The invention discloses an elevator control cabinet fault diagnosis method based on sound signals. The elevator control cabinet fault diagnosis method comprises the steps that the sound signals under the conditions of normal operation and different fault types of an elevator control cabinet are collected; decomposing the sound signals by adopting an underdetermined blind source separation method, and classifying and marking the decomposed sound signals according to fault types; preprocessing the decomposed sound signals, extracting signal features, and establishing a fault sound feature database; and constructing a PSO-BP neural network model, and training through the fault sound feature database to obtain a fault diagnosis model for fault diagnosis. According to the difference of sound signals generated by different fault types, corresponding signal features are extracted, the neural network model is constructed for training to obtain the final fault diagnosis model, and the fault diagnosis model is used for performing fault diagnosis on the sound signals of the elevator control cabinet. Factors influencing the diagnosis result are few, so that the fault diagnosis result is more reliable, and the fault maintenance efficiency of the control cabinet is improved.
本发明公开了一种基于声音信号的电梯控制柜故障诊断方法,包括:采集电梯控制柜正常运行以及不同故障类型情况下的声音信号;采用欠定盲源分离法对声音信号进行分解,对分解后的声音信号按照故障类型进行分类标记;对分解后的声音信号进行预处理后提取信号特征,建立故障声音特征数据库;构建PSO‑BP神经网络模型并通过故障声音特征数据库进行训练得到故障诊断模型进行故障诊断。本发明根据不同故障类型产生的声音信号的差异,提取相应的信号特征并构建神经网络模型进行训练得到最终的故障诊断模型,利用故障诊断模型对电梯控制柜的声音信号进行故障诊断,影响诊断结果的因素少使得故障诊断结果更加可靠,利于提高控制柜的故障维修效率。
Elevator control cabinet fault diagnosis method based on sound signals
一种基于声音信号的电梯控制柜故障诊断方法
2023-06-16
Patent
Electronic Resource
Chinese
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