Effect of tool edge wear on the cutting forces and vibrations in high-speed finish machining of Inconel 718: an experimental study and wavelet transform analysis

被引:53
作者
Fang, Ning [1 ]
Pai, P. Srinivasa [1 ]
Mosquea, S. [1 ]
机构
[1] Utah State Univ, Coll Engn, Logan, UT 84322 USA
关键词
High-speed machining; Tool edge wear; Cutting forces; Cutting vibrations; Inconel; 718; Discrete wavelet transform; ALUMINUM-ALLOY; GEOMETRY; TI-6AL-4V; PARAMETERS; MODEL; DRY;
D O I
10.1007/s00170-010-2703-6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
High-speed machining has been receiving growing attention and wide applications in modern manufacture. Extensive research has been conducted in the past on tool flank wear and crater wear in high-speed machining (such as milling, turning, and drilling). However, little study was performed on the tool edge wear-the wear of a tool cutting edge before it is fully worn away-that can result in early tool failure and deteriorated machined surface quality. The present study aims to fill this important research gap by investigating the effect of tool edge wear on the cutting forces and vibrations in 3D high-speed finish turning of nickel-based superalloy Inconel 718. A carefully designed set of turning experiments were performed with tool inserts that have different tool edge radii ranging from 2 to 62 mu m. The experimental results reveal that the tool edge profile dynamically changes across each point on the tool cutting edge in 3D high-speed turning. Tool edge wear increases as the tool edge radius increases. As tool edge wear dynamically develops during the cutting process, all the three components of the cutting forces (i.e., the cutting force, the feed force, and the passive force) increase. The cutting vibrations that accompany with dynamic tool edge wear were analyzed using both the traditional fast Fourier transform (FFT) technique and the modern discrete wavelet transform technique. The results show that, compared to the FFT, the discrete wavelet transform is more effective and advantageous in revealing the variation of the cutting vibrations across a wide range of frequency bands. The discrete wavelet transform also reveals that the vibration amplitude increases as the tool edge wear increases. The average energy of wavelet coefficients calculated from the cutting vibration signals can be employed to evaluate tool edge wear in turning with tool inserts that have different tool edge radii.
引用
收藏
页码:65 / 77
页数:13
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