Analysis And Failure Diagnoses On Hydraulic System Of Combine Harvester

As one of the modern agricultural machines, combine harvester is important in the harvest season.The intelligent diagnose can improve the reliability of the harvester and has great significance in agricultural technology. Hydraulic system plays an important role in controlling the lifting, walking and steering of combine harvester, if the system is in failure, the harvester cannot work in normal condition.so the fault diagnosis online can reduce time and maintain the harvester easily by predicting the failure of hydraulic system.Firstly, the structure and principle of the hydraulic system is analyzed and the fault mechanism based on the fault-tree method and the possible results caused by the fault are discussed. This work provides database information for the quantitative analysis of the fault of hydraulic systemSecondly, the basic principle of fuzzy logic, the structure of neural network and its training way are discussed. A method based on the combination of fuzzy algorithm and neural network is applied to the fault diagnosis of hydraulic system.Thirdly, considering the data collection method for the Fault Diagnosis System, a data collection test bed of the hydraulic system in the combine harvester is established for the combination of the Fault Diagnosis System and other parts, including a data collection based on PLC and single chip independently. We implement the the communication between the hardware and the indtrusy computer.At Last, an intelligent diagnosis of the combine hydraulic system is accomplished on Labview. We design a friendly man-machine interface with the Labview, a fuzzy neural network rules is derived and the feature data are extracted, processed and diagnosed with the Matlab. The experimental results show that the hardware platform of fault diagnosis system is effective for the hydraulic system.