The invention discloses an elevator safety risk self-adaptive analysis method. The method comprises the steps that a fault prediction model is obtained; obtaining an error sample set based on the sample verification set, and calculating similarity loss based on an error sample set fault prediction result and a real fault type of each sample in the error sample set; constructing a first target loss function based on cross entropy loss, constructing a second target loss function based on similarity loss, and optimizing the fault prediction model to obtain a first fault prediction optimization model and a second fault prediction optimization model; real-time operation parameters are collected, the minimum similarity between the real-time operation parameters and the error samples is confirmed, when the minimum similarity is larger than a preset similarity threshold value, the second fault prediction optimization model is adopted for prediction, otherwise, the first fault prediction optimization model is adopted for prediction, and the elevator risk level is calculated according to the prediction result. The elevator can be monitored in real time, and elevator abnormity and potential risks can be recognized in time.
本发明公开了一种电梯安全风险自适应分析方法,包括:获取故障预测模型;基于样本验证集获取误差样本集,基于误差样本集故障预测结果和误差样本集中每个样本的真实故障类型计算相似度损失;基于交叉熵损失构建第一目标损失函数,基于相似度损失构建第二目标损失函数,对故障预测模型进行优化分别得到第一故障预测优化模型和第二故障预测优化模型;收集实时运行参数,确认实时运行参数与误差样本的最小相似度,当大于预设相似度阈值时采用第二故障预测优化模型预测,否则采用第一故障预测优化模型预测,根据预测结果计算电梯风险等级。本发明可对电梯实时监测,及时识别电梯异常及潜在风险。
Elevator safety risk self-adaptive analysis method
一种电梯安全风险自适应分析方法
2025-01-28
Patent
Electronic Resource
Chinese
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