Big Data Oriented Smart Tool Condition Monitoring System: Tool life prediction result data
收藏科学数据银行2022-11-02 更新2026-04-23 收录
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https://www.scidb.cn/detail?dataSetId=01b0934a36b24a228a8052b491f4c494
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资源简介：
c1_ wear.csv, c4_ Wear.csv and c6_ wear.csv are the open data set of tool wear experiment. The micro groove milling experiment was carried out on HSM600U high speed machining center. The tool used in the experiment is a vertical flat end milling cutter with a diameter of 800 microns. The cutting material is steel T4. Each cutting segment lasts for two seconds, and 100 cutting segments are conducted for each group of experiments. The cutting force signal is measured with a Kistler dynamometer, and the sampling frequency is 50KHz.Six different cutting conditions were used in the experiment. Experiments 1, 3 and 5 are used as training samples, and Experiments 2, 4 and 6 are used as test samples. After each milling, the tool wear data of each tooth is obtained by offline measurement. t_ tl_ 022619.fig and t_ RUL_ 022619.fig is the prediction result of the change of tool life and effective residual tool life with milling time respectively.
提供机构：
中国科学院合肥智能机械研究所; Guochao Li; Kunpeng Zhu; 合肥物质科学研究院
创建时间：
2022-10-31
