| Space Environment Simulation and Research Infrastructure,a major national scientific and technological infrastructure,is an important measure to promote space exploration.The microscopic sub-system is responsible for revealing the microscopic mechanism of material and device performance degradation and failure.It is mainly composed of closed experimental equipment,open experimental equipment and bottom-level experimental equipment,and the bottom-level experimental equipment mainly includes the helium detection equipment in the helium monitoring subsystem and the experimental equipment of the ultra-high vacuum interconnection and sample transfer platform.In order to realize the intelligence and informatization of the microscopic sub-system and ensure its normal and effective operation,this paper takes the experimental equipment in the microscopic sub-system as the research object,and uses the industrial communication network as the technical support to study the experimental equipment data collection and equipment condition monitoring methods suitable for the microscopic sub-system.Firstly,this paper clarifies the requirements for data collection and equipment condition monitoring by analyzing the structure of the microscopic sub-system,the characteristics of the communication network,and the data.This paper proposes a hierarchical monitoring strategy oriented to the microscopic sub-system,analyzes the method of information interaction between levels,and conducts a principle analysis of the related technologies involved in the hierarchical monitoring strategy.Secondly,for the closed experimental equipment that uses the private protocol computer experimental software to complete the experiment process,taking the experimental software as the research object,a method of data collection and condition monitoring of the experimental equipment based on image recognition technology is proposed.Through the automatic capture of the experimental software interface and dynamic event monitoring,the functions of data collection and condition monitoring are realized,and the programming is implemented in Python language,which verifies that the method has high reliability and accuracy.Then,for the open experimental equipment with data interoperability interface,the hardware composition of the data acquisition system is analyzed,and a method for data acquisition using database access interface,file access interface and remote access control interface is proposed.Aiming at the helium detection equipment of the helium monitoring subsystem,the hardware composition of the data acquisition using the helium monitoring subsystem is analyzed and the software program design is carried out.Aiming at the experimental equipment of the ultra-high vacuum interconnection and sample transfer platform,a method of using the TANGO control system to realize the data collection of the experimental equipment is proposed,and the test and analysis are carried out according to specific examples.Finally,in order to realize the function of monitoring the operating status of the experimental equipment,based on the K-means clustering analysis algorithm and the Back Propagation(BP)neural network model,this paper proposes a device condition monitoring strategy based on Analysis of Power Load Characteristics(APLC)technology,analyzes the specific implementation method of using this strategy for device condition monitoring,and uses two devices in the EMBED data set to verify the feasibility of the proposed strategy. |
