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Title: An automatic form error evaluation method for characterizing micro-structured surfaces
Authors: Yu, D.P.
Zhong, X.
Wong, Y.S. 
Hong, G.S. 
Lu, W.F. 
Cheng, H.L. 
Keywords: Adapted iterative closest point (AICP)
Automatic form error evaluation method (AFEEM)
Diamond turning
Fast tool servo
Integral volume
Micro-structured surfaces
Salient point
Issue Date: 2011
Citation: Yu, D.P., Zhong, X., Wong, Y.S., Hong, G.S., Lu, W.F., Cheng, H.L. (2011). An automatic form error evaluation method for characterizing micro-structured surfaces. Measurement Science and Technology 22 (1). ScholarBank@NUS Repository.
Abstract: Ultra-precision micro-structured surfaces are becoming increasingly important in a range of application areas, including engineering optics, biological products, metrology artifacts, data storage, etc. However, there is a lack of surface characterization methods for the micro-structured surfaces with sub-nanometer accuracy. Although some research studies have been conducted on 3D surface characterization, most of them are on freeform surfaces, which are difficult to be applied on the micro-structured surfaces because of their limited characterization accuracy and the repeated surface feature patterns in the micro-structured surfaces. In this paper, an automatic form error evaluation method (AFEEM) is presented to characterize the form accuracy of the micro-structured surfaces. The machined micro-structured surface can be measured by any 3D high resolution measurement instrument. The measurement data are converted and pre-processed for the AFEEM, which mainly consists of a coarse registration and a fine registration process. The coarse registration estimates an initial position of the measured surface for the fine registration by extracting the most perceptually salient points in the surfaces, computing the integral volume descriptor for each salient point, searching for the best triplet-point correspondence and calculating the coarse registration matrix. The fine registration aligns the measured surface to the designed surface by a proposed adaptive iterative closest point algorithm to guarantee sub-nanometer accuracy for surface characterization. A series of computer simulations and experimental studies were conducted to verify the AFEEM. Results demonstrate the accuracy and effectiveness of the AFEEM for characterizing the micro-structured surfaces. © 2011 IOP Publishing Ltd.
Source Title: Measurement Science and Technology
ISSN: 09570233
DOI: 10.1088/0957-0233/22/1/015105
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