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Analysis and Failure Diagnoses on Hydraulic System of Combine Harvester

Author: HeLiPing
Tutor: WangCunTang
School: Jiangsu University
Course: Mechanical and Electronic Engineering
Keywords: Combine harvester Hydraulic system Fault Diagnosis Fuzzy Neural Network Matlab Labview
CLC: S225.3
Type: Master's thesis
Year: 2010
Downloads: 183
Quote: 0
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Abstract


Combines one of the essential equipment of modern agriculture and the introduction of intelligent diagnostic technology combines intelligent diagnostic harvester operating harvesters can not only improve the reliability , reduce the failure rate of the agricultural technology development of great significance. The hydraulic system combines occupy an important position , which controls the lift systems and walking harvester steering system , the event of the failure of the harvester can not normal operation of the hydraulic system fault diagnosis can shorten repair time and predictive failure trends facilitate timely maintenance . In order to achieve the intelligent diagnosis of the hydraulic system , the paper mainly do the following study : First , the analysis of the structure of the combine harvester hydraulic system , operation principle , and combined with the fault tree analysis method combing combines hydraulic system failure mechanism for quantitative failure analysis to provide the database information system later laid a theoretical foundation . Secondly, the discussion of the basic principles of fuzzy logic , neural network structure principle and learning training methods , instead of the membership function of the fuzzy system using neural network weights matrix , fuzzy systems and neural networks are combined to create a mathematical model of fuzzy neural network , combines fuzzy neural network - based the hydraulic fault diagnosis system is constructed . Again , the design of the data acquisition program for the fault diagnosis system . For system harvester diagnosis and effective integration of other control systems , to build a the harvester hydraulic failure diagnostic data collection platform mainly includes PLC data acquisition system and SCM data acquisition detection system and controller - IPC communications. Labview platform hydraulic system combines intelligent diagnosis . To using Labview design -friendly man-machine graphical interface is responsible for the communication and diagnostic results display ; deduced by the Matlab fuzzy neural network rules , to conduct a comprehensive analysis of the collected data and processing , to build fuzzy neural network reasoning model , fault diagnosis results show that combines hydraulic effectiveness of fault diagnosis system .

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CLC: > Agricultural Sciences > Agricultural Engineering > Agricultural machinery and implements > Harvesting machinery > Grain,wheat combine harvester ( Awn )
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