Research On Real Time Data Collection And Analysis Methods For Discrete Intelligent Workshops

Discrete intelligent workshops have been widely applied in numerous industries and fields,driving the upgrade and transformation of small and medium-sized enterprises with its intelligent discrete manufacturing mode.At present,small and medium-sized enterprises generally suffer from problems such as incompatible communication protocols between old equipment with new equipment and untimely data acquisition,which makes it impossible to meet the requirements for data integrity and real-time of discrete intelligent workshops.Therefore,it is urgent to study a real-time data acquisition and analysis method for discrete intelligent workshops.By exploring key issues such as real-time communication,data acquisition,and data analysis,this paper proposed a method for real-time data acquisition and analysis of discrete workshops based on a unified communication management platform.The following of this paper main research contents and results.(1)A research plan for real-time data acquisition and analysis methods was proposed.Based on the actual situation of enterprises and the research status at home and abroad,the research ideas of discrete intelligent workshops,data acquisition and transmission,and data mining analysis were analyzed.Thus,a research plan was suggested,involving equipment interconnection for real-time communication,integration management based on Niagara architecture,and the fusion and mining of multi-source data.(2)A technical architecture for the interconnection in discrete intelligent workshops was designed.By analyzing the characteristics and needs of discrete intelligent workshops as well as the principles of interconnection,a three-layer architecture was proposed featuring on-site workshops equipment,collection communication analysis,and application management coordination.Finally,the interconnection of the underlying equipment in the discrete intelligent workshops was completed,combined the real-time communication transmission plan based on publish/subscribe mode with data mining analysis method.(3)A unified communication management platform and a multi-source data fusion model were constructed,to address the problems of incompatible communication protocols between old equipment with new equipment and inconsistent multi-source data.Firstly,through three aspects of the workshops interface connection,unified communication protocol,and real-time transmission middleware,a standardized and unified real-time communication method was established.Then,based on the abstraction of the underlying equipment hardware of the workshops with Niagara architecture,a unified communication management platform for the underlying equipment of the discrete intelligent workshops was constructed to integrate old and new equipment and collect data.Finally,based on the analysis of the energy consumption mechanism of discrete manufacturing,combined with relevant queries,PCA dimensionality reduction,feature parameters,and data binning processing,a unified encoding multi-source data fusion model(MEDM)was constructed to provide support for subsequent data mining analysis.(4)An energy consumption data mining and analysis algorithm for discrete intelligent workshops was proposed,to solve the problem of complex parameter relationship analysis between massive production energy consumption data.By comparing and analyzing the characteristics and shortcomings of data mining methods,an FP-Growth-DW algorithm which adapted the problems of discrete workshops was proposed,to optimize run-time speed,computational complexity,and rule accuracy,using techniques such as partition parallel method,pruning optimization technology,evaluation indicators and rules library.Finally,through the analysis of a corporate example model,the efficiency and mining effect of the algorithm were improved in both the association rules and the algorithm efficiency.(5)A real-time data acquisition and analysis management system was developed for the discrete intelligent workshops.Combined with the theoretical research and enterprise requirements in this paper,suitable technical architecture was selected based on the Java development environment.The real-time data collection and analysis system for discrete intelligent workshops was developed and tested,including device integration management,data acquisition,and data mining and analysis functions.Finally,the practicality of the method and theory proposed in this paper in real-time data collection and analysis of discrete intelligent workshops was verified.