摘要
针对目前岩土工程所用监测系统的实时性差、可靠性低的问题,提出基于低功耗处理器LPC1768与CAN(Controller Area Network)总线通讯相结合的分布式监测系统。通过设计智能节点对岩土工程的稳定性进行实时监测,获得其状态参数值;基于粒子群算法建立预测模型,对坝体浸润线高度进行预测。将该系统应用在坝体监测工程中,结果表明:该系统稳定可靠,预测精度较高,满足工程要求。
In view of the poor real-time and low reliability of the monitoring system used in geotechnical engineering,a distributed monitoring system based on the low power consumption processor LPC1768 and CAN (controller area network)bus communication is proposed in this paper. The stability of geotechnical engineering is monitored in real time through the design of intelligent nodes,and the state parameters are obtained. The prediction model is established based on PSO)(particle swarm optimization to predict the height of saturated line of dam. The system is applied in monitoring engineering. And the result shows that the system is stable,reliable and processing high prediction accuracy,which meets the engineering requirements.
引文
[1]田帅帅.煤矿顶板动态监测系统CAN总线网络监控器设计[J].煤矿安全,2016,47(3):114-117.Tian Shuaishuai.Design of CAN-bus Network Monitor in Dynamic Monitoring System of Coal Mine Roof[J].Safety in Coal Mines,2016,47(3):114-117.
[2]丁爱华.CAN总线在采矿塌陷区大型厂房监测系统中的应用[J].金属矿山,2015,(4):212-215.Ding Aihua.Application of CAN bus in Large Plant Monitoring System in Mining Subsidence Area[J].Metal Mine,2015,(4):212-215.
[3]崔荣荣,郑伟.基于CAN总线的分布式超声形变监测系统[J].计算机工程,2012,38(19):238-246.Cui Rongrong,Zheng Wei.Distributed Ultrasonic Deformation Monitoring System Based on CAN Bus[J].Computor Engineering,2012,38(19):238-246.
[4]程刚,施斌,张平松,等.采动覆岩变形分布式光纤物理模型试验研究[J].工程地质学报,2017,25(4):926-934.Cheng Gang,Shi Bin,Zhang Pingsong,et al.Physical Model Test Study On Deformation Of Over Lying Strata During Coal Mining With Distributed Fiber Optic Deformation Monitoring[J].Journal of Engineering Geology,2017,25(4):926-934.
[5]李冬辉,贾冠龙,姚乐乐,等.基于LPC1768的能耗采集系统的设计[J].仪表技术与传感器,2016,(3):48-51.Li Donghui,Jia Guanlong,Yao Lele,et al.Design of Energy Acquisition System Based on LPC1768[J].Instrument Technique and Sensor,2016,(3):48-51.
[6]Zhi Huang HUANG,Jun LIN,Dan LV.High-Precision Monitoring and Controlling System of Temperature and Humidity Based on CAN Bus[J].Applied Mechanics and Materials,2012,1603(148).
[7]郭嘉,周苗苗.基于DS18B20的干式变压器无线温度监测系统[J].电测与仪表,2014,51(22):92-96.Guo Jia,Zhou Miaomiao.Dry-Type Transformer Wireless Temperature Monitoring System Based on DS18B20[J].Electrical Measurement&Instrumentation,2014,51(22):92-96.
[8]邹卫霞,王多万,杜光龙.基于粒子群优化的频域多信道干扰对齐算法[J].北京邮电大学学报,2016,39(3):22-26.Zhou Weixia,Wang Duowan,Du Guanglong.On Particle Swarm Optimization for Multi-Frequency Channel Interference Alignment[J].Journal of Beijing University of Posts and Telecommunications,2016,39(3):22-26.
[9]Zhou C,Tao J.Adaptive combination forecasting model for China’s logistics freight volume based on an improved PSO-BP neural network[J].Kybernetes,2015,44(4):707-710.
[10]SHI Y,EBERHART R.Empirical study of particle swarm optimization[A].International Conference on Evolutionary Computation[C].Washington,USA:IEEE,1999:1945-1950.