Cloud Platform Based Remote Fault Diagnosis System For Lysimeters

The lysimeter is an important device for studying the water transport principle in the soil-plant-atmosphere continuum.It plays an important role in promoting water conservation in farmland,guiding water-saving irrigation and studying the growth law of crops.The lysimeter is an unattended device and its installation site is usually remote and scattered.It is therefore difficult to find the fault in time,which seriously restricts the normal operation of the lysimeter.In view of this,this paper designs a remote fault diagnosis system of lysimeter based on cloud platform.The system uploads the data collected by the lysimeter to the cloud platform through wireless communication technology,and uses the Kalman filter algorithm and threshold detection mechanism to detect the abnormality of the data.On the basis of this,a Bayesian network-based fault diagnosis method is used to analyze abnormal data to infer the cause of equipment failure.The application results show that the system can effectively detect the abnormal information of the lysimeter and give the cause of the failure,which is of great significance to ensure the correctness of the monitoring data.The main research work and contributions can be summarized as follows:(1)Based on the system requirements analysis,the system requirements are analyzed in both functional and non-functional terms.Then,a three-layer system framework based on the physical device layer,network transmission layer and software application layer is designed.The structure lays the foundation for the design and implementation of remote fault diagnosis system of lysimeter.(2)By analyzing the characteristics of the data collected by the lysimeter,and using Kalman filter algorithm and threshold detection mechanism to detect abnormal data of the lysimeter,a fault diagnosis method based on Bayesian network is designed to realize the remote detection and diagnosis of lysimeter data abnormalities and faults.(3)By using the SSM framework and combining with modular design ideas,the abnormal data detection and equipment fault diagnosis modules for the remote fault diagnosis system of lysimeter is designed in detail,the abnormal detection of remote data acquisition and fault diagnosis of the corresponding modules of lysimeter are realized.(4)The remote fault diagnosis system of the lysimeter based on the cloud platform is deployed and tested,and the dry land agricultural research institute of the Gansu Academy of Agricultural Sciences is taken as an example for promotion and application.The results show that the remote fault diagnosis system of the lysimeter can effectively detect and diagnose equipment faults and greatly reduce the generation of invalid data.