Multiobjective Optimization of Roadheader Shovel-Plate Parameters Using Gray Weight and Particle Swarm Optimization

As the working efficiency and life span of shovel plate a roadheader directly influence its performance, optimization shovel-plate parameters is crucial. For optimizing parameters, variations in loading capacity grubbing force with respect to are determined this study. Moreover, ideal point method gray weight proposed for multiobjective optimization. The weights resistance by investigating existing molded products through decision method. Thereafter, particle swarm (PSO) algorithm applied parameters. Considering EBZ230-type as an example, parameter decreases mass 14.3% 7.3%, while increasing 1.4%. To demonstrate optimization, coal rock excavation simulated using optimized ANSYS-Workbench environment. results indicate that maximum stress at front 22.1%, minimum fatigue increases 139.6%, safety factor 30.3%. obtained establish that, based on PSO, optimize This can provide theoretical basis reference values design plates be engineering well.