研究生: |
TRAN MINH QUANG TRAN MINH QUANG |
---|---|
論文名稱: |
以切削力訊號分析銑削加工穩定性 Analysis of Milling Stability Based on Cutting Force Signal Processing |
指導教授: |
鍾俊輝
Chun-Hui Chung 劉孟昆 Meng-Kun Liu |
口試委員: |
劉孟昆
Meng-Kun Liu Chun-Liang Kuo Chun-Liang Kuo |
學位類別: |
碩士 Master |
系所名稱: |
工程學院 - 機械工程系 Department of Mechanical Engineering |
論文出版年: | 2017 |
畢業學年度: | 105 |
語文別: | 英文 |
論文頁數: | 78 |
中文關鍵詞: | 銑削加工 、刀具顫震 、時頻分析 、小波分析 、希爾伯特-黃轉換 |
外文關鍵詞: | Milling process, Chatter detection, Time-frequency analysis, Wavelet transform, Hilbert Huang transform |
相關次數: | 點閱:403 下載:13 |
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銑削加工是一種非常常見的成型加工方法,而在銑削加工的過程中,不適當的加工參數會使刀具產生顫震,其顫震原因來自於刀刃與工件之間呈現週期性的不連續切削行為,造成切屑厚度週期性的變化,使得刀具產生自激性的震動以及不穩定的切削行為,而顫震會使銑削加工的不穩定性以及降低切削效率,造成尺寸精度、刀具壽命以及表面完整性的下降,因此本研究主要目標為建立完整之刀具壽命下,開發端銑刀的動態切削力模組,對於銑削加工潛在的顫震進行探討。以模組的方式模擬出之切削立,與實際切削所獲得之切削力進行時間及頻率域比較,我們發現時域、頻率域、短時距傅立葉變換、連率小波轉換以及希爾伯特-黃轉換進行顫震訊號分析,相較於使用傅立葉變換光譜法所獲得之結果是徹底地不同,傅立葉變換光譜法在應用於大量的非線性訊號效率極低,進行動態切削力模組模擬之訊號與實驗所獲得之切削力訊號比較,發現顫震頻率主要由兩個現象之頻率所構成,為刀刃通過工件時之頻率以及顫震造成的不穩定高頻,此外,以standard deviation以及本質模態函數方式所獲得之能量比,可有效率的辦別出刀具顫震,最後通過工件表面形貌、表面粗糙度和穩定性波瓣圖驗證其分析結果
The milling operation is the most common form of machining. Because the action of each cutting edge and workpiece is intermittent and periodical, the chip thickness varies periodically. This could lead to self-excited vibrations and unstable cutting which is called chatter vibration. Chatter causes machining instability and reduces productivity in the metal cutting process. It has negative effects on the surface finish, dimensional accuracy, tool life and machine life. Chatter identification is therefore necessary to control, prevent, or eliminate chatter and to identify the stable machining condition. A dynamic cutting force model of the end-milling process with tool runout error was established in this research to understand the underlying mechanism of chatter. The accuracy of the cutting force model in both time and frequency domains was evaluated by comparing to experimental force signals. Time-frequency analysis approaches, specifically short time Fourier transform, continuous wavelet transform and Hilbert-Huang transform, were utilized to give an utterly different perspective of chatter from the conventional Fourier spectrum which is insufficient in analyzing the signals of rich nonlinear characteristics. By comparing the simulation with experimental result, chatter frequency was found to consist of two major components, frequency modulation alongside tooth passing frequency caused by the increased tool runout error and the non-stationary high frequency from the regenerative vibration. Moreover, dimensionless chatter indicators, defined by the standard deviation and energy ratio of the specific intrinsic mode function, could identify the occurrence of chatter effectively. The analysis result was then validated by the workpiece surface topography, surface roughness and the stability lobe diagram
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