Cylindricity compound errors reversal separation method

Zi Xue; Xiaoyou Ye

doi:10.1117/12.717111

24 October 2006 Cylindricity compound errors reversal separation method

Zi Xue, Xiaoyou Ye

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 635723 (2006) https://doi.org/10.1117/12.717111
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

Spatial rotation error of the spindle, straight movement error of the straight guide, parallelism error between the guide and the spindle are principle error sources for the cylindricity measuring instrument. It is a difficult problem all the time for high precision cylindricity measurement to separate synchronously and effectively the three errors from the cylindricity result. In order to solve the problem, a novel method for high precision cylindricity error separation is developed. The method is developed based on the characteristics which the directions of the movement errors on the two radial ends of the cylindrical artifact are always reverse each other, and the cylindrical surface form can be separated by combination arrangement of the sensors and the error separation table and mutual addition among the measured signals on the different positions. The method can be used to remove totally the spatial rotation error of the spindle, straight movement error of the straight guide, parallelism error between the guide and the spindle in principal. The simulation results show that the method can effectively improve the measurement precision of the cylindrical artifact and the high precision cylindrical profile.

Citation Download Citation

Zi Xue and Xiaoyou Ye "Cylindricity compound errors reversal separation method", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 635723 (24 October 2006); https://doi.org/10.1117/12.717111

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