Research On Big Data Analysis Of Health Status Of Stacker

As the rapid development of informatization,it calls logistics enterprises' great attention gradually to monitor the running status of warehouse operation equipment in the process of modern storage equipment operation.The application of stacking machine is necessary in the large-scale three-dimensional warehouse,due to piling machine used as a main equipment of handling the goods,so its running state is of great significance for warehouse operation.In order to monitoring it's health status,we need to monitor the various parameters of the stacker which are very key to evaluate it's health state correctly and reasonably.We choose vibration parameters,noise parameters,temperature and humidity parameters,historical fault parameters and historical records of maintenance as five key indicators to evaluate it's health status.In this paper,I choose fuzzy comprehensive model based on dynamic weight as the final algorithm model to evaluate the health state of stacker.The monitoring data increase gradually with the monitoring to the stacker state,so the common evaluation methods can't meet the demands in the face of a large amount of historical data and real-time data.Data analysis technology use the corresponding Map/Reduce program can deal with the analyzing problems of large data better based on distributed cluster.This paper just take this advantage to deal with the data about health status of stacker.This paper studies rationality and necessity of health detection of stacker by introducing the studies and application on health status detection of electrical equipment at home and abroad.Aimed at the necessary technological means,I analyzes the theories and the mathematical models related to the big data.This paper uses the advantages of Hadoop distributed cluster environment to process mass of data,and analysis the parameters through the deployment of Hadoop cluster,and then introduces the cluster deployment process in detail.At last,I select the monitoring data within a few months to process on a Hadoop cluster through the actual test.And then get the conclusion through the fuzzy comprehensive evaluation model.Then come to a conclusion according to the analysis results.It can deal with the analytical task of large-scale data very good through analyzing historical by big data technology,and using fuzzy synthesis algorithm to evaluate the health status of stacker,which is also proved to be effective.The final part of this paper summarize the main work and propose the forecast to the further research.