Aiming at the challenging problems such as the measurement of key load parameters of ball mill under multi-operating conditions

a soft sensor model based on domain adaptation with manifold regularization (domain adaptation with manifold regularization

DAMR) for measuring wet ball mill load parameters is proposed. Firstly

the feature transformation matrix is found by using the integrated manifold constraints

the maximum variance and the maximum mean discrepancy. Then

the feature information of the source domain and the target domain are projected into the common subspace. Finally

the model established in the subspace is used to predict critical load parameters. The results show that the proposed method can predict the critical load parameters of wet ball mill under the unknown condition with high precision

and this method has some reference value for the soft sensing of mlti-operating conditions in process industry and process monitoring.