The invention provides a fault diagnosis method and device for an aircraft, electronic equipment and a storage medium, and relates to the technical field of machine learning, and the method comprises the steps: obtaining the state variable data of the aircraft; inputting the state variable data of the aircraft into the fault diagnosis model to obtain a fault prediction result of the aircraft output by the fault diagnosis model; wherein the fault diagnosis model is obtained by training state variable sample data and fault labels of the aircraft on the basis of a k-nearest neighbor algorithm kNN model. According to the method, the similarity between the samples is analyzed by using the k-nearest neighbor algorithm, and various fault types are effectively identified and classified, so that rapid and accurate fault diagnosis is realized, and the efficiency and reliability of fault identification are improved.
本发明提供一种飞行器的故障诊断方法、装置、电子设备和存储介质,涉及机器学习技术领域,该方法包括:获取飞行器的状态变量数据;将飞行器的状态变量数据输入至故障诊断模型,得到故障诊断模型输出的飞行器的故障预测结果;其中,故障诊断模型是在k近邻算法kNN模型的基础上,对飞行器的状态变量样本数据及其故障标签进行训练得到的。本发明通过利用k近邻算法对样本之间的相似性进行分析,有效识别和分类各种故障类型,从而实现快速、准确的故障诊断,提升故障识别的效率和可靠性。
Fault diagnosis method and device of aircraft, electronic equipment and storage medium
飞行器的故障诊断方法、装置、电子设备和存储介质
2024-12-10
Patent
Electronic Resource
Chinese
IPC: | G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B64F GROUND OR AIRCRAFT-CARRIER-DECK INSTALLATIONS SPECIALLY ADAPTED FOR USE IN CONNECTION WITH AIRCRAFT , Boden- oder Flugzeugträgerdeckeinrichtungen besonders ausgebildet für die Verwendung in Verbindung mit Luftfahrzeugen |
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