实时监测中设备状态的自适应采集算法

An Adaptive Sampling Algorithm for Real Time Monitoring of Equipments

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.

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 con- sidering 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.