Design and experimental research of a novel automatic scraping machine
Scraping is a key technology in high-precision machine tool machining. Scraping can eliminate the accumulated error and improve the assembly accuracy of machine tools. Scraping is time-consuming and tedious manual labor, which is usually conducted by skillful scraping workers. To overcome these shor...
Saved in:
Published in | International journal of advanced manufacturing technology Vol. 129; no. 11-12; pp. 4899 - 4908 |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Springer London
01.12.2023
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Scraping is a key technology in high-precision machine tool machining. Scraping can eliminate the accumulated error and improve the assembly accuracy of machine tools. Scraping is time-consuming and tedious manual labor, which is usually conducted by skillful scraping workers. To overcome these shortcomings, a novel automatic scraping machine has been designed and tested in this study. The machine includes a 3-axis motion mechanism, a visual recognition system, a 3-D measurement system, and a control system. In this study, a ball-end milling cutter is used to follow a planned path at high speed to simulate the shape of scraper marks of manual scraping. The proposed measurement system and visual recognition system can quickly acquire the information required for automatic scraping and send it to the control system. Based on the received information, the control system automatically determines the scraping location and scraping stage and then generates a set of control codes which are sent to the 3-axis motion mechanism for scraping processing. The experimental results show that the quality of the workpieces scraped by this machine is close to that of manual scraping and reaches the standard of a high-precision machine. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0268-3768 1433-3015 |
DOI: | 10.1007/s00170-023-12604-6 |