The invention provides a high-speed train braking system fault prediction method based on Informer, and the method comprises the steps: screening train state variables related to a braking system fault through a Pearson correlation coefficient, standardizing variable data, and carrying out the dimension reduction processing to obtain an intermediate feature; a fault identification model based on an improved one-dimensional CNN is constructed, an Informer time sequence prediction model performs time sequence prediction on intermediate features after dimension reduction to obtain future intermediate features, and then the future intermediate features are mapped into fault tags through the trained fault identification model, so that the fault prediction effect is achieved. According to the combination method in the method, the long-term dependency relationship in the input intermediate features can be fully learned, long-term prediction can be carried out, and meanwhile, the accuracy of fault tag prediction is also ensured.
本发明提出了一种基于Informer的高速列车制动系统故障预测方法,通过皮尔森相关系数筛选与制动系统故障相关的列车状态变量,将变量数据标准化后,进行降维处理得到中间特征;构建基于改进的一维CNN的故障识别模型,Informer的时间序列预测模型对降维后的中间特征进行时间序列预测得到未来中间特征,然后通过训练好的故障识别模型将未来中间特征映射为故障标签,以此达到故障预测的效果。本发明方法中的组合方法,即可充分学习输入中间特征中的长期依赖关系并进行较长期的预测,同时也保证了预测故障标签的准确性。
High-speed train braking system fault prediction method based on Informer
基于Informer的高速列车制动系统故障预测方法
2023-04-11
Patent
Elektronische Ressource
Chinesisch
IPC: | G07C TIME OR ATTENDANCE REGISTERS , Zeit- oder Anwesenheitskontrollgeräte / B60T Bremsanlagen für Fahrzeuge oder Teile davon , VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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