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In this paper, an intelligent fault diagnosis method is presented to solve the problem that the accuracy of pumping unit fault diagnosis is not high. This method selects the Shape invariant moment and the Fourier descriptor to extract the characteristic parameters of the sample indicator diagram, and uses the BP neural network optimized by iterative learning control to classify and identify. Finally, the expert diagnosis method is used to compare the recognition results to obtain the diagnosis result. The experiment shows that the method is fast, accurate and intelligent.

Research on fault diagnosis of indicator diagram based on BP neural network optimized by iterative learning control