基于标量加权信息融合的智能故障诊断方法研究  

Intelligent Fault Diagnosis Method Scalar Weighted Information Fusion

作　　者：王金玉[1] 刘彤军[1] 王涛[1] 周丽丽[1] 杨喆[1] 

机构地区：[1]黑龙江省科学院自动化研究所,黑龙江哈尔滨150090

出　　处：《自动化技术与应用》2015年第7期62-65,共4页Techniques of Automation and Applications

摘　　要：为了满足生产过程中越来越复杂的系统,多传感器逐渐被引入到了故障诊断系统中,多个传感器的应用,使得故障诊断更加及时迅速。本文基于标量加权的线性最小方差最优信息融合算法,对多传感器离散线性随机系统,给出一种分布式标量加权信息融合Kalman滤波器,并在故障诊断中应用,通过仿真例子验证算法的有效性。In order to meet the production process increasingly complex systems, multi-sensor gradually being introduced into the fault diagnosis system, multiple sensor applications, making troubleshooting more promptly. In this paper, based on the integration of linear minimum variance optimal information scalar weighted algorithm, the multi-sensor linear discrete stochastic systems, presents a distributed scalar weighted information fusion Kalman filter and application in fault diagnosis, verification through simulation example of effective algorithms.

关 键 词：故障诊断 标量加权融合准则 KALMAN滤波 信息融合 

分 类 号：TP277.3[自动化与计算机技术—检测技术与自动化装置]