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实时监测中设备状态的自适应采集算法
引用本文:周晓军,沈炜冰,奚立峰.实时监测中设备状态的自适应采集算法[J].上海交通大学学报,2008,42(12):1975-1978.
作者姓名:周晓军  沈炜冰  奚立峰
作者单位:上海交通大学机械与动力工程学院,上海市第一污水管理所
基金项目:国家高技术研究发展计划(863)项目 , 上海市登山计划项目  
摘    要:设备状态的按需采集是平衡数据数量和质量的有效手段.基于移动平均理论,采用区域限值方法建立了一种自适应采集算法,并通过与等间隔采集方法的对比验证了其有效性.通过有无干扰两种情况下的算例仿真,结果显示,自适应采集方法对于设备状态加速变化时的状态捕捉能力优于等间隔采集方法,是设备实时监测时数据采集的一种较好的替代方案.

关 键 词:设备  数据采集  自适应  移动平均

An Adaptive Sampling Algorithm for Real Time Monitoring of Equipments
ZHOU Xiao-jun,SHEN Wei-bing,XI Li-feng.An Adaptive Sampling Algorithm for Real Time Monitoring of Equipments[J].Journal of Shanghai Jiaotong University,2008,42(12):1975-1978.
Authors:ZHOU Xiao-jun  SHEN Wei-bing  XI Li-feng
Institution:ZHOU Xiao-jun~1,SHEN Wei-bing~2,XI Li-feng~1
Abstract:Adaptive monitoring is a good solution to balance the quantity and the quality of sampling data.For this sake,an adaptive sampling algorithm was proposed based on the moving average theory and the range constraint method.Then,an analysis method was given to show how to prove the availability of the proposed adaptive algorithm.Two kinds of numerical simulation were implemented,with or without considering the external interfering.The simulation results show that the ability of hunting the variation of equipment condition for adaptive method is much better than the one for periodical method.Therefore,the proposed adaptive sampling algorithm is a good alternative for the data acquisition in real time monitoring.
Keywords:equipment  data acquisition  adaptive  moving average
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