The Application Of Data Mining Technology In The Fault Diagnosis Of Postal Packet-Automatic Sorting Machine

With the growing of data in human social life,using data mining technology can find valuable information,especially in the field of mechanical fault diagnosis,through the data mining to predict equipment fault,can reduce and avoid the big loss.Now express logistics industry rapid development,in order to enhance the capacity of processing,the use of automatic sorting machine is a massive increase in postal,the equipment in use process there are a lot of failure,accumulated a lot of production data at the same time,through the study of the data and analysis,found using different data mining techniques which is related to the fault knowledge,can provide useful guidance for fault diagnosis.This text studies the mechanical fault diagnosis of conventional methods and content,the basic model of data mining,the development of modern logistics technology and automatic sorting machine,and main methods of data mining technology are studied.In this paper,the postal equipment failure of automatic sorting machine was studied,the control system,mechanical system,bearing,shaft,gear.etc fault characteristics and reasons are analyzed,before data analysis,the operation data of the main monitoring of equipment was pretreated.Using a decision tree model,based on SPSS statistical analysis tools,the decision tree model of the discrete and continuous field in the data is established and analyzed respectively,the fault diagnosis conclusion,and the control system and mechanical system fault maintenance scheme is proposed.