摘要
离心泵是过程工业使用广泛的关键设备。使用中泰公司的数据采集和信号调理模块,对离心泵运行状态在线监测。系统基于Visual C++开发,对软件中涉及到的监测数据存储、曲线显示和多线程等关键技术进行改进和代码优化,有效的提高了系统的实时性和可靠性。针对基本G(1,1)模型预测精度差的缺陷,选用新陈代谢G(1,1)模型进行状态预测,并对状态预测模型进行了实例验证。
Centrifugal pump is the key equipment that used widely in process industry.Based on Visual C + + development,the system is exploited for centrifugal pump online monitoring by Zhongtai's data acquisition and signal conditioning modules.In this software,the key technologies such as storage for monitoring data,curves display and multi-thread of monitoring system were improved and the code was optimized.It can effectively raise the real time and reliability.For the basic G(1,1) models to predict the defects of poor accuracy,select the metabolic of G(1,1) model,the state forecast model was tested and verified by example.
出处
《微计算机信息》
2010年第25期13-14,3,共3页
Control & Automation
基金
基金申请人:周云龙
项目名称:基于小波分析和神经网络信息融合的离心泵在线监测与故障诊断
基金颁发部门:吉林省教育厅(NO200747)