工具機刀具狀態偵測系統之開發研究

在自動化生產加工系統中，刀具狀態偵測系統扮演著極為重要的角色，當刀具發生磨耗或崩損時，適時的更換刀具能減少不良廢品造成的損失及提昇產品品質與生產良率。本研究之目的在於針對刀具狀態偵測系統開發進行初步探討及研究，根據許多文獻指出加工時震動訊號之特徵頻率能量與刀具狀態有密切之相關性。但為了分離出特徵頻率使用傅立葉轉換法須選擇適當頻段的濾波器，這對沒有相關專業知識背景的操作員而言是相當困難的，為解決此問題本研究提出一簡易量化頻譜變化的演算法-頻譜相關法，實驗結果顯示頻譜相關法能有效辨識出刀具磨耗及微崩的發生但無法得知刀具崩損之位置。對此本研究也針對切削力進行測量及探討希望藉由比對切削力之變化對應出刀具發生崩損之訊號門檻與可能位置，根據實驗結果顯示當刀具崩損位置切入工件後其切削力明顯劇增，故切削力本身即可作為辨識刀具損壞之指標，因此利用切削力之特徵趨勢配合閾值建立之演算法系統便能輕易達到辨識刀具微崩發生位置之目的，根據實驗結果顯示此法能有效的達到刀具微崩發生位置之辨識。

關鍵字

刀具狀態偵測；頻譜相關法；微崩偵測

並列摘要

It is well known that tool condition monitoring system plays an important role in automatic machining system. By detecting, and thus changing the worn tool in time, the loss due to defect products can be greatly reduced and hence ensuring product quality and reliability. The purpose of this research is to develop a tool condition detection and monitoring system for the tool wear and breakage during cutting process. According to many research findings, the characteristic frequency energy of cutting vibration signal gives the best information corresponding to the tool condition. However, in order to isolate the characteristic frequencies, it requires selecting appropriate filters that are difficult for the less-skilled operators in applications of the Fourier based methods. To avoid this difficulty, spectrum correlation method is proposed in this study. The experimental results showed that the spectrum correlation method was able to detect the tool wear and chipping, but it is unable to find out the chipping position of the worn tool. For this reason, further investigation was made to the cutting forces. The experimental results showed that cutting forces increase sharply right after the tool chipping zone was engaged into the workpiece. A rapid change in cutting forces can itself be a good indicator to detect the tool failure. According to the force features received, the tool chipping detection and monitoring system, that has the capacity to recognize the chipping position of cutting tool, was developed. Experimental verification was conducted with a high degree of success.

並列關鍵字

tool condition monitoring ； tool chipping detecting ； spectrum correlation

參考文獻

[2] N.H. Cook, “Tool Wear and Tool Life”, Journal of Engineering for Industry,

[6] S. Ramalingam and P.K. Wright, “Abrasive wear in machining: Experiment with material of controlled microstructure,” Journal of Engineering Materials and Technology, Vol. 103, 151-156, 1981

[7] M.C. Shaw, Metal Cutting Principles, Oxford Univ. Press New York, 1984

[8] Mayer,“Device for Early Detection of Break and Marginal Wear in The Cutting Edges of Tools”, US Patent, No.4,885,530, 1989

[9] A. Prateepasen, Y. H. J. Au, B. E. Jones, “Acoustic Emission and Vibration for Tool Wear Monitoring in Single-Point Machining Using Belief network,” IEEE Instrumentation and Measurement Technology Conference, Budapest, Hungary, May 21-23, 2001

國際替代計量

工具機刀具狀態偵測系統之開發研究

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