The invention belongs to the technical field of train fault detection, particularly relates to a railway train wheel set tread fault detection method and device and a medium, and provides a fault diagnosis algorithm for optimizing a BP neural network through a genetic algorithm on the basis of extracting wheel set tread fault vibration signal feature vectors through a wavelet packet algorithm. According to the method, a wheel set tread fault diagnosis and risk prediction model is constructed, the extracted feature vectors are used as input parameters of a neural network model, a BP neural network optimized by a genetic algorithm is adopted for training and learning, and the diagnosis efficiency and accuracy of wheel set tread faults can be greatly improved.

    本申请属于列车故障检测技术领域,具体为一种铁路列车轮对踏面故障检测方法、设备及介质,在采用小波包算法提取轮对踏面故障振动信号特征向量的基础上,提出了一种遗传算法优化BP神经网络的故障诊断算法,构建了轮对踏面故障诊断与风险预测模型,将提取的特征向量作为神经网络模型的输入参数,采用遗传算法优化的BP神经网络进行训练和学习,能够大幅提高轮对踏面故障的诊断效率和准确率。


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    Titel :

    Railway train wheel set tread fault detection method and device and medium


    Weitere Titelangaben:

    一种铁路列车轮对踏面故障检测方法、设备及介质


    Beteiligte:
    YUN SHANQI (Autor:in) / DOU ZHANGRUI (Autor:in) / FAN ZHE (Autor:in) / ZHAO CHUNHUA (Autor:in) / LIU CHANG (Autor:in) / ZHUANG XUMING (Autor:in) / XUE XIN (Autor:in) / CAO KONGYU (Autor:in) / CHEN JINGWEI (Autor:in) / GUO ZHANGUANG (Autor:in)

    Erscheinungsdatum :

    2024-05-10


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B61L Leiten des Eisenbahnverkehrs , GUIDING RAILWAY TRAFFIC / G01H MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES , Messen von mechanischen Schwingungen oder Ultraschall-, Schall- oder Infraschallwellen / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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