Research On Industrial Internet Plus Condition Monitoring And Fault Diagnosis System For Hydraulic System Of Hydraulic Servo Motor

With the rapid development of the new generation of information technologies such as big data,cloud computing and Industrial Internet of Things(IIoT),it also provides new theory and technology for research on condition monitoring and fault diagnosis systems(CMFDS)of equipment.The integration of new information technology and traditional hydraulic technology has further developed,it has important theoretical significance and practical value to develop CMFDS of hydraulic servo motor based on IIoT.Therefore,the hydraulic system of hydraulic servo motor was employed as the object,and mining fault information from condition monitoring data was taken as target.Through the technology of IIoT,it has opened the information channels of signal data acquisition,edge data processing,cloud data transmission,massive data elastic storage,fault diagnosis modeling and analysis.The research provides a new theory,technology and method for the CMFDS of hydraulic system of hydraulic servo motor.Firstly,according to the theory of CPS,a six-tier architecture of system-level CPS is proposed for the CMFDS,which covering various functional requirements from data acquisition to data analysis.Then the WISE-PaaS was selected as the carrier to build the functional architecture of the CMFDS of hydraulic servo motor based on IIoT.Secondly,the hydraulic system of hydraulic servo motor is divided into two working states: normal adjustment and fast closing buffering.And on the AMESim simulation platform,the faults of the nozzle and damping hole of the electro-hydraulic servo valve,the leakage in the hydraulic cylinder,and the degradation of the electromagnetic performance of the solenoid valve are simulated.By exploring the effective data sources needed for the CMFDS,it provides theoretical guidance for the data access of the IIoT.Thirdly,aiming at the leakage fault of the hydraulic servo motor in the normal regulating state.Based on the single value classification algorithm of SVDD,a new model of leakage fault diagnosis in hydraulic cylinder is constructed by using the minimum and maximum eigenvalues of the time-domain signal of the pressure condition monitoring of the two chambers of hydraulic cylinder.It provides a model algorithm for fault diagnosis of hydraulic cylinder of hydraulic servo motor on the IIoT.Fourthly,aiming at the fault diagnosis of the electromagnetic performance degradation of the two position three way valve,which the control component of the hydraulic servo motor fast closing buffering system.Based on the data-driven modeling of the outlet pressure signal of the solenoid valve,a new fault diagnosis method of the hydraulic solenoid valve based on the combination of PCA and XGBoost is proposed.It provides a method for fault diagnosis of fast closing solenoid valve on the IIoT.Finally,the CMFDS of the new hydraulic servo motor is developed on the WISE-PaaS.Functional modules are developed from signal data collection,edge feature extraction,cloud data analysis,etc.It provides a specific solution for the " industrial internet plus CMFDS for hydraulic system of hydraulic servo motor".The research results of this paper can not only provide a new method for the construction of the CMFDS of the hydraulic servo motor on IIoT.It also is an example of the integration of hydraulic technology and industrial Internet technology.