The invention discloses an intelligent fault diagnosis method for a pump station main device, and relates to the field of signal processing. The method comprises the steps of collecting a data signalof a to-be-tested key part of a to-be-tested pump station main device in a working state, and using the data signal as a to-be-tested sample; and inputting the to-be-tested sample into a VMD-gcForestdiagnostic model, sequentially drawing a modal function spectrum diagram and performing a multi-granularity cascade forest diagnosis to obtain a working status label corresponding to the to-be-testedsample, and obtaining the working state of the to-be-tested key part according to the working status label. The intelligent fault diagnosis method of the invention solves the problem that the waveletbasis function and the filtering threshold existing in an original vibration signal extraction process cannot be determined in the prior art; the problems of a lack of theoretical basis, the end pointeffect and the modal aliasing of EMD; and the problems that the existing fault diagnosis method based on the original vibration signal is extremely complicated in parameter adjustment, time-consumingin calculation, and low in diagnostic accuracy.