Prediction of surface roughness in CNC end milling by machine vision system using artificial neural network based on 2D Fourier transform

International Journal of Advanced Manufacturing Technology

Volumn 54, Issue 9-12, 2011, Pages 1033-1042

  Palani, S ^a   Natarajan, U ^b  

^a Mount Zion College of Engineering and Technology   (India)

^b ALAGAPPA CHETTIAR COLLEGE OF ENGINEERING AND TECHNOLOGY   (India)

Author keywords

ANN; CNC end milling; Fourier transform; Machine vision; Surface roughness

Indexed keywords

ANN; ARTIFICIAL NEURAL NETWORK; DEPTH OF CUT; END MILLING; FEEDRATE; FOURIER; GRAY LEVEL IMAGE; GRAY LEVELS; IMAGE TEXTURE; INPUT AND OUTPUTS; INPUT DATAS; MACHINE VISION SYSTEMS; MACHINING CONDITIONS; MANUFACTURING PROCESS; MILLED SURFACES; NON-CONTACT; OUTPUT DATA; PEAK FREQUENCIES; PRINCIPAL COMPONENTS; REASONABLE ACCURACY; SPATIAL FREQUENCY DOMAINS; STYLUS METHODS; TOOL MARKS; TWO-DIMENSIONAL FOURIER TRANSFORM;

BACKPROPAGATION ALGORITHMS; COMMINUTION; COMPUTER VISION; FORECASTING; FOURIER TRANSFORMS; MILLING (MACHINING); NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; SURFACE PROPERTIES; TWO DIMENSIONAL;

SURFACE ROUGHNESS;

EID: 79958834553     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-010-3018-3     Document Type: Article

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