关键词 : 叶片　 特征识别　 小波模极大值　 特征尺度因 子中 图分类号: TP391文献标识码: A文章编号: 10001298( 2010) 01 019505Accurate Recognition Method for Crosssection DataFeature Points of BladesQu Weiwei　 Gao Feng　 Du Farong　 Zhou Yu　 Li Xuexue( School of Transportation Science and Engineering, Beihang University, Beijing 100191, China)AbstractWavelet modulus maximum method can be used to recognize the features and restrain the noise.However, some important local features would disappear in the finest scales when using this method torecognize the whole crosssection data. The concept of characteristic scale factor was proposed to find outthe differences of the features contained in the crosssection data. When the characteristic scale factor waslarger, the numbers of the decomposable scales would become more and more, and vice versa. The crosssection data can be divided into several sections to be recognized respectively when the features of thecrosssection data differed considerably.And the feature points of each section would be integratedfinally. The experimental results show that the shapescale factor can reflect the information contained inthe signal well and guide features recognition. This recognition method can ensure the integrity of thefeature numbers effectively.Key words　 Blade, Feature recognition, Wavelet modulus maximum, Characteristic scale factor