Session: Pumps 1

Paper Number: 111737

111737 - Numerical Study of an Axial Piston Pump : The Effect of Different External Loads on Pressure Ripples 

The axial piston pump (APP) is the key component in power hydraulic systems. As an important information source of APP condition monitoring, discharge pressure signals can reflect on the flow dynamics characteristics of the axial piston pump. However, pressure ripple is not only related to the health status of the pump, but also to the external load. There are various forms of hydraulic circuits, and it is necessary to study the pressure ripple and the mapping relationship between flow ripple and pressure ripple under the different load types. In this paper, a numerical study of the axial piston pump under different external loads type(loading with hydraulic motors or valves, with or without accumulators) is conducted to investigate the effect of external loads on pressure ripple characteristics. Firstly, an accurate 3D CFD model of APP connected to a pipe is established for obtaining the flow physics and simulating the internal fault in the pump. Then, at the end of the pipe, connected to the 3D CFD model of the hydraulic motor, the orifice equation, or a constant outlet pressure is chosen as the boundary condition of the pipe to simulate the situations of various hydraulic circuits(loading with hydraulic motors or valves, with or without accumulators). Finally, the analysis of pressure ripple characteristics under different external loads and different health status is conducted. The result shows that the pressure ripple of the pump is indeed influenced by the external loads and can provide a theoretical basis for condition monitoring of hydraulic systems.

Presenting Author: Chang Dong Shanghai Jiaotong University

Presenting Author Biography: Chang Dong received the B.S degree in mechanical engineering form Southeast University, Nanjing, China, in 2020. He is currently pursuing the Ph.D. degree in mechanical engineering with Shanghai Jiao Tong University,Shanghai,China. His research interests include machinery health monitoring, prognostics and health management, machine learninig, and signal processing.