基于数据挖掘的复杂机械产品质量关联分析方法  

Quality Correlation Analysis Method of Complex Mechanical Products Based on Data Mining

作　　者：武亚琪 杨晓英[1,2] 杨逢海 闫欢欢 李博 WU Yaqi;YANG Xiaoying;YANG Fenghai;YAN Huanhuan;LI Bo(School of Mechanical Engineering,Henan University of Science and Technology,Luoyang 471003,China;Henan Collaborative Innovation Center of Advanced Manufacturing of Machinery and Equipment,Henan University of Science and Technology,Luoyang 471003,China)

机构地区：[1]河南科技大学机电工程学院,洛阳471003 [2]河南科技大学机械装备先进制造河南省协同创新中心,洛阳471003

出　　处：《组合机床与自动化加工技术》2025年第3期78-82,共5页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：河南省重点研发专项项目(231111222600)。

摘　　要：针对复杂机械产品属多零件、多工序、各零件工序质检参数之间有着复杂的关联关系,直接影响产品装配质量这一关键问题,改进设计Apriori算法,将复杂装备数据转换成三元组形式输入,挖掘各工序质检参数精度等级间的关联关系,找出精度误差传递规律。通过算法对比分析和在回转结晶器产品上应用,验证了关联分析算法的有效性,对优化复杂机械产品工艺和提升工序质量提供技术支撑。In view of the complex relationship between the quality inspection parameters of multi-parts,multi-process and each part process of complex mechanical products,which directly affects the key problem of product assembly quality,the Apriori algorithm is improved and designed.The complex equipment data is converted into three-tuple input,and the relationship between the accuracy levels of the quality inspection parameters of each process is excavated to find out the law of accuracy error transmission.Through the comparative analysis of the algorithm and the application in the rotary crystallizer products,the effectiveness of the correlation analysis algorithm is verified,which provides technical support for optimizing the process of complex mechanical products and improving the process quality.

关 键 词：复杂机械产品 质量分析 改进Apriori算法 FP-GROWTH算法 

分 类 号：TH162[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]