A Novel Approach to Determine Dredge Pump NPSHR in Field Conditions
CEDA Dredging Days 2017 - Sustainable Dredging - Continued Benefits
Abstract: The dredge pump is one of the core components of dredging vessels such as the trailing suction hopper dredger and the cutter suction dredger. The pump is a key part of the hydraulic transport system and determines the production of the dredging vessel. One of the main characteristics of a dredge pump is its suction capability. This suction capability is described by the required net positive suction head (NPSHR). Having a NPSHR with low values leads to better production rates in vacuum limited situations and is therefore of paramount importance for a dredge pump. The dredge pump is subject to erosive wear, as it used to pump sand-water mixtures. The wear on the pump impeller also influences the NPSHR of the pump. So the NPSHR characteristics of the pump can detoriate over time due to the wear of the pump. Determination of the NPSHR characteristics can be a complex task. It involves manipulation of the inlet pressure while keeping other parameters constant. A number of approaches exists. In practice, these approaches are mainly suited for use on the controlled environment of a pump test stand. For measurement in the field, on a pump mounted in a dredger, it is far more dicult to get good measurements. We describe a novel approach to measure the NPSHR characteristics in field conditions. The data is obtained with a straightforward measurement. A post-processing method with a solid mathematical background is used to obtain the NPSHR characteristics. The practical application of the method is illustrated with example data. The proposed method can be employed to implement real-time monitoring of cavitation, enabling optimization of the production in vacuum limited situations. Also, the detoriation of NPSHR can be monitored over time, which can be used to implement condition based maintenance. An outlook on these aspects is given.
Key words: dredge pump, condition based maintenance, NPSHR measurement, big data analysis