Evaluation of machined surface quality of SiC_P/Al composites based on dual tree complex wavelet transform

The machining surface of SiC_P/Al composites contains of lots of bumps, potholes and defects, leading to the confusion of roughness and defect information and unreasonable evaluation of the machining surface. In order to extracting the surface roughness and evaluating of the machining surface of SiC_P/Al composites reasonably, a filtering method based on dual tree complex wavelet transform(DT-CWT) was put forward in this paper. The least squares method, Gaussian filtering method and the filtering method based on DT-CWT were adopted to extract the information of surface roughness and evaluated from two aspects including stability and degree of influence by defects. The results show that filtering method based on DT-CWT has high stability and can distinguish surface roughness from defect information more effectively. Therefore, it is more suitable for the extract of the surface roughness of SiC_P/Al composites. According to comparison between the machining surface of SiC_P/Al whose Al-matrix includes of 2024 and 6063 aluminum alloy by the filtering method base on DT-CWT, it is found that the quality of 2024 aluminum matrix composite surface is better than that of 6063 aluminum composite.