Fluid-dynamic analysis of an in-line water piston pump

Abstract

The paper focuses on the analysis of inline water piston pumps, by means of simulation of the fluid-dynamic behaviour and experimental characterization. These pumps are commonly used on the car wash systems, industrial washes systems and fire protection systems. They possess a robust architecture, made of a typical rod-crankshaft mechanism, which transforms the circular motion of the pump shaft in the reciprocating displacement of the piston. The pump analyzed in the paper, in particular, moves three pistons, shifted one another of 120°; each piston sucks from a tank and delivers water to a hydraulic line via automatic, spring loaded, poppet valves. The shaft, rod and other movable components are lubricated with mineral oil; the three ceramic pistons are isolated from this environment using opportune seals and work with water. This pump is robust and durable but suffers of some problems: the instantaneous pressure trend within each piston is ideally a square wave: the pressure is equal to the tank pressure during suction, while it is equal to the delivery pressure during the delivery phase. Instead, non –ideal behaviour of the poppet valves, leakages, fluid properties make the pressure trend more critical: during the pressure transient between the two high and low levels, pressure peaks and de-pressurization till aeration and cavitation occurrence may happen. These phenomena generate vibrations and noise and can damage the pump components. In order to study this, a lumped parameter fluid dynamic model of the pump has been realized, later compared with experimental results coming from the test rig to validate it. The model has been used to explore the dynamic pump behaviour in several operating conditions (various speed values and delivery pressure levels), calculating the flow irregularity, the pressure and forces instantaneous trends. The design characteristics of the poppet valves have been explored, in particular the spring characteristics, to discuss the trend of the previous variables.