摘要
为弥补传统监控方式无法全面覆盖监控区域的不足,设计基于遥感技术的大型游乐设备远程自动化监控预警系统。现场采集层利用遥感技术设计遥感信息采集模型,采集大型游乐设备的结构、环境遥感图像信息,经由通信层传输至监控层,利用卷积神经网络完成轿厢与设备外围出入口等自动化监控,且利用循环神经网络完成设备运行状态与制动器工作状态等自动化监控。实验证明,该系统可有效采集大型游乐设备的遥感图像与遥感数据信息,可有效依据遥感信息完成游乐设备的远程自动化监控预警,且精度较高。
In order to make up for the shortcomings of traditional monitoring methods that can not fully cover the monitoring area,a remote automatic monitoring and early warning system for large-scale amusement facilities based on remote sensing technology is designed.The on-site collection layer uses remote sensing technology to design a remote sensing information collection model,collects remote sensing image information of the structure and environment of large amusement equipment,and transmits it to the monitoring layer through the communication layer.Convolutional neural networks are used to complete automatic monitoring of the elevator car and the peripheral entrances and exits of the equipment.Recurrent neural networks are also used to complete automatic monitoring of equipment operation status and brake working status.Experimental results have shown that the system can effectively collect remote sensing images and data information of large amusement equipment,and can effectively complete remote automated monitoring and early warning of amusement equipment based on remote sensing information,with high accuracy.
作者
杨锐
YANG Rui(Xi’an Special Equipment Inspection Institute,Xi’an 710075,China)
出处
《电子设计工程》
2025年第5期182-187,共6页
Electronic Design Engineering
关键词
遥感技术
大型游乐设备
远程监控
自动化
预警系统
神经网络
remote sensing technology
large amusement facilities
remote monitoring
automation
early warning system
neural network
