Self-tuning of Teachless Process Monitoring Systems with Multi-criteria Monitoring Strategy in Series Production☆
Self-tuning of Teachless Process Monitoring Systems with Multi-criteria Monitoring Strategy in Series Production☆
复制标题
在批量生产中采用多标准监控策略进行无示教过程监控系统的自调整â
DOI：
10.1016/j.protcy.2014.09.022
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Dahlmann
中科院分区：
文献类型：
--
作者：
Denkena;Dahlmann
机床中的现代监控系统能够及时检测过程错误。然而，由于安全监测参数化的复杂性，限制了监测系统的应用。在大多数情况下，只有经过专门培训的人员才能在多主轴机床或车铣中心处理这项工作。研究项目“Proceed”的目的是确定在何种程度上可以实现工业系列生产中监控系统的自参数化和独立优化。因此，处理链的完整参数化，包括信号源的选择、特征提取、监控和决策策略，应自动化。研究了基于遗传算法的多目标监测系统的自参数化问题。
Modern monitoring systems in machine tools are able to detect process errors promptly. Still, the application of monitoring systems is restricted by the complexity of parameterization for save monitoring. In most cases, only specially trained personnel can handle this job at multi-spindle machines or turn-mill centers. The aim of the research project “Proceed” is to figure out in which extent a self-parameterization and independent optimization of monitoring systems in industrial series production can be realized. Therefore, the complete parameterization of the processing chain, consisting of the choice of signal sources, character extraction, the monitoring- and decision making strategy, shall be automated. This paper deals with the self-parameterization of a multi-criteria monitoring system based on a genetic algorithm.
DOI：
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发表时间：
2012
期刊：
影响因子：
--
作者：
Markos Papageorgiou;Marion Leibold;M. Buss
通讯作者：
M. Buss