摘要
为了获得多工位制造系统足够的有效测量信息和最大化多工位制造系统的偏差源监测能力,应采用合适的测量策略并对传感器布置进行优化.在状态空间模型基础上,建立了多工位制造系统中3个偏差源与传感器测量值间的空间关系,给出了量化描述系统偏差源监测能力的方差监测敏感度系数,以及将数据挖掘算法与进化算法相结合的传感器布置的优化方法,解决了最大化多工位制造系统偏差源监测能力的传感器布置优化问题.通过箱形工件加工实例,验证了该方法的有效性.
In order to achieve sufficient as well as effective measuring sensing data,an optimal sensor distribution system should be carried out so that maximal error source detection capability is enabled.The spatial relationship between three types of error sources and measuring sensing data in multistation manufacturing system was established based on the state space model,and a variance-detecting sensitivity index was proposed for characterizing the detection ability of process variance components.Then a data-mining-guided evolutionary method was devised to solve the optimization problem for sensor distribution.An（illustrative） example was performed to validate the importance and effectiveness of the proposed analytical procedure.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2010年第12期1753-1757,共5页
Journal of Shanghai Jiaotong University
基金
高校博士点专项科研基金资助项目(20070248021)
国家自然科学基金资助项目(70932004)
上海市教委科研创新重点项目(09ZZ19)
关键词
传感器布置
多工位制造系统
状态空间模型
敏感度
数据挖掘
进化算法
sensor distribution
multistation manufacturing system
state space model
sensitivity
data mining
evolutionary algorithms
