The invention relates to the technical field of elevator anomaly detection, in particular to an elevator door anomaly detection method and device, electronic equipment and a storage medium, and the method comprises the steps that three-axis acceleration signals and magnetic induction intensity signals in the operation process of an elevator door are collected to obtain original multivariable time sequence signals to construct a data set, dividing the data set into a training set and a test set, constructing a deep neural network with an auto-encoder, pre-training the auto-encoder by using the training set, obtaining and mapping a normal sample into a feature space by using the initialized auto-encoder, obtaining a sphere center of a hyper-sphere so as to continuously train the initialized auto-encoder in combination with the training set, and obtaining a feature space of the hyper-sphere; and finally, the auto-encoder is tested by using the test set, and an abnormal detection result of the elevator door is obtained and output by using a final elevator door abnormal detection model. Therefore, the problems that an abnormal detection method of the elevator door is insufficient in generalization ability, and the abnormal detection requirements of elevators with complex types in actual scenes cannot be met are solved.
本申请涉及电梯异常检测技术领域,特别涉及一种电梯门异常检测方法、装置、电子设备及存储介质,其中,方法包括:采集电梯门运行过程中的三轴加速度信号和磁感应强度信号,以获得原始多变量时间序列信号构建数据集,将数据集划分为训练集和测试集且构建具有自编码器的深度神经网络,利用训练集预训练自编码器,得到并利用初始化后的自编码器将正常样本映射至特征空间中,获取超球体的球心以结合训练集继续训练初始化后的自编码器,得到最终自编码器再利用测试集进行测试,得到并利用最终的电梯门异常检测模型输出电梯门的异常检测结果。由此,解决了电梯门的异常检测方法泛化能力不足,无法满足实际场景中类型复杂的电梯异常检测需求等问题。
Elevator door anomaly detection method and device, electronic equipment and storage medium
电梯门异常检测方法、装置、电子设备及存储介质
2024-04-05
Patent
Electronic Resource
Chinese
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