| CHENG Miao,CHEN Song,XU Jin-wen,ZHANG Xiao-feng,CHEN Yan,HAN Bing.Experimental Research on Precision Grinding of Inner Surface of Elbow Based on Profile Recognition[J],50(11):372-382 |
| Experimental Research on Precision Grinding of Inner Surface of Elbow Based on Profile Recognition |
| Received:January 05, 2021 Revised:June 07, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.16490/j.cnki.issn.1001-3660.2021.11.040 |
| KeyWord:magnetic abrasive finishing elbow profile centerline grinding track force state grinding efficiency |
| Author | Institution |
| CHENG Miao |
School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan , China |
| CHEN Song |
School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan , China |
| XU Jin-wen |
School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan , China |
| ZHANG Xiao-feng |
School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan , China |
| CHEN Yan |
School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan , China |
| HAN Bing |
School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan , China |
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| Abstract: |
| The work aims to solve the problems of large random errors caused by manual point sampling in the magnetic abrasive finishing process of the inner surface of the elbow, the grinding gap cannot be guaranteed, and the inaccurate pose. Combined with an industrial robot and an industrial camera, a process method for quickly obtaining the centerline of the curved pipe profile and calculating the grinding pose was designed and realized. First, the basic principle of the magnetic abrasive finishing process on the inner surface of the elbow is analyzed. According to the force state of a single abrasive particle during the grinding process and the magnetic field simulation of the grinding area, the main process parameters that affect the grinding pressure are obtained. Secondly, use the industrial camera to obtain the image of the bent pipe, and obtain the profile centerline of the bent pipe through the image processing algorithm. Finally, the coordinate points on the center line are converted, fitted, and discrete, and combined with the characteristics of the magnetic abrasive finishing process to calculate the movement poses of the robot during the grinding process. At the same time, the test results of this method and the manual point collection method are compared and analyzed, to test the feasibility of this method. The finishing trajectory extracted by the profile recognition method is smoother, takes less time, can maintain a stable finishing gap and is closer to the actual center line of the bend. Under the same test conditions, copper elbow with 180° corner was ground. After 60 minutes of grinding by the profile recognition method, the surface roughness Ra decreased from the original 0.854 μm to 0.236 μm, reaching the best effect. The scratches on the surface are dense and uniform, without defects such as over-grinding and deep scratches. The average speed is about 35.8% higher than the manual point-taking method, and the roughness reduction rate is enhanced by about 3.8%. The application of the profile recognition method in the magnetic abrasive finishing process of the inner surface of the elbow can quickly and accurately obtain the profile centerline of the elbow and calculate the grinding pose of the robot. It can maintain a stable grinding gap while maintaining the correct grinding position, which can effectively improve the grinding efficiency and surface quality of the magnetic abrasive on the inner surface of the elbow. |
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