摘要
针对基于故障数据的数控装备可靠性研究中的小样本问题,提出了建立基于支持向量机的性能劣化模型。在研究支持向量机的建模理论和参数优化方法的基础上,将最小二乘法支持向量机工具LSSVM.M应用于性能退化数据处理,提出一种改进的参数选择方法,以提高拟合和预测准确性。通过实例,验证了该方法的可行性,并建立了数控机床加工精度的性能劣化模型,为可靠性评估奠定了基础。
In order to solve the small samples problem in reliability assessment based on failure data of Numerical Control （NC） equipments, the method of degradation modeling based on Support Vector Machine （SVM） was proposed. After studying on modeling theories of SVM and the parameter optimization of SVM, the Least Squares Support Vector Machines tool （LSSVM. M） was used to process the performance degradation data. An improved parameter selection method was presented, which improved the veracity of simulation and forecasting. After validating by examples, the performance degradation model of NC machining accuracy was established, which laid foundation for reliability assessment.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2009年第4期685-689,共5页
Computer Integrated Manufacturing Systems
基金
国家863计划资助项目(2006AA04Z407)
国家自然科学基金资助项目(50705036)~~
关键词
支持向量机
性能劣化模型
退化数据
可靠性评估
数控系统
support vector machine
performance degradation model
degradation data
reliability assessment
numerical control system
