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作 者:刘沁 王春丽 尹琛 陈秉乾 高献 林晓宁 吴慧莹 Liu Qin;Wang Chunli;Yin Chen;Chen Binggan;Gao Xian;Lin Xiaoning;Wu Huiying(State Grid Fujian Electric Power Co.,Ltd.,Fuzhou 350009,China;Economic and Technological Research Institute of Fujian Electric Power Co.,Ltd.,Fuzhou 350012,China)
机构地区:[1]国网福建省电力有限公司,福建福州350009 [2]国网福建省电力有限公司经济技术研究院,福建福州350012
出 处:《能源与环保》2022年第11期12-17,共6页CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基 金:2016年华北电力大学中央高校基金项目(2016MS125)。
摘 要:为了避免由于施工人员缺乏安全意识导致安全事故,设计了基于ASP的电力施工安全质量监测系统。在电力施工现场中布置ZigBee节点,通过ZigBee节点采集电力施工现场安全质量信息,无线收发模块将节点采集的安全质量信息送至智能监测层,智能监测层利用ASP.NET MVC框架作为网页开发技术,选取ATMEI89C52微控制器作为数据处理芯片,数据处理芯片将卷积神经网络的电力施工安全质量监测算法固化在EEPROM内,监测电力施工现场是否存在安全质量问题,监测结果利用表示层展示至用户。测试结果表明,系统可以有效监测电力施工安全质量,不同类型电力施工安全质量问题的监测精度高于98%,可以避免发生电力施工安全事故。In order to avoid safety accidents caused by the lack of safety awareness of construction personnel,a monitoring system for power construction safety quality based on ASP was designed.ZigBee node was arranged in the electric power construction site to collect the safety and quality information of the electric power construction site through ZigBee node.The wireless transceiver module sent the safety and quality information collected by the node to the intelligent monitoring layer.The intelligent monitoring layer used ASP.NET MVC framework as the web page development technology,and selected ATME89C52 microcontroller as the data processing chip,The data processing chip solidified the power construction safety and quality monitoring algorithm of convolutional neural network in EEPROM to monitor whether there were safety and quality problems at the power construction site,and the monitoring results were displayed to users using the presentation layer.The test results showed that the system could effectively monitor the safety quality of power construction,and the monitoring accuracy of different types of power construction safety quality problems was higher than 98%,which could avoid power construction safety accidents.
关 键 词:电力施工 安全质量 监测系统 无线收发模块 卷积神经网络
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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