Identification of the Optimum Level of Wavelet Decomposition for Acoustic Emission Signal Denoising of a Milling Machine

Tool wear is one of the most important problems encountered during the manufacturing process in milling machines. To overcome this opsticle, various methods are used including the analysis of vibration or acoustic emission signals coming from the desk or spindle of the machine. On the other hand, wavelet analysis helps engineers and specialists to reduce noise, which is the primary nature of raw signals. An accurate and efficient noise reduction process is achievable by choosing an appropriate base or mother equation and decomposition level in wavelet transform. This paper analyzes the types of base equations and two levels of signal decomposition for data driven from acoustic emission at spindle of a milling machine. Finally, the reasons for selecting the level of decomposition, maternal equation and threshold method in wavelet analysis are explained and discussed.