The invention belongs to the technical field of elevators, and discloses an elevator operation abnormal state analysis method which comprises the following steps: collecting signals in an elevator operation process through a sensor; performing time domain and frequency domain analysis on the signals, and extracting signal features; performing principal component analysis on the signal features; inputting the signal features into a BP neural network for learning and training, wherein the BP neural network is optimized through an improved whale optimization algorithm; and elevator signals collected in real time and the extracted signal features are input into the trained BP neural network, and the BP neural network outputs an elevator operation abnormal state analysis result. According to the method, the BP neural network is optimized through the improved white whale optimization algorithm, the optimized BP neural network has high learning ability, the abnormal state of elevator operation can be analyzed from the elevator operation data, and therefore the elevator is maintained.
本发明属于电梯技术领域,公开了一种电梯运行异常状态分析方法,包括以下步骤:通过传感器采集电梯运行过程中的信号;对其中的信号进行时域和频域分析,提取信号特征;将信号特征通过主成分分析;将信号特征输入BP神经网络进行学习训练,BP神经网络通过改进的白鲸优化算法进行优化;将实时采集的电梯信号和提取的信号特征输入训练后的BP神经网络,BP神经网络输出电梯运行异常状态分析结果。本申请通过改进后的白鲸优化算法对BP神经网络进行优化,经过优化后的BP神经网络具有很强的学习能力,能够从电梯运行数据中分析出电梯运行的异常状态,从而对电梯进行维保。
Elevator operation abnormal state analysis method
一种电梯运行异常状态分析方法
2024-04-12
Patent
Electronic Resource
Chinese
IPC: | B66B Aufzüge , ELEVATORS |
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