On-line detection and measurements of tool wear for precision boring of titanium components

Tien I. Liu*, Bob Jolley, Che Hua Yang

*此作品的通信作者

研究成果: 期刊稿件文章同行評審

5 引文 斯高帕斯(Scopus)

摘要

On-line detection and measurements of tool wear is important to assure manufacturing accuracy, enhance manufacturing efficiency, and reduce manufacturing costs. In this research, adaptive neuro-fuzzy inference systems are utilized in conjunction with features extracted from three-axis cutting force data for the on-line detection and measurements of tool wear for precision boring of titanium components. Cutting force data were measured for carbide tools during the boring of titanium parts. At the end of every boring process, the average flank wear width was measured to determine the cutting tool conditions. Measurements were accomplished with the aid of a toolmaker's microscope. In total, 14 features were obtained from the cutting force data. Euclidean distance measure was utilized to determine which features showed the best indication of cutting tool conditions. This approach can reduce the number of features for on-line detection and measurements of tool wear for precision boring of titanium parts. The selected two most prominent features were kurtosis of longitudinal force and average of the ratio between tangential force and radial force. On-line detection of boring tool wear obtained excellent results, using a 2×2 adaptive neuro-fuzzy inference systems, of being able to predict tool conditions on-line with 100% reliability. On-line measurements of boring tool wear also produced exceedingly successful results with a minimum error for a 1×10 adaptive neuro-fuzzy inference systems of 0.87%.

原文英語
頁(從 - 到)1331-1342
頁數12
期刊Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
230
發行號7
DOIs
出版狀態已出版 - 01 07 2016
對外發佈

文獻附註

Publisher Copyright:
© IMechE 2015.

指紋

深入研究「On-line detection and measurements of tool wear for precision boring of titanium components」主題。共同形成了獨特的指紋。

引用此