%0 Journal Article
	%A Nuawi M. Z. and  Lamin F. and  Ismail A. R. and  Abdullah S. and  Wahid Z.
	%D 2009
	%J International Journal of Electronics and Communication Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 30, 2009
	%T A Novel Machining Signal Filtering Technique: Z-notch Filter
	%U https://publications.waset.org/pdf/3078
	%V 30
	%X A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.

	%P 1252 - 1257