摘要
针对目前常用切削加工表面粗糙度预测方法存在预测精度不高、泛化能力不强的问题,提出一种融合模糊和随机性的粗糙度云预测新方法。在分析大量试验数据的基础上给出了多维预测云的数字特征和数学模型,设计粗糙度预测的多维多规则定性推理发生器,将各切削用量作为前件云输入,分析其对粗糙度后件云的影响关系,并通过对推理规则的多元组合,实现不同加工工艺规范下对工件表面质量的精准预测,揭示加工表面质量随切削参数变化的规律。试验结果表明,在相同样本条件下所提方法的平均相对预测误差低于4.78%,求解速度和预测精度方面均有所提高,且预测范围更加广泛。
Aiming at the problems of lower prediction accuracy and narrower prediction range for the common prediction method,a new surface roughness prediction method based on multidimensional multi-rules reasoning of cloud model is put forward.Based on analyzing a large quantity of test data,the digital characteristic of a multidimensional cloud is represented and the generator on multidimensional multi-rules for qualitative reasoning is designed firstly.Then through combining the reasoning rules in various modes,the accurate surface roughness prediction is realized with the cutting speed,feed rate and cut depth as the input conditions and the predicted roughness values as output,thus the variation law of quality of machined surface following milling parameters can be obtained.Finally,experimental results show that the presented method is more accurate with the average relative prediction error below to 4.78% in the same conditions.Compared with other prediction models,the presented model makes the information classification and accuracy prediction more precise,and the predicted range wider.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2016年第15期204-212,共9页
Journal of Mechanical Engineering
基金
国家自然科学基金(51365022)
云南省教育厅重点(2014Z032)资助项目
关键词
粗糙度
云模型
多规则推理器
精准预测
roughness
cloud model
multi-rules reasoning generator
accuracy prediction
