I-kaz™-Based Analysis of Cutting Force Signals for Tool Condition Monitoring in Turning Process

被引:0
|
作者
Rizal, Muhammad [1 ]
Ghani, Jaharah A. [1 ]
Nuawi, Mohd Zaki [1 ]
Haron, Che Hassan Che [1 ]
机构
[1] Univ Kebangsaan Malaysia, Dept Mech & Mat Engn, Fac Engn & Built Environm, Bangi 43600, Malaysia
来源
关键词
Cutting force; low-cost sensor; I-kaz (TM) method; tool condition monitoring; NEURAL-NETWORK; WEAR ESTIMATION;
D O I
10.4028/www.scientific.net/AMM.471.203
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Cutting force is an important signal in machining process and has been widely used for tool condition monitoring. Monitoring the condition of the cutting tool in the machining process is very important to maintain the machined surface quality and consequently reduce inspection costs and increase productivity. This paper utilizes I-kaz-based analysis of cutting force signal to monitor the status of tool wear. The cutting force signals are measured by two channels of strain gauge that were mounted on the surface of tool holder. Experiments were carried out by turning hardened carbon steel and cutting force signals were analyzed using I-kaz (TM) technique by integrating two component of signals (I-kaz 2D, Z(2)(infinity)), I-kaz of cutting force (Z(infinity) of F-y), and I-kaz of feed force (Z(infinity) of F-x). The results show that I-kaz of feed force can be effectively used to monitor tool wear progression during turning operation.
引用
收藏
页码:203 / 207
页数:5
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