Information Analysis And Processing Of Meteorological Integrated Metrology System

Meteorological disaster is a serious threat to people's life and property.Recently,Accurate detection based on meteorological data on weather forecasting,weather warning can reduce the loss in many industries,and accurate weather prediction depends on the meteorological instruments,the overall performance of the sensor,calibration and assessment tests about the instruments.Meteorological data includes radiation,atmospheric pressure,humidity,temperature,and in order to reduce the impact of sensitivity of the instrument on monitoring the meteorological data,it is necessary to carry out verification of these monitoring instruments and data analysis.In this paper,for the monitoring of meteorological instruments pyranometer,JJG 458-1996 Verification Regulation is selected.This paper introduced wavelet algorithm to process the data and verify it's influence on the sensitivity.There are three aspects of the radiation meter calibration system.They are data collection,data analysis,and system alarms.In terms of data collection,this paper used serial asynchronous communication transmission mode,the transmission of meteorological data and interactive interface design based on the Windows platform to facilitate automated monitoring staff,batch data collection.And stores the data into EXCEL spreadsheet for easy viewing.In data processing,this paper discussed the influence of the abnormal sensitivity of the senser and about processing the abnormal sensitivity,this paper analyzed the advantages and disadvantages of the Layida,Xiaoweile,Grubbs and Dixon guidelines.In using these guidelines to process the gross errors,we focus on the wavelet transform algorithm to remove the outliers,which include the decomposition,thresholding and reconstruction,we use the matlab to simulate the result of wavelet processing,and the result is satisfying.About the alarm system,in order to ensure the accuracy of the monitoring system,this paper research several environmental factors which may effect the radiation table data,including temperature,humidity,cloud cover,etc.With the process of stepwise regression equation,multidimensional linear regression prediction model,it will be timely alarmed if there are abnormal test data.