Research on Ultrasonic Guided Wave Technology for the Rail Fatigue Cracks Based on PCA-adaboost.M2 Algorithm

Abstract

Abstract As a key equipment in high-speed railway operation, rails inevitably produce various fatigue cracks during long-term service, which are major safety hazards in the railway transportation. In order to achieve intelligent detection of the rail fatigue cracks, the PCA-adaboost.M2 algorithm based on ultrasonic guided waves is proposed for the classification and identification of rail fatigue cracks. First, a rail fatigue crack detection system based on an ultrasonic guided wave was established to obtain ultrasonic guided wave signals at different depths of the rail fatigue cracks. Then, five time–frequency domain features of the ultrasonic guided wave (the maximum, the mean, the variance, the center of gravity frequency, and the frequency variance) were extracted, and the five main components of the ultrasonic guided wave were extracted by the principal component analysis (PCA) method and are used for classification and recognition of the adaboost and the adaboost.M2 algorithm, separately. The experimental results show that the ultrasonic guided wave based on the PCA-adaboost.M2 algorithm proposed has good performance in quantitative detection of the rail fatigue crack depth. The ultrasonic guided wave based on the PCA-adaboost.M2 algorithm proposed in this paper provides a method for detecting the rail fatigue crack depth.