切削條件改變下之刀具狀態監測

Acoustic Emission Based Tool Condition Monitoring Under Different Cutting Condition

林伯恂(Bor-Shiun Lin)

指導教授 ： 李貫銘

國立臺灣大學/工學院/機械工程學研究所/碩士(2014年)

https://doi.org/10.6342/NTU.2014.01669

摘要

影響機械加工精度與品質的因素不外乎使用的工具機狀況以及切削條件合適與否，工具機的狀況包含了如刀具狀況、震顫現象的產生等，而切削條件與加工材料的配合也是十分重要的。為了避免上述因素影響，實際加工狀態的監控便顯得非常重要。
使用單一種類的感測器在開發以及訊號處理上是較為簡易的，然而我們監測加工狀況依靠的乃是訊號的組成以及某些物理現象的特徵，這些條件須滿足重複性、可靠性、響應性以及解析度等特性才足夠全面以及高精度的反應出實際加工的狀況。故理論上而言，多種訊號的擷取以及分析，能得到越全面性的指標，感測器融合即是滿足上列需求的方法。
本研究係以利用聲射訊號以及切削溫度監控刀具狀態為目的。藉由不同切削條件的1045中碳鋼車削實驗，建立出一個訊號與刀具磨耗間的關係，進而能推廣應用在車削條件改變的情況下，準確預估刀腹磨耗。利用本研究的結果，加上一些簡單的切削訊號分析，便可在線推估出刀具磨耗的狀況是否為合宜加工的範圍內，提供了加工者非常有利且易於辨識的資訊。
根據本研究的實驗結果分析，利用感測器融合概念，使用聲射訊號與溫度的偵測，能有效地找出磨耗量與切削速度的改變對於聲射訊號與切削溫度的關係，進而分別建立數學模型進行磨耗計算。可以利用更少實驗數量便可以推估得各種條件參數下的磨耗情況，尤其多種感測器的融合能有效地消除感測器在特定狀況失效或不準確的情形所造成的影響。

關鍵字

聲射訊號 ； 切削溫度 ； 刀腹磨耗 ； 感測器融合

並列摘要

Machining efficiency and quality are usually affected by the status of the machine tool and cutting conditions. A suitable cutting condition for the work piece material is very important. In order to avoid these factors that cause significant damage, the processing monitoring must be done.
It’s relatively easy using a single type of sensors and signal processing during the development. However, we are monitoring the processing conditions which depend on the composition of the signal and certain physical phenomena and characteristics. To fully meet the actual situation, these signals must qualify to repeatability, reliability, responsiveness and resolution. In theory, the collection and analysis of multiple signals can get more comprehensive information. In short, sensor fusion is the solution of the demands above.
The purpose of this study is to use both acoustic emission signals and cutting temperature to monitor the tool condition. By experimenting turning of 1045 steel under different cutting conditions, we are able to establish the relation between signals and tool wear thus can be extended in the case of different cutting conditions, and can estimate flank wear accurately. According to the results of this study, we can estimate if the tool wear level were within the range of appropriate processing or not with some simple cutting experiments, which provide information clearly and are easy to identify.
The use of sensor fusion concepts, using acoustic emission signals and temperature detection, can identify how the acoustic emission signals, temperature, cutting speed, and wear were related, then establish mathematical models to calculate the wear level. We can estimate wear level through fewer experiments, particularly the integration of sensor fusion can effectively eliminate the impact of circumstances or inaccurate sensor failure in particular reasons caused situations.

並列關鍵字

Acoustic Emission ； Cutting Temperature ； Flank Wear ； Sensor Fusion

參考文獻

[1] D. E. D. Snr., "Sensor signals for tool-wear monitoring in metal cutting operations—a review of methods," International Journal of Machine Tools & Manufacture 40 (2000) 1073–1098, 1999.

[2] L. Dan and J. Mathew, "Tool wear and failure monitoring techniques for turning," International Journal of Machine Tools and Manufacture, vol. 30, pp. 579-598, // 1990.

[5] 陳松佑, "成形車刀狀態偵測系統之開發與研究," 國立台灣大學機械工程學系碩士論文, 2011.

[6] N. H. Abu-Zahra and G. Yu, "Analytical model for tool wear monitoring in turning operations using ultrasound waves," International Journal of Machine Tools and Manufacture, vol. 40, pp. 1619-1635, 9// 2000.

[8] M. H. Hayato Yoshioka, and Hidenori Shinno, "Status Monitoring of Ultraprecision Machining Using Micro Thermo Sensor and AE Sensor," 2009.