| Wheel is the most important part of running locomotive. During manufacturingand running, all kinds of flaws may appear in it, which highly affect the traffic safetyof train. During the ultrasonic non-destructive testing of wheel flaws, reflection fromthe wheel brake, sign, touch point, and the surface wave all may influence the flawechoes recognition result. This paper presents an application of fuzzy patternrecognition method in ultrasonic transverse wave detection of wheel flaws.Using a gas engine wheel as the test experiment sample, in order to simulate thenatural flaws, several typical artificial flaws were made in it according to the nationalwheel testing standard. By analyzing the structure of wheels and the law of flawappearance, an ultrasonic transverse wave detection method is selected. Referring tocorrelative acoustics theory, the probe sound field and the wheel testing rule arestudied, and the experiments verify the computing result.Using the frequency domain values as the pattern features, the fuzzy clusteringmethod is presented to construct the fuzzy sets of typical flaws. The concept ofsimilarity degree and the choosing near principle are employed in the fuzzy patternrecognition. Experiments show that the method is efficiency. The correctlyrecognition ratio is up to 92.5ï¼….Further more, considering the multi-scale analysis merit of CWT, the echosignals are transformed by continuous wavelet first, then the spectrum of which ischosen as the pattern's feature values. The fuzzy cluster analysis method is applied inrecognition. Experiment results show that the method can enhance thediscriminability of different flaws, and achieve more promising performance.
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