The invention discloses a multi-structure data driven wheel flat quantitative identification method and system, and the method comprises the steps: constructing a vehicle-track rigid-flexible coupling dynamic model, and taking a synthesized flat as wheel out-of-circle excitation to obtain axle box dynamic responses under different working conditions; respectively carrying out time domain, frequency domain and time-frequency domain processing on the vertical vibration acceleration of the axle box to prepare sample sets with different structural forms; a multi-input convolutional neural network with proper structures and configuration parameters is constructed, vehicle speed signals are used as constraint information of the network, sample sets of different structural forms and combinations thereof and the speed signals are fused and input to an MCNN model for training, and the accuracy and timeliness of quantitative recognition of the wheel flat by the MCNN model under different data structures are compared. Based on the method, an optimal sample input form combination with optimal recognition performance can be obtained, and the obtained recognition model not only has good anti-noise capability, but also has better performance due to the fact that the speed serves as network constraint information, and the overall superiority is better.

    本发明公开了一种多结构数据驱动的车轮扁疤定量识别方法及系统,构建车辆–轨道刚柔耦合动力学模型,将合成扁疤作为车轮不圆激励,以获取不同工况下轴箱动态响应;对轴箱垂向振动加速度分别进行时域、频域和时频域处理,制成不同结构形式样本集;构建具有恰当结构与配置参数的多输入卷积神经网络并以车速信号为网络的约束信息,将不同结构形式及其组合的样本集与速度信号融合输入至MCNN模型训练,比较不同数据结构下MCNN模型对车轮扁疤定量识别的准确性与时效性。基于本发明的方法可得到具有最佳识别性能的最优样本输入形式组合,且得到的识别模型不仅具有良好的抗噪能力,还因将速度作为网络约束信息而性能更佳,整体优越性较好。


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Multi-structure data driven wheel flat quantitative identification method and system


    Weitere Titelangaben:

    一种多结构数据驱动的车轮扁疤定量识别方法及系统


    Beteiligte:
    XIE QINGLIN (Autor:in) / QIAN XINYU (Autor:in) / WEN ZEFENG (Autor:in) / TAO GONGQUAN (Autor:in) / HU ZHIGANG (Autor:in)

    Erscheinungsdatum :

    2024-04-02


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    B61K Andere Hilfseinrichtungen für Eisenbahnen , OTHER AUXILIARY EQUIPMENT FOR RAILWAYS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



    A data-driven method for estimating wheel flat length

    Ye, Yunguang / Shi, Dachuan / Krause, Philipp et al. | Taylor & Francis Verlag | 2020


    Early wheel flat detection: an automatic data-driven wavelet-based approach for railways

    Mosleh, Araliya / Meixedo, Andreia / Ribeiro, Diogo et al. | Taylor & Francis Verlag | 2023




    Aerodynamic wheel cover structure with flat surface

    JEONG JI MIN | Europäisches Patentamt | 2021

    Freier Zugriff