Monitoring vibration signatures produced by axial piston pumps can provide insight into changes of the pump system, which may then be associated with early signs of mechanical or hydraulic component failures. To replicate these conditions using physical experiments and sensor-based measurements on pumps is often costly and time-consuming. Therefore, in order to better understand the failure mechanisms, specifically of the swash plate bearing, simulation models are constructed to develop a vibration-based health monitoring procedure to predict hydrostatic bearing failure within an axial piston pump. First, a one-dimensional multi-physics model of an axial piston pump is developed with a representation of the swash plate bearing interface. Next, a series of physical and virtual experiments is designed and used to obtain parameters for this model; these include measured transfer functions that relate housing accelerations to dynamic forces. The model is then utilized to quantify dynamic hydraulic and mechanical loads within the pump as well as to estimate acceleration on the pump housing under a variety of operating conditions. Finally, by detecting changes in acceleration spectra due to a simulated failure, a robust vibration-based health monitoring metric is defined. The resulting metric seems to consistently detect hydrostatic bearing failure under a wide range of pump operating conditions; it is somewhat insensitive to variations in model parameters. This research could ultimately be used by agricultural, industrial, and aerospace pump manufacturers to gain insights into preventative maintenance guidelines, to identify the least damaging and quietest pump operating regimes, and to screen design concepts before building prototypes.Eaton CorporationNSF I/UCRC Smart Vehicle Concepts (SVC) CenterA one-year embargo was granted for this item.Academic Major: Mechanical Engineerin
