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Proceedings Paper

Detection of abnormal data during dynamic measurement of discontinuous surfaces
Author(s): Hao Meng; Lianqing Zhu; Qingshan Chen
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Paper Abstract

In order to effectively detect and remove abnormal data during dynamic measurement of discontinuous surfaces, this paper presents an effective method based on the dynamic GM(1,1). The dynamic GM(1,1) is used to implement modeling for the primary measurement data. The model based on the dynamic GM(1,1) can be a good approximation to normal data, while insensitive to abnormal data. Through comparing the model with the primary measurement data, abnormal data can be effectively detected according to a certain criterion. An experiment is carried out to verify the proposed method for detecting and removing abnormal data. A gross error is artificially introduced into the mesh errors of a hob at the ninth cutting. For the ninth cutting edge, the residual error between the mesh error and the modeling value is 3.2077 and greater than 2.5S. The mesh error of the ninth cutting edge is abnormal and replaced by the corresponding modeling value. The experimental result shows that the proposed method can effectively detect and remove abnormal data during dynamic measurement of discontinuous surfaces.

Paper Details

Date Published: 28 December 2010
PDF: 6 pages
Proc. SPIE 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 75440A (28 December 2010); doi: 10.1117/12.885810
Show Author Affiliations
Hao Meng, Beijing Information Science and Technology Univ. (China)
Lianqing Zhu, Beijing Information Science and Technology Univ. (China)
Qingshan Chen, Beijing Information Science and Technology Univ. (China)


Published in SPIE Proceedings Vol. 7544:
Sixth International Symposium on Precision Engineering Measurements and Instrumentation

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