Abstract
This paper studies the dynamic sensitivity-based tool condition monitoring and finds the factors that affect tool wear under operation. First, the dynamic sensitivity of the method is discussed in the article. This discussion is divided into three parts: (i) The hammer test on the computer numerically controlled (CNC) lathe is carried out to study the sensitive components and sensitive directions of low-frequency modes in the static state. (ii) The modal parameters of tools are identified by using the method of operational modal analysis (OMA) in the cutting process. The sensitivities of the operational modes and different directions are analyzed, with a description of the variation of the tool-workpiece system. (iii) Sensitive directions and dominant modes that affect tool wear are obtained by comparing and analyzing the dynamic sensitivity under static and operational states. Furthermore, the results of tool condition monitoring experiments are analyzed and discussed. The characteristics of the tool wear state are obtained based on dynamic sensitivity under different cutting parameters. Additionally, machining applications based on dynamic sensitivity are discussed in three aspects: tool wear rate, process design optimization, and cutting depth optimization. Finally, the results show that the method can be used to characterize the wear state of the tool. A reliable method of tool state monitoring that is independent of the cutting speed has been found.
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The authors are grateful to other participants in the project for their cooperation.
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The research is supported by the National Natural Science Foundation of China under Grant No. 51775212 and 51505084.
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Jiang, X., Li, B., Mao, X. et al. Tool condition monitoring based on dynamic sensitivity of a tool-workpiece system. Int J Adv Manuf Technol 98, 1441–1460 (2018). https://doi.org/10.1007/s00170-018-2252-y
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DOI: https://doi.org/10.1007/s00170-018-2252-y