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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2017, Vol. 38 ›› Issue (1): 120167-120167.doi: 10.7527/S1000-6893.2016.0129

• Fluid Mechanics and Flight Mechanics • Previous Articles     Next Articles

A measurement approach for ice shape based on variational segmentation model

LI Weibin1,2, YI Xian1,2, DU Yanxia1,2, ZHOU Zhihong1   

  1. 1. State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China;
    2. Computational Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China
  • Received:2016-02-26 Revised:2016-04-26 Online:2017-01-15 Published:2016-04-28
  • Supported by:

    National Natural Science Foundation of China (11172314, 11472296); National Key Basic Research Program of China (2015CB755800)

Abstract:

Ice shape is one of the key elements in an icing wind tunnel test. In order to measure ice shape efficiently, a non-contact measurement approach is proposed based on a variational segmentation model. The primary work of the proposed approach is to obtain shape curves by segmenting the overhead view image of airfoil. With exact transformation of the curves, the ice shape can be determined. In the segmentation procedure, a novel energy function is presented by using a constructed region characteristic function at the beginning. And then the selective segmentation which is for the purpose of removing the interference of unrelated objects or factors and getting a more accurate result can be implemented by minimizing the energy. The proposed approach has been successfully applied to ice shape measurement, which indicates that it is viable. And the quantitative result of error analysis demonstrates that the proposed measurement approach is highly accurate. Moreover, the measurement test on noisy image shows that it is robust to noise. The proposed approach can be easily applied to other fields which are related to shape measurement.

Key words: aircraft icing, icing wind tunnel, ice shape measurement, image segmentation, variational model

CLC Number: