基于蚁群粒子群混合算法的PDC钻头侧向力平衡优化

OPTIMIZATION OF LATERAL FORCE BALANCE OF PDC BITS BASED ON ANT COLONY PARTICLE SWARM HYBRID ALGORITHM

为了突破PDC钻头结构对侧向力平衡优化设计的限制,尝试采用融合了蚁群算法和粒子群算法(PSO)的混合算法对PDC钻头侧向力平衡进行优化,充分利用PSO算法的快速、全局收敛性和蚁群算法的正反馈机制,建立了PDC钻头侧向力平衡优化设计方法。通过该混合算法对刀翼式PDC钻头侧向力平衡的优化设计,结果表明,与单独采用PSO优化的结果相比,能够得到更好的优化结果,算法收敛速度更快,优化的刀翼周向位置角更好。

while optimizing a polycrystalline diamond compact(PDC) bits structures in terms of the lateral-force balance,the number of objectives to be optimized is more and the searched scope for the optimum solution grows quickly.In order to break the limit to optimization design of lateral force balance from bit structures,a new optimization design method by ant colony particle swarm hybrid algorithm was developed.The fast convergence of particle swarm optimization(PSO) and the positive feedback mechanism of ant colony algorithm are used.A blade bit was optimized by this hybrid algorithm.It has fast convergence and can find better bit's cutting structure,thus its results of optimization for blade bits are better than that of PSO.