The paper uses modern control theory and mechanical and structural vibration theory to study a mass-spring system of three degrees. Using Newton's first law analyzing the force of the object, drawn the simulation diagram from the control perspective. Reflecting all changes of the independent variables and their relationships. And revealing the characteristics of the system. We also analyzed the system can not only be controlled but also can be observed, understanding the inherent nature of the system further. About the dynamic characteristics of the system, we use the main formation method to calculate the natural frequency, the main formation and displacement response of the system[1].

Sulfur-containing prebaked anodes, mainly made from petroleum coke, can give rise to SO2 emission in the production of electrolytic aluminum. In order to study the correlation between the emission volume and desulfurization rate of the flue gas discharged from the calcination of petroleum coke, a traditional double hidden layer BP neural network model was established on the basis of BP neural network by taking the emission data of the petroleum coke calcination flue gas desulfurization system as input parameters. This model was used to predict the desulfurization rate of the petroleum coke calcination flue gas desulfurization system, with an aim to control the SO2 removal rate of flue gas through controlling the flue gas parameters of the desulfurization system, so as to reduce SO2 emission from the flue gas of the electrolytic aluminum industry. The study will be of practical significance for the SO2 removal of the petroleum coke calcination flue gas.