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Volume 32 Issue 12
Dec.  2006
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Journal of Beijing University of Aeronautics and Astronautics  > 2006  >  32(12): 1435-1438.
Ding Peng, Li Changyou, Ma Qishuang, et al. Wavelet based fault detection of aeronautic engine vanes by borescope[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(12): 1435-1438. (in Chinese)
Citation: Ding Peng, Li Changyou, Ma Qishuang, et al. Wavelet based fault detection of aeronautic engine vanes by borescope[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(12): 1435-1438. (in Chinese)
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Wavelet based fault detection of aeronautic engine vanes by borescope

  • 1.

    School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

  • 2. Center of Aviation Safety Technology of China, General Administration of Civil Aviation of China, Beijing 100028, China

  • Received Date: 27 Dec 2005
  • Publish Date: 31 Dec 2006
    Abstract
  • Using borescope equipment to inspect the inside of turbofan engines is an important technology to the daily fault diagnostic of aeronautic engine. In all the aeronautic engine interior faults, vane′s face fault is a regular one. Towards vane′s face fault, a kind of fault detection and estimation method was presented. First, vane′s face fault was detected by the SUSAN(smallest univalue segment assimilating nucleus) edge detector. Second, the image was analyzed by wavelet transforms to achieve the different frequency components at different locations. Third, the energy of the alternating components around fault was computed by the spectrum. And at last the vane′s face fault was detected and estimated by the energy. Test result shows that this method can quantificationally detect the fault of aeronautic engine vanes and estimate the grade of the fault. It provides a scientific basis for the fault detection and estimation of aeronautic engine vanes by borescope.

     

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  • [1] Smith S M, Brady J M. SUSAN:a new approach to low level image processing . Journal of Computer Vision,1997,23(1):45-78 [2] Stephane M.A wavelet tour of signal processing[M].Second Edition.Beijing:China Machine Press,2003 [3] Perez M M,Dennis T J. An adaptive implementation of the SUSAN method for image edge and feature detection International Conference on Image Processing. Los Alamitos,CA:IEEE Comp Soc,1997,2:394-397 [4] Marr D,Hildreth E C.Theory of edge detection[M].London:Proceedings of the Royal Society,1980:187-217 [5] Antonini M, Barlaud M, Mathieu P, et al. Image coding using wavelet transform[J].IEEE Transactions on Image Processing,1992,1(2):205-220 [6] Leon C.Time frequency analysis theory and applications[M]. Indianapolis:Prentice Hall PTR, 1994 [7] 丁鹏,马齐爽,李长有,等. 基于小波的非线性模型的孔探图像压缩[J].北京航空航天大学学报,2006,32(2):214-217 Ding Peng, Ma Qishuang, Li Changyou, et al.Wavelet and nonlinear model based borescope image compression[J]. Journal of Beijing University of Aeronautics and Astronautics,2006,32(2):214-217(in Chinese)
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