An Algorithm for Improving the Point Cloud Density Calculation of Sheet Surface by 3D Profile Sensor

Abstract

The present invention relates to the technical field of intelligent manufacturing, and specifically relates to an algorithm for improving the point cloud density of a plate surface calculated by a 3D profile sensor, including, step 1, collecting ultra-high density point cloud data of the same type of plate; The mean value of the depth value and the standard deviation of the depth value of the density point cloud data, the data whose depth value is located in the interval is judged as routine data, and the data whose depth value is located outside the interval is judged as extreme data; step 3, train a Set of IT2 fuzzy logic system, train a set of T1 fuzzy logic system through the extreme data; Step 4, scan the sparse point cloud data of the plate to be detected, set the required interpolation coordinate points, combine the IT2 fuzzy logic system and the The T1 fuzzy logic system calculates depth estimates for the interpolated coordinate points sought. The method of the present application can greatly reduce the use cost of the 3D profile sensor, and has wide applicability and good use effect.

Description

technical field [0001] The invention relates to the technical field of intelligent manufacturing, in particular to an algorithm for improving the point cloud density of a plate surface calculated by a 3D profile sensor. Background technique [0002] 3D profile sensors are also called 3D scanners and 3D cameras in the industry. Depending on the accuracy of application scenarios and project cost requirements, design schemes based on different principles including triangular distance measurement, structured light projection, and time-of-flight can be used. Among them, the principle of 3D profile sensor based on laser triangulation ranging is as follows: figure 1 Shown: the semiconductor laser focuses on the measured object through lens 1, and the reflected light of the measured object is collected through lens 2 and projected onto the CCD array. The signal processor calculates the position of the light spot on the array through trigonometric functions to obtain the distance of ...

AI Technical Summary

Problems solved by technology

For example, a piece of wood floor has a dark crack with a width of about 0.3mm along the y-axis, and the interval of the point cloud on the x-axis is 0.5mm. If the crack happens to be in the middle of two columns of points, it cannot be detected

On the other hand, the price of 3D profile sensors is high. For example, the price of domestic modules that meet the scanning width of about 200mm and the x-axis accuracy of about 0.3mm is more than 100,000 yuan. It is unacceptable. If the width of the plate is greater than 200mm, multiple sets of modules are required to be used together, which not only doubles the price, but also increases the cycle of mechanism design. Otherwise, the scanning width can only be increased by greatly sacrificing accuracy.

Similarly, the y-axis accuracy will also be challenged when the pipeline speed is high, which may further increase the manufacturing cost

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