Tool condition monitoring based on dynamic sensitivity of a tool-workpiece system
| Autor: | Hongqi Liu, Xuchu Jiang, Bin Li, Caihua Hao, Xinyong Mao |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Computer science Mechanical Engineering 020208 electrical & electronic engineering Mechanical engineering Process design 02 engineering and technology Industrial and Manufacturing Engineering Computer Science Applications Operational Modal Analysis 020901 industrial engineering & automation Modal Machining Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Sensitivity (control systems) Tool wear Software |
| Zdroj: | The International Journal of Advanced Manufacturing Technology. 98:1441-1460 |
| ISSN: | 1433-3015 0268-3768 |
| DOI: | 10.1007/s00170-018-2252-y |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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