Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61012
Title: A new representation with probability distribution for nanometric surface roughness in ultra-precision machining
Authors: Zhang, SJ
To, S 
Wang, SJ
Zhang, GQ
Keywords: Probability distribution
Surface roughness
Ultra-precision machining
Issue Date: 2016
Publisher: Elsevier
Source: Precision engineering, 2016, v. 45, p. 445-449 How to cite?
Journal: Precision engineering 
Abstract: Ultra-precision machining (UPM) commonly produces nanometric surface roughness (NSR), which is governed by high-frequency components with tool marks sensitive to noise. Its spacing features (SF) majorly affect optical quality by diffraction and interference. However, the ISO SR standard cannot effectively represent SF. In this study, a new representation for SF was developed by evaluating surface derivative, as extra SR parameters. Probability distribution with the 95-99 rule was adopted to reduce noise effects. The results were found that the extra SR parameters well represents SF and are sensitive to spatial frequency. Probability distribution is an efficient means of reducing noise effects. Significantly, the proposed method is simple and efficient to represent SF of NSR in UPM.
URI: http://hdl.handle.net/10397/61012
ISSN: 0141-6359
DOI: 10.1016/j.precisioneng.2016.02.009
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