Data-driven modeling method with reverse process

The factors that affect the performance of the equipment are numerous and complicated, which makes it difficult to establish a performance calculation model. This paper puts forward a data-driven modeling method with reverse process for this problem. Based on the partial least squares (PLS) algorithm and the gray relational analysis (GRA) method, the analysis method of the performance related factors, the extraction method of characteristic variables, and the performance modeling method are studied. The related factors of the energy consumption of an industrial steam turbine are analyzed, and an energy consumption calculation model is established, and the effectiveness of the above-mentioned modeling methods is verified with sample data, which provides a basis for the energy-saving optimization of the steam turbine.