Surface finish evaluation using curvelet transforms based machine vision system
作者： G.C.S.G. Bharat , R.S. Umamaheswara Raju , B. Srinivas
DOI: 10.1016/J.MATPR.2020.10.203
关键词: Face (geometry) 、 Machining 、 Curvelet 、 Computer science 、 Machine vision system 、 Scratch 、 Artificial intelligence 、 Computer vision 、 Surface finish 、 Image processing 、 Texture (geology)
摘要: Abstract Machining is done to obtain dimensional accuracy and surface finish; several automated systems are available for the evaluation of accuracy, whereas finish rare. Face milling operation performed at diverse cutting parameters (speed, feed rate, depth cut) on aluminum 6101 alloys. In this work, a machine vision system developed finish. Curvelet transforms based advanced image processing techniques used extract texture features from machined captured images. An ANN-PSO model map feature measured The evaluated accurately given features. Machine as such non-tangible; scratch protective, less time consuming, cost-effective, productive.
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