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基于粒子群优化算法的数控机床可靠性建模研究
Research on CNC Machine Tools Reliability Modelling Based on PSO
【摘要】 对某型号数控机床进行可靠性试验,采集故障数据。在此基础上,建立可靠性模型,推断属于威布尔分布,并进行可靠性模型分析;采用粒子群优化算法对威布尔分布的尺度参数α和形状参数β进行估计。研究结果表明,采用此方法建立的可靠性模型较传统的更加准确。
【Abstract】 Reliability test for a certain NC machine tool was carried out. Failure data were collected. On this basis, a reliability model was established. It was inferred that it was a Weibull distribution. The reliability model was also analyzed. PSO(particle swarm optimization)algorithm was used to estimate the scale parameter α and shape parameter β of Weibull distribution. Research results show that the reliability model established by this method is more accurate than the traditional one.
【关键词】 数控机床;
可靠性建模;
粒子群优化算法;
参数估计;
故障时间;
【Key words】 NC machine tool; Reliability modeling; PSO algorithm; Parameter estimation; Failure time;
【Key words】 NC machine tool; Reliability modeling; PSO algorithm; Parameter estimation; Failure time;
【基金】 国家自然科学基金面上项目(51775261);南京工程学院校级重大项目(CKJA201402;CKJA201602);江苏省海洋科技创新专项(HY2017-3)
- 【文献出处】 机床与液压 ,Machine Tool & Hydraulics , 编辑部邮箱 ,2020年20期
- 【分类号】TG659;TP18
- 【被引频次】3
- 【下载频次】214