PSO-BP Control Algorithm of Granulation Process Based on Evaluation and Optimization of Granularity Distribution

李勇,; 吴敏,; 曹卫华,; 赖旭芝,; 王春生,

doi:10.3724/sp.j.1004.2012.01007

Cited by 3 publications

(1 citation statement)

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“…Mathematical algorithms, as essential tools for parameter optimization, can search globally for optimal conditions for various objectives. The particle swarm optimization algorithm (PSO) [27,28] has a fairly fast search speed and cannot easily find the local optimum through the deterministic local search algorithm. Nath [29] optimized the fuel ratio and negative pressure conditions for the two sintering layers using a genetic algorithm so as to obtain the optimal sintering quality.…”

Section: Introductionmentioning

confidence: 99%

Fuel-Appropriate Distribution of the Material Layer Based on Numerical Model of Sintering with Particle Swarm Optimization Algorithm

et al. 2023

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An optimization model for the fuel distribution of the material layer with mechanism models and algorithms is presented, which can reduce the fuel ratio of ore blending and enhance the fuel content in the upper layer to improve the homogeneity of the sinter quality. The actual fuel distribution of the material layer is analyzed through the granulation model and the theoretical fuel distribution for each unit is obtained using the numerical model. Then, the fuel particle size composition and segregation characteristics are optimized via the particle swarm optimization algorithm to bring fuel distribution close to the theoretical value, with a sum of their absolute values of 0.025. In comparison with the initial conditions, the fuel particle size composition conforms to a normal distribution with increased coarse particles, and the deviation of the granules from the vertical direction of the sinter layer decreases. Through this optimization method, the sinter bed with the ideal thermal profile can be achieved, namely uniform sintering along with a reduced coke ratio.

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Section: Introductionmentioning

confidence: 99%