Abstract
Since the environments the pumping units working in, is always severe and the dowhole condition is very complex, so it's difficult to diagnose the faults of the pumping units. The indicator diagram can be a good indication of the pumping unit's work conditions, it is also the main basis of fault analysis. Judging the pumping unit's faults using intelligent algorithms is also the demand of digital oilfield. The key is how to extract the indicator diagrams' features and what kind of intelligent algorithm is applicable. In this article, we first extract seven moment invariants of the typical faults' indicator diagrams, then we use ART2 neural network to classify these moment invariants. In which way, we can recognize pumping unit faults efficiently.
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