Development and Analysis of AE Signal Generation Model in Micro-milling

• Main Authors: Chien-Wei Hung, 洪健為
• Other Authors: Ming-Chyuan Lu
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/98003241560652098405

碩士 === 國立中興大學 === 機械工程學系所 === 97 === In micro-cutting machining, various kinds of signals variated because of the tool wear can be detected with the sensors. Among them, acoustic emission signal is a high frequency signal that distributed in the range from several dozen kHz to several dozen MHz, generated mainly by dislocation of materials and more difficult to be influenced by the low frequency background noise of cutting. On the basis of study the relation between high frequency acoustic emission signal generation mechanism to tool wear, the research set up a model of acoustic emission signal generation and propagation to probe into the relation between the variation of frequency and amplitude of acoustic emission signal to tool wear. Used the finite element software to simulate the shear strain rate distribution of shear plane and plough plane in orthogonal cutting first, and then calculated dislocation density in materials by using Orowan’s law, finally, set up a model of acoustic emission signal distribution and propagation by using Gaussian probability density function and wave equation. Set up an acoustic emission signal model via metal cutting generated dislocation motion, and even forming acoustic emission signal source, then propagated to acoustic emission sensor. Furthermore, using the acoustic emission signal generation model to observe the signal variation in different tool wear condition. The research finally proceeded a cutting experiment by micro-milling machine tool. Compared and discussion acoustic emission signal of experimental and simulate. And can be found the phenomenon of increasing amplitude of acoustic emission time domain signal with simulate and experimental. In acoustic emission frequency domain signal, both energy increasing and frequency move to high frequency, maximum peak frequency ranged between 250 kHz to 300 kHz. Therefore, it proved the acoustic emission signal generation model in micro-milling set up by the research has considerably accuracy.