The invention discloses a time dimension expansion and local weighting extreme learning machine-based soft measurement modeling method. A local weighting extreme learning machine-based method aims at a nonlinear process and has good intensive reading performance and relatively high calculation speed, but a data quantity of an industrial process is often short of generalization performance when an extreme learning machine is applied. An applied improvement method is that a sample is subjected to time dimension expansion in time dimension by adopting a just-in-time learning thought, and local weighting is performed in a new space, thereby aiming at a dynamic characteristic of the industrial process. According to the method, the advantages and the main shortcomings of the just-in-time learning thought and the extreme learning machine are combined and overcome, so that a high-speed high-precision industrial process soft measurement modeling method is obtained.