacturing. Background technique [0002] Large-scale siding parts have the characteristics of large size, complex shape and poor structural rigidity. The forming quality inspection methods of wall panel parts have been transformed from traditional geometrical analog inspection methods to digital inspection methods. At present, its main quality inspection methods are laser tracker inspection and articulated arm inspection. [0003] 1. Laser tracker detection method [0004] The laser tracker detection method belongs to the contact detection method. The contact digital detection method base...

Claims

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Application Information

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IPC IPC(8): G01B11/24
Inventor 赵罡王志佳杨学蕊孙涪龙关煜杰韩鹏飞
Owner BEIHANG UNIV
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