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


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[1] Dočekal, A., Dynybyl, V., Kreidl, M., Šmíd, R., Žák, P. (2008). Localization of the best measuring point for gearwheel behaviour testing using group of adaptive models evolution. Measurement Science Review, 8 (2), 42-45.10.2478/v10048-008-0011-1Search in Google Scholar

[2] Takeoka, F., Komori, M., Kubo, A. et al. (2009). High-precision measurement of an involute artefact by a rolling method and comparison between measuring instruments. Measurement Science and Technology, 20, art. no. 045105.10.1088/0957-0233/20/4/045105Search in Google Scholar

[3] Yang, J., Arai, Y., Gao, W. (2009). Rapid measurement of involute profiles for scroll compressors. Measurement Science Review, 9 (3), 67-69.10.2478/v10048-009-0009-3Search in Google Scholar

[4] Lou, Z., Wang, L. (2010). Adjustment of the measurement point’s position in a double-disc instrument for measuring an involute. Metrologia, 47, 583-584.10.1088/0026-1394/47/5/009Search in Google Scholar

[5] Frazer, R.C., Bicker, R., Cox, B. et al. (2004). An international comparison of involute gear profile and helix measurement. Metrologia, 41, 12-13.10.1088/0026-1394/41/1/003Search in Google Scholar

[6] Kamenský, M., Kováč, K. (2011). Correction of ADC errors by additive iterative method with dithering. Measurement Science Review, 11 (1), 15-18.10.2478/v10048-011-0004-3Search in Google Scholar

[7] Barbato, G., Genta, G., Germak, A., Levi, R., Vicario, G. (2012). Treatment of experimental data with discordant observations: Issues in empirical identification of distribution. Measurement ScienceReview, 12 (4), 154-159.10.2478/v10048-012-0020-ySearch in Google Scholar

[8] Ali, S.H.R. (2010). Probing system characteristics in coordinate metrology. Measurement Science Review, 10 (4), 121-129.10.2478/v10048-010-0023-5Search in Google Scholar

[9] Zhang, F., Qu, X. (2012). Fusion estimation of point sets from multiple stations of spherical coordinate instruments utilizing uncertainty estimation based on Monte Carlo. Measurement Science Review, 12 (2), 40-45.10.2478/v10048-012-0009-6Search in Google Scholar

[10] Miao, Y., Su, H., Gang, R., Chu, J. (2009). Industrial processes: Data reconciliation and gross error detection. Measurement and Control, 42 (7), 209-210.10.1177/002029400904200704Search in Google Scholar

[11] Koufakou, A., Georgiopoulos, M. (2010). A fast outlier detection strategy for distributed highdimensional data sets with mixed attributes. DataMining and Knowledge Discovery, 20 (2), 259-289.10.1007/s10618-009-0148-zSearch in Google Scholar

[12] Wang, Z., Wang, Q., Wang, X. (2011). A novel method of gross error identification in non-diffracting beam triangulation measurement system. In FourthInternational Seminar on Modem Cutting andMeasurement Engineering, 10-12 December 2010. SPIE, Vol. 7997, 1-6.Search in Google Scholar

[13] Qin, P., Shen, Y., Wang, Z. (2006). Grey evaluation of non-statistical uncertainty in multidimensional precision measurement. International Journal ofAdvanced Manufacturing Technology, 31, 539-540.10.1007/s00170-005-0224-5Search in Google Scholar

[14] Zhang, Y., Yang, J., Jiang, H. (2012). Machine tool thermal error modeling and prediction by grey neural network. International Journal of AdvancedManufacturing Technology, 59, 1065-1066.10.1007/s00170-011-3564-3Search in Google Scholar

[15] Gao, Y., Wang, Z., Tao, Z., Lo, C. (2003). Estimation of non-statistical uncertainty in precision measurement using grey system theory. International Journal ofAdvanced Manufacturing Technology, 22, 271-272.10.1007/s00170-002-1470-4Search in Google Scholar

[16] Meng, H., Zhu, L., Chen, Q. (2010). Detection of abnormal data during dynamic measurement of discontinuous surfaces. In Sixth InternationalSymposium on Precision Engineering Measurementsand Instrumentation, 8-11 August 2010. SPIE, Vol. 75440, 1-6.Search in Google Scholar

[17] Shi, Z., Zhu, L., Dong, M. (2003). Grey detection and replacement of unwanted asperities in dynamic measurement of discontinuous curves. Journal ofBeijing University of Technology, 29 (1), 15-18.Search in Google Scholar

[18] Wang, Z., Gao, Y., Qin, P. (2002). Detection of gross measurement errors using the grey system method. International Journal of Advanced ManufacturingTechnology, 19, 801-804.10.1007/s001700200091Search in Google Scholar

[19] Ke, H., Chen, Y., Wu, J. (2008). New distinguishing model for gross error based on GM (1,1) model. Systems Engineering and Electronics, 30 (10), 2005-2006.Search in Google Scholar

[20] Lou, Z., Wang, L. (2008). Research on reference levelinvolute testing theory and technology. PhD thesis, Dalian University of Technology, China.Search in Google Scholar

[21] Xie, N., Liu, S. (2009). Discrete grey forecasting model and its optimization. Applied MathematicalModeling, 33, 1173-116.10.1016/j.apm.2008.01.011Search in Google Scholar

[22] Liu, S., Lin, Y. (2005). Grey Information: Theory andPractical Applications (1th ed.). Springer-Verlag.Search in Google Scholar

[23] Yao, T., Forrest, J., Gong, Z. (2012). Generalized discrete GM (1,1) model. Grey Systems: Theory andApplication, 2 (1), 4-12.10.1108/20439371211197622Search in Google Scholar

[24] Zhao, J., Yang, S., Xin, L. (2011). Stepwise ratio GM (1,1) model for image denoising. MeasurementScience Review, 11 (1), 36-44.10.1109/GSIS.2011.6043959Search in Google Scholar

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6 veces al año
Temas de la revista:
Engineering, Electrical Engineering, Control Engineering, Metrology and Testing