基于SVM和模糊专家系统的机械加工工序质量诊断

被引:2
作者
吴常坤 [1 ]
机构
[1] 江苏省特种设备安全监督检验研究院无锡分院
关键词
工序质量诊断; SVM; 模糊理论; 专家系统;
D O I
暂无
中图分类号
TH161 [机械加工精度理论]; TP182 [专家系统、知识工程];
学科分类号
0802 ; 1111 ;
摘要
为控制产品质量,诊断出机械加工工序误差源,本文提出了基于SVM和模糊专家系统的机械加工工序质量诊断方法。该方法以专家系统为载体,结合SVM和模糊理论,实现对机械加工过程中引起质量波动的异常误差源的诊断。
引用
收藏
页码:433 / 434
页数:2
相关论文
共 12 条
[1]   A fuzzy-based genetic approach to the diagnosis of manufacturing systems [J].
Khoo, LP ;
Ang, CL ;
Zhang, J .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2000, 13 (03) :303-310
[2]   Understanding ART-based neural algorithms as statistical tools for manufacturing process quality control [J].
Pacella, M ;
Semeraro, Q .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2005, 18 (06) :645-662
[3]   基于神经网络和模糊逻辑的加工误差源诊断系统 [J].
陈康宁,林志航,杨鸿鹏 .
西安交通大学学报 , 1995, (07) :60-66
[4]   零件加工误差原因诊断专家系统 [J].
傅晓锦 ;
张新华 .
机械设计与制造工程, 1999, (03) :42-44+5
[5]   用于机械加工误差源诊断的模糊专家系统设计 [J].
龚雯 .
现代制造工程, 2005, (05) :97-100
[6]  
Monitoring and Diagnosis of A Multi-stageManufacturing Process Using Bayesian Networks. Wolbrecht E,Ambrosio B D,Pasceh B, et al. Artificial Intelligence for Engineering Designand Manufacturing . 2000
[7]  
运用灰色理论分析诊断FI-PCNC数控铣床铣削加工误差源. 姜万生. 西安交通大学 . 1990
[8]  
Understanding ARI-based Neural Algorithms as Statistical Tools for Manufacturing Process Quality Control. Massimo Pacella,Quirico Semeraro. Engineering Applications of Artificial Intelligence . 2005
[9]  
Fault diagnosis of multistage manufacturingprocesses by using state space approach. Y. Ding,D. Ceglarek,J. Shi. Journal of Manufacturing Scienceand Engineering–Transactions of ASME . 2002
[10]  
Stream ofvariation modeling and diagnosis of multi–stationmachining process. HUANG Qiang,ZHOU Nairong,SHI Jianjun. Process of International MechanicalEngineering Congress and Exposition . 2000