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Proceedings Paper

A new methodology for evaluating profile and position errors of blade based on parameter priority
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Paper Abstract

As one of the core components of a turbine, the quality of the blade manufacturing has a strong impact on the energy conversion efficiency of the turbine, where the key technology of quality evaluation of blades is point cloud registration. However, with the application of structured light three-dimensional measurement technology in full profile measurement, the typical point cloud registration methods only focus on the minimization of surface profile error, ignoring the position error relative to reference datum, which can easily lead to the misjudgment of qualified blades. In this paper, a new blade error evaluation method is presented to register the point cloud data scanned from a physical blade to its theoretical CAD model, which fits the two surfaces based on parameter priority. Firstly, qualified blades are quickly selected after global fine registration using the best-fit algorithm. Subsequently, based on the priority of position error parameters, the coordinate descent algorithm combined with the minimum zone criterion is adopted for local fine registration, which guarantees accurate evaluation results. Finally, the shape and position error of the actual blade is obtained accurately by calculating transformation parameters of registration and the deviation between the registered point cloud and its CAD model of the blade. Experimental results show that compared with state-of-the-art registration methods, the presented method gives higher priority to the parameters which are difficult to finish or repair by machining, and the position errors are controlled in the tolerance area, which effectively reduces the misjudgment. In addition, evaluation results of blade errors with the method are mainly reflected in profile, which is valuable for guiding the blade finishing or trimming in practice.

Paper Details

Date Published: 12 March 2020
PDF: 14 pages
Proc. SPIE 11439, 2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 1143919 (12 March 2020); doi: 10.1117/12.2548316
Show Author Affiliations
Junjie Hao, Xi'an Jiaotong Univ. (China)
Junhui Huang, Xi'an Jiaotong Univ. (China)
Zhao Wang, Xi'an Jiaotong Univ. (China)
Janmin Gao, Xi'an Jiaotong Univ. (China)

Published in SPIE Proceedings Vol. 11439:
2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems
Jigui Zhu; Kexin Xu; Hai Xiao; Sen Han, Editor(s)

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