Extended Kalman Filter Algorithm for Advanced Diagnosis of Positive Displacement Pumps

Abstract In recent years many studies on detecting faults during the operation of positive displacement pumps have been initiated. Several diagnosis techniques that are based on the application of fuzzy logic or neural networks were applied to pump systems in order to increase their efficiency, safety and maintenance service level. However, certain characteristics and states of pumps (especially of positive displacement pumps) are currently not accessible with sufficient accuracy and reliability. One promising approach to tackle this situation is the implementation of the Extended Kalman Filter (EKF) to pump systems in order to estimate nonmeasurable but desirable signal data of these hydraulic units. A prototype implementation of an EKF for the signal data of a three screw spindle pump is described in this paper.

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