AE monitoring and analysis of tool wear of numerical control lathe

Abstract

To study the mechanism and characteristics of tool wear, the frequency band energy analysis method of acoustic emission(AE) signal based on wavelet packet decomposition were used. The experiments were conducted on the FTC20numericalcontrol lathe using carbide tool. The band components of the AE signals during turning machining were analyzed and the friction signal was extracted from the raw AE signal. Then the percentages of the energy and the main frequency range distribution of friction signals and chip forming signals in the raw AE signals were investigated. The worn amount of tool nose δ was used as a quantitative measuring index of the tool wear, and the center frequency of signal was defined. The AE signals captured under different tool wears and broken states were analyzed by wavelet packet decomposition, and the total energy, the energy of each frequency band and the center frequency of AE signal was obtained. By analyzing the results, the energies of each frequency band and the center frequency of AE signal changing with the tool wear in the process of turning was obtained. The results showed that the chip forming signal was the key components of the AE signals; and with the increase of the amount of tool nose δ, the energy of 20–40kHz band decreased and the energy of 40–60kHz band as well as the center frequencies of AE signals increased. When the tool broke resulting from the development of the crater wear, the total energy and the root mean square of the AE signals increased greatly and the variation trends of the energy of different frequency bands were the same as those of tool wear.