Method for predicting abrasion of hob of slurry balance shield machine based on BP (Back Propagation) neural network

The invention belongs to the technical field of shield tunneling machines, and particularly relates to a slurry balance shield tunneling machine hob abrasion prediction method based on a BP neural network, which comprises the following steps: step 1, constructing a hob abrasion data set which comprises data samples of tunneling parameters influencing hob abrasion along with time change in shield construction; the method comprises the following steps of 1, establishing a hob abrasion parameter set, 2, according to the hob abrasion loss and a tunneling ring number parameter corresponding to the hob abrasion loss, distributing the hob abrasion loss to each tunneling ring to obtain the abrasion loss of each tunneling ring of the hob, 3, establishing a BP neural network model, inputting the hob abrasion parameter set in the step 1 and the abrasion loss of each tunneling ring of the hob in the step 2 into the BP neural network model for training, and 4, establishing a BP neural network model. And performing predict