Article

Characterization of surface defects in fast tool servo machining of microlens array using a pattern recognition and analysis method

Key State Laboratory in Ultra-precision Machining Technology, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Centre for Precision Technologies, University of Huddersfield, Huddersfield HD1 3DH, UK; Department of Instrumentation, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People’s Republic of China
Measurement DOI:10.1016/j.measurement.2010.06.003 pp.1240-1249

ABSTRACT Microlens array (MLA) is a type of structured freeform surfaces which are widely used in advanced optical products. Fast tool servo (FTS) machining provides an indispensible solution for machining MLA with superior surface quality than traditional fabrication process for MLA. However, there are a lot of challenges in the characterization of the surface defects in FTS machining of MLA. This paper presents a pattern recognition and analysis method (PRAM) for the characterization of surface defects in FTS machining of MLA. The PRAM makes use of the Gabor filters to extract the features from the MLA. These features are used to train a Support Vector Machine (SVM) classifier for defects detection and analysis. To verify the method, a series of experiments have been conducted and the results show that the PRAM produces good accuracy of defects detection using different features and different classifiers. The successful development of PRAM throws some light on further study of surface characterization of other types of structure freeform surfaces.

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Keywords

analysis method
 
characterization
 
defects detection
 
different classifiers
 
different features
 
Fast tool servo
 
freeform surfaces
 
FTS machining
 
good accuracy
 
indispensible solution
 
machining MLA
 
Microlens array
 
optical products
 
paper presents
 
structure freeform surfaces
 
successful development
 
Support Vector Machine
 
surface characterization
 
surface defects
 
traditional fabrication process
 

C. F. Cheung