Multi-scale texture filtering-based quantitative machining mechanism characterisation for ultra-precision machined surfaces

Abstract

Ultra-precision machined surfaces with nanometric surface texture have realised widespread applications. However, it is still challenging to quantitatively characterise the complex generation mechanisms due to the coupling of the machining factors. To address this issue, this work developed a multi-scale texture filtering-based method for ultra-precision machined surfaces. First, experiments were conducted including diamond turning, diamond milling, and ultra-precision grinding. Next, power spectrum density was utilised to reveal the multi-scale characteristics of surface texture generation. Then, the discrete wavelet transform was proposed for multi-scale texture filtering. Finally, root mean square height Sq was evaluated on S-F surfaces according to ISO 25178-2 and the machining mechanisms were quantitatively characterised by the contribution percentages of each scale. The results demonstrated that surface texture generation was dominated by multi-scale machining mechanisms to manifest as cutting residual, tool mark, material effect, spindle vibration, and ductile-brittle transition. Surface texture characterisation quantitatively indicated that small-scale features (cutting residuals and material effects) are crucial factors at low material removal volume (MRV). Due to the increased MRV, there is a transition since the middle/large-scale features (tool marks, spindle vibration, and ductile-brittle transition) gradually play their important role. This work provides novel thoughts to quantify machining mechanisms by multi-scale surface texture metrology for ultra-precision machining.