<abstract xmlns="http://www.w3.org/1999/xhtml"><p>To decrease the influence of outlier on the measurement of tooth profiles, this paper proposes a method of outlier detection and correction based on the grey system theory. After studying the characteristics of outliers from the deviations of tooth profiles, this paper proposes a preprocessing method for the modeling data which include abnormal value, and establishes an outlier detection and correction model for the deviations of tooth profiles. Simulation results show that the precision of ONDGM(1,1)(one order and one variable non-homogenous discrete grey model whose outlier is processed by the preprocessing method proposed in this paper) is higher than that of NDGM(1,1)(one order and one variable non-homogenous discrete grey model), and the ONDGM(1,1) is more suitable than the NDGM(1,1) for dealing with the outliers from the deviations of tooth profiles. The experiment results show that the outlier detection and correction model detects and corrects the outliers from the deviations of tooth profiles, and the correction value of the outlier is basically in accordance with the actual deviation. Therefore, the method of outlier detection and correction decreases the influence of outlier and improves the precision in the measurement of tooth profiles.</p></abstract>

To decrease the influence of outlier on the measurement of tooth profiles, this paper proposes a method of outlier detection and correction based on the grey system theory. After studying the characteristics of outliers from the deviations of tooth profiles, this paper proposes a preprocessing method for the modeling data which include abnormal value, and establishes an outlier detection and correction model for the deviations of tooth profiles. Simulation results show that the precision of ONDGM(1,1)(one order and one variable non-homogenous discrete grey model whose outlier is processed by the preprocessing method proposed in this paper) is higher than that of NDGM(1,1)(one order and one variable non-homogenous discrete grey model), and the ONDGM(1,1) is more suitable than the NDGM(1,1) for dealing with the outliers from the deviations of tooth profiles. The experiment results show that the outlier detection and correction model detects and corrects the outliers from the deviations of tooth profiles, and the correction value of the outlier is basically in accordance with the actual deviation. Therefore, the method of outlier detection and correction decreases the influence of outlier and improves the precision in the measurement of tooth profiles.

Outlier Detection and Correction for the Deviations of Tooth Profiles of Gears

Institute of Precision Instrument, School of Electrical Engineering and Automation, Harbin Institute of Technology, West Dazhi Street 92, 150001, Harbin, China

School of Electronic Science, Northeast Petroleum University, Fazhan street 199, 163318, Daqing, China

Measurement Science Review

{"article-title":"Outlier Detection and Correction for the Deviations of Tooth Profiles of Gears"}

To decrease the influence of outlier on the measurement of tooth profiles, this paper proposes a method of outlier detection and correction based on the grey...

Outlier Detection and Correction for the Deviations of Tooth Profiles of Gears

Pubblicato online: 03 apr 2013

Pagine: 56 - 62

DOI: https://doi.org/10.2478/msr-2013-0013

This content is open access.