The Design Of Training And Application System In Virtual AWS Based On Lab VIEW

Meteorological disasters have high frequency and affect the people of a wide range in China. In order to meet the requirements of meteorological observation business, fifty thousand of automatic meteorological stations are equipped until 2015. With the purpose of making sure the data of automatic meteorological stations is accurate and reliable, the instrument structure and technique are fully optimized, which makes automatic meteorological stations are improved constantly. For this reason, a virtual automatic meteorological station system is designed for training and application based on LabVIEW development platform, which contains three parts including the modules of basic knowledge, fault information management and measurement error compensation.The basic knowledge module is deigned for training components of automatic meteorological stations. Therefore, the virtual instrument technology is introduced and the technical data of automatic meteorological station is interacted with the user in form of words, pictures and dynamic simulation, which can improve the learning initiative and creativity for meteorological professionals. In addition, the module can be used as self-study materials for operations personnel technology and technical training teaching of automatic meteorological station, which greatly facilitates the meteorological operations personnel for learning and mastery of the technology and ensures the normal operation of automatic meteorological station.The fault information management module can collect and search the information of automatic meteorological station, which implements the automatic meteorological station fault information within add, delete, change and check based on LabVIEW database technology and the failure analysis judgment process of automatic meteorological station. What’s more, the module searches the related fault information quickly and guarantees the maintenance experience accumulated, which improves the troubleshooting accuracy and timeliness of automatic meteorological station.The article designs another module for measurement error compensation of automatic meteorological station. The module establishes compensation model for meteorological observation data and enhance the observing quality by combining the virtual instrument technology, BP neural network and SVM. The experiment platform is set up including temperature humidity box, JJQ1 meteorological signal simulator and HMP45D humidity sensor. Further, the module is tested to verify the reliability and the results show that data errors are averagely reduced an order of magnitude, which means the designed module can effectively compensate the temperature influence on humidity sensor and enhance the humidity measurement accuracy of automatic meteorological station.