期刊
JOURNAL OF TRIBOLOGY-TRANSACTIONS OF THE ASME
卷 144, 期 11, 页码 -出版社
ASME
DOI: 10.1115/1.4054319
关键词
ball screws; wear; recurrence analysis; fractal dimension; surface properties and characterization
资金
- National Natural Science Foundation of China [51905274]
- National Science and Technology Major Projects of China [2018ZX04039001, 2017ZX04011001, 2012ZX04002021]
- Open Fund of Key Laboratory of CNC Equipment Reliability of Jilin University [202105]
This study proposes a method to measure the raceway surface profiles of ball screws and characterizes the lubricated wear process using statistical parameters, recurrence analysis, and fractal dimensions. The results show a significant increase in surface roughness and maximum peak-to-valley height after 1.42 million running revolutions, along with a decrease in recurrence rate. Further analysis reveals that the fractal dimension method has the strongest linear correlation with the number of revolutions, providing a new way to predict the wear states of ball screws.
Owing to the measurement difficulty and the required time needed to analyze wear processes of ball screws, very few studies have been reported. Here, on the basis of a test bench and a Taylor Hobson surface profilometer, the measuring procedure for the raceway surface profiles of ball screws was proposed first. Then the raceway surface profiles of a typical ball screw were measured after 1.42 million running revolutions. Finally, a combinational method including the statistical parameters, recurrence analysis, and fractal dimensional was used to characterize the lubricated wear process. Results show that the increase of the surface roughness (Ra) and maximum peak-to-valley height (Rz) can be up to 396% and 395%, the recurrence rate can decrease more than 59%, and the ratio between the minimum and maximum values of the fractal dimension can be 77% after 1.42 million running revolutions. Further analysis showed that the three methods all reflected the raceway wear dependence on the number of revolutions, and the linear correlation of the fractal dimension method with the number of revolutions was the strongest, which provides a new way to predict the wear states of ball screws by monitoring the worn states of the raceway surface profiles.
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