Cutting Tool Wear Real-Time Monitoring Technology Research In Aeronautical Parts Machining

In manufacturing, tool is one of the most basic important factors,which directly impacts the quality of workpiece, efficiency of production and the cost of manufacture etc. Aeronautical parts, especially the vast majority parts in aeroengine are difficult to cut materials such as superalloy. These materials need strict requirements for tool, and the prices of tool is high. However, in order to ensure the machining accuracy, have to replace the tool frequently. This will bring about waste and increase manufacturing costs for it doesn't make full use of the actual life of tool. Therefore, tool condition monitoring has become one of the most significant parts in the whole aeronautical parts manufacturing process.In this paper, acoustic emission (AE) signal was used as access to study tool wear monitoring. This paper main include the following aspects:1.Through researching the knowledge about the tool wear and acoustic emission monitoring Principle, studying the acoustic emission signals mechanism in Cutting tool, according to the theory of elastic-plastic . In addition, using the experimental verify the correctness of the theory analysis;2.According to the characteristics of acoustic emission signal , design a set of On-line tool wear monitoring system based on acoustic emission.3.Study of theoretical basis of parameter analysis, spectrum analysis and wavelet analysis, and using these methods to analysis the experimental signal. Finding the wavelet analysis is a more effective way for acoustic emission signal. Study on the methods in acoustic emission signal de-noising and analysis the cutting tool acoustic emission signals using the method of wavelet de-noising4.Analysis on the methods of how to select the suitable wavelet basis for cutting tool wear acoustic emission signal through further study of the knowledge relate to wavelet decomposition and wavelet packet decomposition. Come to a difference between new tool and tool Wear Condition through using wavelet to decompose cutting tool wear AE signal. Using db8 wavelet packets basis to decompose cutting tool wear AE signal into 5 level and calculating the signal band energy. Select the characteristics of the band as a criterion of tool wear and set the standard tool wear threshold through the experiment many times. In the end, the state of tool wear monitoring was finished successfully.