A method for acquiring three-dimensional topography of multiple surfaces of moving abrasive particles

Abstract

A method for acquiring the three-dimensional topography of multiple surfaces of moving abrasive particles. Through the existing video acquisition platform of moving abrasive particles, the automatic tracking of moving abrasive particles is realized, and the image sequence of the same moving abrasive particles under different viewing angles is obtained, and then SIFT is used to The algorithm extracts the feature points of the abrasive grain surface, and locates the corresponding position of the feature points in adjacent frames, and then realizes the establishment of the spatial point cloud model by calculating the three-dimensional coordinates of the feature points, and at the same time reconstructs the surface morphology of the abrasive grains through the SFS algorithm, and finally through The fusion algorithm fuses the surface morphology of the abrasive particles reconstructed by the SFS algorithm with the spatial point cloud model to realize dense reconstruction, and reconstructs the three-dimensional morphology of the multi-surface of the moving abrasive particles with a sense of reality through the texture mapping method; the invention effectively The combination of automatic tracking technology and 3D reconstruction technology solves the problem that the current wear particle analysis technology can only analyze static wear particles from a single surface, and realizes the accurate extraction of full information on the three-dimensional surface of wear particles.

Description

technical field [0001] The invention belongs to the abrasive particle analysis technology in the field of machine wear state monitoring, and in particular relates to a method for acquiring three-dimensional shapes of multiple surfaces of moving abrasive particles. Background technique [0002] Wear between friction pairs is one of the main causes of mechanical equipment failures. According to statistics, failures caused by wear account for about 75% of mechanical equipment failures. Wear status monitoring provides failure prediction and maintenance strategies for mechanical equipment by analyzing the operating status of mechanical equipment, which can improve the safety and reliability of mechanical equipment, fully extend the service life, and minimize maintenance costs and downtime losses of mechanical equipment. With the rapid development of modern industry, the requirements for the safety and reliability of mechanical equipment are getting higher and higher, so it is of ...

AI Technical Summary

Problems solved by technology

The main application of two-dimensional wear particle analysis is ferrographic image processing. This method can extract the plane two-dimensional features of wear particles, such as concentration, equivalent size, shape parameters, etc., but cannot obtain the spatial feature information of wear particles, making it unable to 2D image reflecting wear particles with irregularities

This method is complex to operate, expensive to use, and limited in scope

In addition, whether it is two-dimensional wear particle analysis or three-dimensional wear particle analysis technology, there are always the following deficiencies in the current application: ① only wear particles under static conditions can be analyzed, but the wear particles obtained under static conditions The characteristic parameters will produce different results due to the conditions of taking the image of the wear particles and the aggregation of the wear particles, etc.

②The characteristics of abrasive grains can only be extracted from a single perspective, but the shape of abrasive grains is irregular, and a single surface cannot truly reflect the properties of abrasive grains

[0004] In general, wear particle analysis technology to achieve wear state characterization has become an important means of monitoring the wear state of mechanical equipment, and has been widely used in industrial fields such as aviation, ships, wind power, etc., but due to the shortcomings of its method , such as static wear particle analysis, can only extract the characteristic information of wear particles on a single surface, but cannot comprehensively and accurately extract the information of wear particles

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