摘要
随着自动电扶梯应用的日益普及,安全事故率呈上升趋势,设备运行监控及报警应该得到足够的重视。文章基于温度信号与噪声信号相融合的方式构建自动扶梯故障监测系统,通过监测扶手带的温度来预判扶手带的张紧情况,通过监测梯级的噪声来判断梯级是否出现故障,同时基于BP神经网络与遗传算法进行故障类型识别,通过对多个传感器的监测创建覆盖自动扶梯全寿命周期、高效精确的故障监测系统。
With the increasing popularity of the application of escalators,the safety accident rate is on the rise.Equipment operation monitoring and alarm should be paid enough attention.This paper constructs the escalator fault monitoring system based on the fusion of temperature signal and noise signal,predicts the tension of the handrail by monitoring the temperature of the handrail,and judges whether the step has fault by monitoring the noise of the step.At the same time,it identifies the fault type based on BP neural network and genetic algorithm,and creates an accurate and efficient fault monitoring system covering the whole life cycle of the escalator through the monitoring of multiple sensors.
作者
麦一飞
MAI Yifei(Station House Construction Headquarters of China Railway Guangzhou Group Co.,Ltd.,Guangzhou 510000,China)
出处
《现代信息科技》
2022年第4期177-181,共5页
Modern Information Technology
关键词
自动扶梯
故障监测
温度
噪声
escalator
fault monitoring
temperature
noise
