Hydraulic system fault prediction method of hydraulic forging press based on digital twin system

The invention relates to a hydraulic system fault prediction method of a forging hydraulic press based on a digital twinborn system, which comprises the following steps: S1, acquiring geometric parameters of a hydraulic system of the forging hydraulic press, and constructing a digital twinborn model; s2, realizing digital twinborn model order reduction of the hydraulic system of the hydraulic forging press by using a DNN-based deep neural network, and establishing a parameterized model of the hydraulic system of the hydraulic forging press; s3, order reduction of the digital twin model of the hydraulic forging press is completed, and fault diagnosis and prediction of the hydraulic system are achieved. According to the method, a multi-scale physical model is adopted, data environment interaction between a physical space and a virtual space is achieved, and finally intelligent decision and maintenance of the hydraulic forging press are achieved. Fault diagnosis, online monitoring and performance optimization of