The invention discloses an abnormal operation early warning method for locomotive state monitoring data, which belongs to the technical field of locomotive state monitoring and comprises the following steps: S1, data acquisition: acquiring locomotive information data through an information acquisition module in a locomotive system; s2, data processing: transmitting the collected data, and processing and analyzing the data; s21, feature extraction: extracting and modeling a database of the locomotive in a normal state according to operation features and specific requirements of the locomotive; s22, data comparison: extracting the data in operation, identifying, analyzing and comparing, and performing data comparison in a Fourier frequency shift characteristic mode; s3, abnormal early warning: according to an output result of the model, performing early warning on the data predicted to be abnormal; on the basis of monitoring and analyzing the running state data of the locomotive in real time, measures can be taken in advance for repair and maintenance, abnormal conditions can be quickly and accurately recognized, and the false alarm rate is reduced.
本发明公开了一种机车状态监控数据的运行异常预警方法,属于机车状态监控技术领域,包括:S1、数据采集:通过机车系统中的信息采集模块采集机车信息数据;S2、数据处理:对采集到的数据进行传输,并对数据进行处理分析;S21、特征提取:根据机车的运行特点和具体需求,进行提取和建模正常状态下机车的数据库;S22、数据对比:对运行中的数据进行提取,并识别分析对比,通过傅里叶频移特性方式进行数据比较;S3、异常预警:根据模型的输出结果,将预测为异常的数据进行预警报警;本发明在实现对机车运行状态数据的实时监测和分析的基础上,还可以提前采取措施进行维修和保养,且可以快速准确地识别出异常情况,减少误报率。
Abnormal operation early warning method for locomotive state monitoring data
一种机车状态监控数据的运行异常预警方法
2024-03-26
Patent
Electronic Resource
Chinese
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