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Open Access

Structured light measurement-driven adaptive machining for low-pressure turbine blades with powder metallurgy γ-TiAl

Yifei YOUa,b, Wenhu WANGa,b, Shaobo NINGa,b, Wenbing TIANa,b, Shengguo ZHANGa,b, Yuanbin WANGa,b,( )
Key Laboratory of High Performance Manufacturing for Aero Engine (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi’an 710072, China
Engineering Research Center of Advanced Manufacturing Technology for Aero Engine, Ministry of Education, Northwestern Polytechnical University, Xi’an 710072, China

Peer review under responsibility of Editorial Committee of JAMST

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Abstract

Powder metallurgy is a promising method for gamma titanium aluminides (γ-TiAl) low-pressure turbine blade manufacturing as it generates better mechanical properties. However, the powder metallurgy γ-TiAl has an uneven deformation during the pressing process, making it difficult to align the workpiece to the right position during the machining process. To solve this problem, a structured light measurement-driven adaptive machining method is proposed in this paper for the low-pressure turbine blades with powder metallurgy γ-TiAl. The point cloud of the powder metallurgy workpiece is firstly obtained with structured light measurement. Then, the feature point matching method is proposed for coarse registration of the point cloud of the semi-product with the blade design model. Afterwards, a weighted iterative closest point (ICP) algorithm is applied for fine registration of the position of the point cloud to distribute the machining allowance evenly for better machining quality and efficiency. The experiments show that the proposed method can effectively improve the allocation accuracy and allocation results.

Keywords

Powder metallurgyLow-pressure turbine bladePoint cloud registrationWeighted ICPAllocation accuracy

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Journal of Advanced Manufacturing Science and Technology
Volume 4 Issue 3,
July 2024
Article number: 2024009
DOI: 10.51393/j.jamst.2024009
Cite this article:
YOU Y, WANG W, NING S, et al. Structured light measurement-driven adaptive machining for low-pressure turbine blades with powder metallurgy γ-TiAl. Journal of Advanced Manufacturing Science and Technology, 2024, 4(3): 2024009. https://doi.org/10.51393/j.jamst.2024009

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Received: 22 November 2023
Revised: 27 December 2023
Accepted: 16 February 2024
Published: 15 July 2024
© 2024 JAMST

This is an Open Access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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