Modeling And Fault Maintenance Of Swash Plate Axial Piston Pump Based On AMESim

Hydraulic pump is the core power component of the hydraulic system,in which the swash plate axial piston pump is widely used in the field of construction machinery.With the development of heavy machinery industry,the reliability requirements for pistion pump continue to increase,and lead to the probability of pump failure is also rising.Therefore,the fault diagnosis and health monitoring of pistion pumps is an effective means to improve the reliability of hydraulic systems.Whether the swash plate axial piston pump works normally will affect the healthy operation of the entire hydraulic system,and the forms of pistion pump failure is complex and diverse,and the diagnosis is complicated.Therefore,this paper studies the failure of the swash plate axial piston pump,so as to complete the failure identification and maintenance of the piston pump.The main research contents are as follows:(1)According to the working principle,motion and force analysis of the swash plate axial piston pump,summarize the failure mechanism of the piston pump.Three types of failures mainly studied in this paper are selected: internal leakage,insufficient oil suction pressure of oil inlet and oil pollution,and the three typical failure mechanisms of pistion pump are analyzed in detail.(2)Taking Rexroth A10VN0 pump as an example,the simulation model was established by using AMESim simulation software,and the real parameters of the piston pump simulation were set.The correctness of the model was verified by analyzing the simulation curve under normal state.The failure simulation of the pistion pump was realized by using the fault injection method,and the pressure and flow curves of the pump outlet were obtained.Finally,the maximum,minimum,average values of the outlet pressure and flow when the pistion pump is stable are used as the failure samples of the pump data.(3)As the BP neural network generally has slow convergence and prone to local minimums in the diagnosis of pistion pump faults,a particle swarm algorithm is proposed to optimize the BP neural network.In MATLAB,BP neural network and PSO-BP neural network are used to classify and identify the piston pump faults,and realize the diagnosis of three typical faults of the pistion pump,and achieve the purpose of fast and accurate fault diagnosis.It is proved that both of the two network models can be used for pistion pump fault diagnosis.By comparing the fault diagnos is results of BP neural network,it is concluded that the PSO-BP neural network has more advantages in the fault diagnosis of pistion pump.(4)According to the three typical faults of the piston pump,the onlinemonitoring system was established,and a predictive maintenance plan for the plunger pump was proposed to diagnose and repair the plunger pump in time,so as to prolong the service life of the pistion pump,and ensuring the pistion pump works safely and efficiently.