The invention discloses an elevator brake state monitoring and fault diagnosis method, relates to the technical field of elevator brake hidden danger detection, and can effectively identify early faults and give an early warning in advance, thereby preventing accidents and improving the detection efficiency. The elevator brake state monitoring and fault diagnosis method comprises the following steps that a signal collecting device is used for collecting vibration data under different faults; the collected original vibration data is converted into a data format which can be used for analysis through a preprocessing step; extracting characteristics reflecting the performance of the brake from the processed data; a machine learning model is trained by using the extracted features, model training adopts a supervised learning mode, training is performed by using data of known faults, model diagnosis accuracy is evaluated by using a test sample, and model parameters are optimized if the accuracy does not reach a set value; and when the model detects features similar to the known fault mode, the fault is identified and fault early warning is sent out.
一种电梯制动器状态监测及故障诊断方法,涉及电梯制动器隐患检测技术领域,其能够有效识别早期故障并做到提前预警,从而防止事故发生,提高检测效率。所述电梯制动器状态监测及故障诊断方法,包括以下步骤:利用信号采集装置采集不同故障下的振动数据;将采集到的原始振动数据通过预处理步骤,转化为可用于分析的数据格式;从处理后的数据中提取出反映制动器性能的特征;利用提取的特征训练机器学习模型,且模型训练采用监督学习的方式,利用已知故障的数据进行训练,并采用测试样本进行评估模型诊断正确率,正确率达不到设定值即优化模型参数;当模型检测到与已知故障模式相似的特征时,识别故障并发出故障预警。
Elevator brake state monitoring and fault diagnosis method
电梯制动器状态监测及故障诊断方法
26.03.2024
Patent
Elektronische Ressource
Chinesisch
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