Optimal Number of Control Points for Fitting B-Splines in Wind Turbine Blade Measurement

Chan, Ching Hin Lydia; Wang, Qing; Holden, Roger; Huang, Songling; Zhao, Wei

Abstract

The manufacture of large-scale products such as aircraft and wind turbines needs detailed inspection to ensure the required dimensional tolerances are met. A coherent laser radar with an assisting mirror was used in this research to inspect a half-size wind turbine blade. This paper investigates the optimal distribution of inspection points that would produce the most accurate B-Spline fitting to the CAD model surfaces and so shorten the inspection and analysis process without compromising on accuracy. Even though the optimal solution was found to be points with 100 mm spacing on a moderate surface gradient and with 20–25 mm spacing on a more severe surface gradient, the findings suggest the employment of a non-uniform distribution would produce a more accurate fitting. This paper also explores data alignment by Degree of Freedom constraints with a triple B-Spline and investigates whether denser data points would improve the transformation. The optimal solution was found to be constraining movement in Z, Rx and Ry. Therefore, to achieve better transformation, surfaces were treated based on their gradient. This resulted in a constraint in X, Y and Z, and Ry for a moderate gradient and Y, Z and Rz for a more severe gradient. The optimal number of inspection points for fitting a B-Spline on a half-size blade was found to be 18 points for the front section with 100 mm spacing, 15 points for the back section with 100 mm spacing, and between 14 and 18 points with 20–25 mm spacing on the base section.

Citation

Chan, C. H. L., Wang, Q., Holden, R., Huang, S., & Zhao, W. (2019). Optimal Number of Control Points for Fitting B-Splines in Wind Turbine Blade Measurement. International Journal of Precision Engineering and Manufacturing, 20(9), 1507-1517. https://doi.org/10.1007/s12541-019-00173-2

• Journal Article Type: Article
• Acceptance Date: Jun 11, 2019
• Online Publication Date: Jun 28, 2019
• Publication Date: Sep 30, 2019
• Deposit Date: Jul 12, 2019
• Publicly Available Date: Jun 28, 2020
• Journal: International Journal of Precision Engineering and Manufacturing
• Print ISSN: 2234-7593
• Electronic ISSN: 2005-4602
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 20
• Issue: 9
• Pages: 1507-1517
• DOI: https://doi.org/10.1007/s12541-019-00173-2
• Public URL: https://durham-repository.worktribe.com/output/1297509