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- W3157924416 abstract "In this paper, a method of intelligent identification and data smooth processing of flying flexible joint pivoting center based on machine vision is proposed. The intelligent identification is realized by the following process: first of all the geometric center of the two markers attached to the flying body is located on a straight line at a certain angle to the center-line of the measured pivoting body, secondly then continuous image sampling is carried out by industrial camera when the marker swings with the pivoting body, and image data is transmitted through a data interface to an industrial computer, Finally the image processing module de-noises the image, removes the background and locates the markers to obtain the plane coordinates of the markers in the coordinate system of the test system. The data smooth of obtained coordinates is carried outby Matlab software including the following steps: the coordinates of the mark points detected based on machine vision are optimized to obtain the smooth curve by fitting of the parabola and arc. Then the coordinates of the points on the curve are used to optimize the coordinates of the marked points from measurement. The optimized coordinate values are substituted into the calculation module of pivoting center, so the average pivoting center of the sampling interval of two images is calculated according to the mathematical model to approach the instantaneous pivoting center during the motion of the pivoting body. The result processing module displays and records the curve of pivoting center shift directly and effectively. Finally, it is validated by simulation and experiments that the precision of pivoting center measured by such measuring system is ~0.5%." @default.
- W3157924416 created "2021-05-10" @default.
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- W3157924416 date "2021-04-29" @default.
- W3157924416 modified "2023-10-16" @default.
- W3157924416 title "Research on Intelligent Identification of Pivoting Center and Smooth Processing of Test Data for Flying Flexible Joint" @default.
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- W3157924416 doi "https://doi.org/10.3389/fnbot.2021.666285" @default.
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