摘要
风速风向是气象观测的关键性参数,阴影效应对超声测风仪测量风速风向有显著影响。为了消除不同风速风向和温度条件下阴影效应导致的测量误差,结合超声波时差法测风原理提出了一种基于计算流体力学(CFD)仿真和反向传播(BP)神经网络数据处理的阴影效应补偿方法。首先通过CFD仿真软件Fluent对超声测风仪的风场进行模拟分析,获取了受阴影效应影响的风速、风向以及温度样本数据,然后利用这些样本从减小相对误差方面对BP神经网络算法在超声测风仪中应用的性能进行了研究与分析,最后利用超声测风仪风洞实验的测量数据对本文的阴影效应补偿方法的准确性进行了验证。研究结果表明:通过基于CFD和BP神经网络的预测模型对阴影效应进行修正后,测试系统风速风向的测量精度有显著的提升,可满足高精度超声测风的测量需求。本文的研究结果对于高精度超声测风仪的研制有一定的参考价值。
Wind is a critical parameter of meteorological observation,and the shadow effect has a significant effect on the wind speed and direction measured by the ultrasonic anemometer. In order to eliminate the measurement error caused by the shadow effect under different wind speed and temperature conditions,a shadow effect compensation method based on computational fluid dynamics（CFD） simulation and back propagation（BP） neural network data processing is proposed in combination with the measuring principle of the ultrasonic time difference method. Firstly,the CFD simulation software—Fluent is used to simulate the wind field of ultrasonic anemometer. The wind speed,wind direction and temperature sample data affected by the shadow effect are obtained,and then the performance of BP neural network algorithm in ultrasonic anemometer is studied and analyzed by using these samples to reduce the relative error. Finally,the accuracy of the shadow effect compensation method in this paper is validated by using the wind tunnel data of the ultrasonic anemometer. The results show that the accuracy of the wind measurement is significantly improved after correcting the shadow effect by the prediciton model based on CFD and BP neural network,which can meet the high precision measurement requirements of ultrasonic anemometer. The results of this study have a certain reference value for the development of high precision ultrasonic wind measurement instrument.
作者
张加宏
孙林峰
李敏
冒晓莉
葛益娴
ZHANG Jiahong 1,2,3 ,SUN Linfeng 3,LI Min 1,3,4,MAO Xiaoli 1,3 ,GE Yixian 1,2,3(1.Jiangsu Key Laboratory of Meteorological Observation and Signal Processing,Nanjing University of Information Science and Technology,Nanjing 210044,China;2.Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology,Nanjing University of Information Scienceand Technology,Nanjing 210044,China;3.School of Electronic andInformation Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;4.CMA Research Centre on Meteorological Observation Engineering Technology,Beijing 100081,Chin)
出处
《传感技术学报》
CAS
CSCD
北大核心
2018年第8期1201-1210,共10页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(61306138
61307061
41605120)
江苏省气象探测与信息处理重点实验室/江苏省气象传感网技术工程中心联合开放基金课题项目(KDXS1407
KDXS1504)
中国气象局气象探测工程技术研究中心开放基金课题
江苏省高校品牌专业建设工程项目(TAPP)
关键词
超声测风仪
阴影效应
CFD仿真
BP神经网络
数据融合补偿
实验验证
ultrasonic anemometer
shadow effect
CFD simulation
back-propagation neural network
data fusion
experimental verification
