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基于智能集成的水轮发电机组温度在线监测系统
引用本文:李生民,石争浩,孙旭霞.基于智能集成的水轮发电机组温度在线监测系统[J].大电机技术,2004(4):38-40.
作者姓名:李生民  石争浩  孙旭霞
作者单位:西安理工大学,陕西,西安,710048;西安理工大学,陕西,西安,710048;西安微电子技术研究所,陕西,西安,710054
摘    要:提出一种基于智能集成的水轮发电机组温度在线监测系统,利用数据融合对多个温度传感器的测量数据进行融合分析,以融合后的数据作为水轮发电机组温度最优估计,利用神经网络完成专家系统的正向推理,由专家系统的反向推理机完成反向推理,自主完成发电机组温度的在线监测.与传统温度监控系统相比,本系统决策误差信息小,具有较好的实时性和准确性.介绍了该系统的总体框架结构及关键技术.

关 键 词:神经网络  专家系统  数据融合  智能集成  在线监测
文章编号:1000-3983(2004)04-0038-03
修稿时间:2003年8月3日

Temperature Online Monitoring System for Hydrogenerator Units Based on Intelligence Integrated
LI Sheng-min.,SHI Zheng-hao.,.,SUN Xu-xia..Temperature Online Monitoring System for Hydrogenerator Units Based on Intelligence Integrated[J].Large Electric Machine and Hydraulic Turbine,2004(4):38-40.
Authors:LI Sheng-min  SHI Zheng-hao    SUN Xu-xia
Affiliation:LI Sheng-min.1,SHI Zheng-hao.1,2.,SUN Xu-xia.1
Abstract:A real-time temperature online monitoring system for a hydrogenerator units based on intelligence integrated is proposed. Measure datum of each tempe rature sensor is fused as the optimization estimation of the hydrogenerator unit temperature. The hydrogenerator units temperature online monitoring is automati c done by direct reasoning of the expert system with BP neural network and rever se reasoning of the expert system with its reverse reasoning unit. Compared with traditional temperature monitoring system, decision-making error information of this system is less, and it has better real-time performance and veracity. The basic frame structure of this system and its key technology is introduced.
Keywords:artificial neural network  expert system  data fusion  intelligence integrated  online monitoring
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