Abstract: An abnormal operation status detection method based on dynamic Hopfield artificial neural network（ANN） is designed for nuclear power plants. By online training of the ANN, it can be ensured that the ANN can tail after the normal change of the dynamic characteristics of the NPP caused by the change of its operation state, so as to reduce the possibility of misdiagnosis. By observing the weighted mean square error of the ANN predictive output and the real output of the device, the abnormal change of the parameters can be detected in early time. Taking the primary loop pressure of a NPP as example, several tests are performed to validate the ability of the method to detect the operation parameter abnormal change. The results show that within the entire operation spectrum of the NPP, the method exhibits well faculty of the parameter abnormal change detection.