A Wheel Flat Scar Detection Method Based on Wavelet Time-frequency Diagram and Quantum Genetic Algorithm
To solve the difficulty in online diagnosis of wheel flat scars of metro,an intelligent online diagnosis method of out-of-round wheel based on wavelet time-frequency diagram,gray-projection method and quantum genetic algorithm is proposed.Firstly,the wavelet time-frequency analysis is carried out on the vertical vibration signal between the wheel and rail,and the wave-let time-frequency diagram is obtained.Then,the features of wheel flat scars are extracted from the time-frequency map combined with the grayscale projection method.Finally,the quantum genetic algorithm is used to optimize the support vector machine to im-prove the classification accuracy of SVM.An engineering example verifies the effectiveness of the method in identifying wheel flat scars.The results show that the method can accurately and quickly detect the wheel flat scars,and the performance of the used clas-sification model is better than that of the existing models.
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