The embodiment of the invention relates to an abnormal data detection method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining battery two-dimensional data sent by a vehicle in real time; wherein the battery two-dimensional data comprises two pieces of battery parameter data with internal association; inputting the battery two-dimensional data into a pre-trained unsupervised learning model to obtain a prediction result output by the unsupervised learning model; and determining whether the two-dimensional data of the battery is abnormal or not according to the prediction result. The two-dimensional data of the battery comprises two pieces of battery parameter data with internal association, so that the two-dimensional data can be closer to the real condition of the battery, and the detection accuracy is improved. In addition, the unsupervised learning model is trained in advance, so that the requirement on the operational capability of a hardware structure is low.
本发明实施例涉及一种异常数据检测方法、装置、电子设备以及存储介质,方法包括实时获取车辆发送的电池二维数据;其中,所述电池二维数据包括具有内在关联的两个电池参数数据;将电池二维数据输入预先训练的无监督学习模型,得到无监督学习模型输出的预测结果;根据所述预测结果,确定所述电池二维数据是否异常。由于电池二维数据包括具有内在关联的两个电池参数数据,因此可以更贴近电池的真实情况,提高检测准确性。此外,无监督学习模型已预先训练,因此对于硬件结构的运算能力要求低。
Abnormal data detection method and device, electronic equipment and storage medium
一种异常数据检测方法、装置、电子设备以及存储介质
2023-03-24
Patent
Elektronische Ressource
Chinesisch
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