The invention provides a method and system for predicting the slip amount of an elevator, and the method comprises the steps: firstly collecting the slip amount data of the elevator under the same working condition and different working time periods, and carrying out the data preprocessing; then, an encoder-decoder model is initialized, the encoder structure is a self-defined slippage distribution generation encoder, and the model generates corresponding probability distribution according to the collected elevator slippage data; the decoder model is combined with a deep reinforcement learning model to realize output from a probability distribution model to actual slippage data; meanwhile, an external attention mechanism is introduced into an encoder-decoder model, the dependency relationship between elevator slippage data and an external lift car, a counterweight and the like is captured and collected, and model parameters are continuously optimized; then, selecting a model with the minimum average test error in the S-time evaluation by applying an S-fold cross validation method; and finally, predicting the model, and comparing a prediction result with actual data to obtain a root-mean-square error (RMSE) and a mean absolute percentage error (MAPE).
本发明提出了一种电梯滑移量的预测方法及系统,首先采集相同工况下不同工作时间段下的电梯滑移量数据,并进行数据预处理;然后初始化编码器‑解码器模型,其中编码器结构为自定义滑移量分布生成编码器,该模型将采集到的电梯滑移量数据生成一个对应的概率分布;解码器模型结合深度强化学习模型,实现从概率分布模型到实际滑移量数据的输出;同时在编码器‑解码器模型中引入外部注意力机制,捕获采集电梯滑移量数据与外部轿厢、对重等的依赖关系,不断对模型参数进行优化;接着应用S折交叉验证方法,选出S次评测中平均测试误差最小的模型;最后对模型进行预测,并将预测结果与实际数据进行对比获得均方根误差RMSE、平均绝对百分比误差MAPE。
Method and system for predicting slippage of elevator
一种电梯滑移量的预测方法及系统
2023-10-31
Patent
Elektronische Ressource
Chinesisch
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