Accurate recognition method for cross-section data feature points of blades

Wavelet 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 to recognize the whole cross-section data. The concept of characteristic scale factor was proposed to find out the differences of the features contained in the cross-section data. When the characteristic scale factor was larger, 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 the cross-section data differed considerably. And the feature points of each section would be integrated finally. The experimental results show that the shape-scale factor can reflect the information contained in the signal well and guide features recognition. This recognition method can ensure the integrity of the feature numbers effectively.