The invention discloses an intelligent fault diagnosis method based on a circulation neural network. The method comprises following steps of (1) by use of an acceleration sensor, acquiring time sequence vibration signals of a rotary machine during work in different health states, and dividing acquired original vibration signals into a training set and a test set; (2) establishing a circulation neural network; (3) training the circulation neural network; (4) testing the trained circulation neural network, according to a classification result, judging whether the network reaches an expected diagnosis target, and if the accuracy is lower than the expected value, repeating the step (3) until the circulation neural network whose accuracy is higher than the expected value is acquired; and (5) carrying out intelligent fault diagnosis through the circulation neural network obtained in the step (4). According to the invention, by use of the modeling ability for sequence information of the circulation neural network, the original time sequence vibration signals are directly processed, so faults of the rotary machine can be precisely diagnosed by use of lesser information, and quite high identification speed is achieved.