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一种在线分析变压器故障特征气体的智能传感器
引用本文:佟继春,陈伟根,陈荣柱. 一种在线分析变压器故障特征气体的智能传感器[J]. 高压电器, 2004, 40(6): 433-435,438
作者姓名:佟继春  陈伟根  陈荣柱
作者单位:重庆大学,重庆,400044;温州电业局,浙江,温州,325000
摘    要:在线监测变压器油中溶解气体可有效地分析变压器绝缘状况,在线监测用气体传感器是实施该技术的关键。针对半导体气体传感器的交叉敏感特性,提出了将气体传感器阵列与人工神经网络技术相结合,利用6个半导体气体传感器组成传感器阵列,采用BP神经网络进行模式识别。大量的试验证明,所提出的智能传感器可有效地提高H2,CO,CH4,C2H4,C2H2,C2H66种气体的分辨率和检测灵敏度。

关 键 词:变压器  油中气体  在线监测  智能传感器
文章编号:1001-1609(2004)06-0433-03

One Intelligent Sensor for Online Analysis of Oil-dissolved Gas in Transformer
TONG Ji-chun,CHEN Wei-gen,CHEN Rong-zhu. One Intelligent Sensor for Online Analysis of Oil-dissolved Gas in Transformer[J]. High Voltage Apparatus, 2004, 40(6): 433-435,438
Authors:TONG Ji-chun  CHEN Wei-gen  CHEN Rong-zhu
Affiliation:TONG Ji-chun1,CHEN Wei-gen1,CHEN Rong-zhu2
Abstract:Online detection technology of transformer oil dissolved gas can be used to analyze insulation status of transformer effectively, and the gas sensor in online detection is crucial to this technology. Using the intersection sensitivity for semiconductor gas sensors, this paper presents a smart sensor integrating gas sensor array with artificial neural network technology. The author employs gas sensor array consisting of six semiconductor sensors and BP neural network to do pattern recognition. Lots of experiments prove that the smart sensor can improve resolution and sensitivity of online detection on six gases of H2, CO, CH4, C2H4, C2H2 and C2H6 .
Keywords:transformer  oil dissolved gas  online monitoring  intelligent sensor  
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