厂房温湿度检测仪器运行状态预测算法设计
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摘要
状态预测是厂房温湿度检测仪器预防性维护的重要组成部分,也是提高厂房温湿度检测仪器使用寿命的有效措施。本文针对BP神经网络在设备状态预测中的不足,提出基于BP神经网络的L-M优化算法,用以对厂房温湿度检测仪器预测中。通过仿真和实验相结合的方法,采用原始样本数据对厂房温湿度检测仪器进行预测。研究表明,基于BP神经网络的L-M优化算法能够实现对厂房温湿度检测仪器的状态预测,并且误差较小,证明了该方法的有效性。
State prediction is an important component of preventive maintenance of plant temperature and humidity measuring instruments.It is also an effective measure to improve the service life of temperature and humidity measuring instruments.In this paper,a L-M optimization algorithm based on BP neural network is proposed according to the deficiency of BP neural network in equipment state prediction.Through the combination of simulation and experiment,the original sample data is used to predict the temperature and humidity of the building.The research shows that the L-M optimization algorithm based on BP neural network can realize the state prediction of the temperature and humidity detection instrument of the factory building,and the error is small,which proves the validity of the method.
State prediction is an important component of preventive maintenance of plant temperature and humidity measuring instruments.It is also an effective measure to improve the service life of temperature and humidity measuring instruments.In this paper,a L-M optimization algorithm based on BP neural network is proposed according to the deficiency of BP neural network in equipment state prediction.Through the combination of simulation and experiment,the original sample data is used to predict the temperature and humidity of the building.The research shows that the L-M optimization algorithm based on BP neural network can realize the state prediction of the temperature and humidity detection instrument of the factory building,and the error is small,which proves the validity of the method.
引文
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[2]雷亚国,陈吴,李乃鹏,等.自适应多核组合相关向量机预测方法及其在机械设备剩余寿命预测中的应用[J].机械工程学报,2016,01:87-93.
[3]秦琳琳,马国旗,储著东,等.基于灰色预测模型的温室温湿度系统建模与控制[J].农业工程学报,2016,S1:233-241.
[4]王子洋,秦琳琳,吴刚,等.基于切换控制的温室温湿度控制系统建模与预测控制[J].农业工程学报,2008,07:188-192.
[5]谭静芳.温室温湿度智能测控系统的设计[J].农业装备技术,2014,01:28-30.
[6]周伟,汪小旵.温室温度约束模型预测控制研究[J].新疆农业科学,2014,06,1015,1021.
[7]孙浩文.基于单片机的温室温湿度采集系统设计[J].自动化与仪器仪表,2017,03:198-200.
[8]王远航,邓超,胡湘洪,等.基于性能退化的机械设备寿命预测[J].计算机集成制造系统,2015,08,2147,2157.
[9]沈敏,张荣标,盛碧琦,等.温室测控系统开关设备优化组合预测控制方法[J].农业机械学报,2011,02:186-189+161.
[10]李春林.无线传感器网络温湿度采集系统[D].陕西:西安电子科技大学,2014.
[11]衣翠平.基于无线传感器网络的粮库温湿度实时监控系统研究[D].吉林:长春理工大学,2012.
[12]豆刚军.机房热管理试验平台开发研究[D].陕西:西安电子科技大学,2013.
[13]冯媛硕,宋吉江.基于单片机的温湿度检测控制系统设计[J].山东理工大学学报(自然科学版),2014,(1):57-59.
[14]李娜,张明玉,汪材印.基于单片机的图书馆温湿度远程控制系统设计[J].赤峰学院学报(自然科学版),2013,(3):147-149.
[15]李有堂,张正谦,丁海荣,等.基于Zig Bee和Lab VIEW的车库无线监测系统设计[J].兰州理工大学学报,2016,(1):204-206.
[16]王玉刚,赵兴堂,董绪华,等.基于Lab VIEW的多功能显示模拟器设计[J].现代电子技术,2015,(18):74-76.
[17]Daudi S.Simbeye,Jimin Zhao,Shifeng Yang.Design and deployment of wireless sensor networks for aquaculture monitoring and control based on virtual instruments[J].Computers and Electronics in Agriculture,2014,(8):654-667.
[18]Lun-Wu Yeh,Meng-Shiuan Pan.Beacon scheduling for broadcast and convergecast in Zig Bee wireless sensor networks[J].Computer Communications,2013,(5):1147,1156.