风电轴承环成形缺陷数值模拟与工艺优化

Numerical Simulation and Process Optimization Methods of the Forming Defects in Wind Turbine Bearing Ring

风电轴承环属于大型异形环状零件,环件轧制技术是目前成形该类零件的主要方法。环件轧制过程中金属流动复杂,轧制孔型与环件之间接触情况复杂,同时由于轧制用毛坯、轧制工艺参数等原因,导致轧制过程中出现多种缺陷,缺陷的出现降低了环件质量,甚至使零件报废。该文针对风电轴承环轧制过程中出现的直径不扩大、椭圆度缺陷,运用Deform 3D软件对0134090003p6轴承成形过程进行模拟,提出当环件轧制到一定尺寸时,改用胀形工艺成形,获得了精度较高的环件,该工艺具有一定工程实用价值。并运用正交试验设计,发现影响胀形环件综合性能的主要因素是胀形坯料的尺寸形状,同时得到了该工艺的近似最优参数组合。采用粒子群优化算法优化相应的SVR参数,用训练好的SVR模型对胀形结果进行预测,得到一个可以预测环件胀形性能的SVR模型,该模型对工程实践有较好的辅助价值。

The main method of forming wind turbine bearing,which belongs to large abnormity section ring,is Ring rolling technology.The complexity of metal flow,and contact between rolling groove and ring,as well as the rolling blank and the inaccuracy of rolling process parameters,etc.often lead to various defects,which greatly lower the quality of the ring,even lead to scrapped parts.This paper puts forward rolling-bulging composite forming process by using Deform 3 D numerically simulate the defects of the not expanding of diameter and ovality of 0134090003 p6 in ring rolling.This process is proved to haven certain engineering practical value because of obtaining a high precision ring.These research finds the main impact factors of ring bulging overall performance is shape and size by using Orthogonal array designing and the approximate optimal combination at the same time.Using particle swarm optimization algorithm to optimize the corresponding SVR data,trained SVR models are used for predicting the result of ring bulging.The aim is to get a SVR model that can predict the ring bulging properties.This model has good auxiliary value in engineering practice.