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变压器油中微水含量在线监测系统研究
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摘要
变压器油是变压器内部重要的液体绝缘介质,起绝缘、冷却和消弧的作用。变压器油中存在的微量水分会使设备的绝缘性能大大降低,严重时可导致绝缘击穿、烧毁设备等重大事故。通过控制变压器油中微水含量不仅可以防止其绝缘强度降低至危险水平,还可以对变压器整体绝缘状况进行评估以及对设备密封性做出判断。因此,对变压器油中微水含量实施在线监测对变压器设备的安全可靠运行具有十分重要的意义。
     论文研究了变压器油中水分产生的原因,变压器中水分动态变化的机理以及油纸间水分含量平衡关系,分析了变压器油中微量水分的存在形态以及对变压器绝缘性能的危害。针对现行变压器油中水分测量方法的不足和局限,提出了对变压器油中微水含量实施在线监测的具体方法。
     结合目前湿度传感器的研究现状,以及在线监测的具体要求,选择了聚酰亚胺薄膜电容式湿度传感器作为微水含量监测传感器。设计了变压器油中微水含量在线监测系统;通过对传感器输出信号的转换,实现了温湿度信号利用计算机串口的数据采集;并对湿度传感器在变压器油环境中的特性进行了研究。
     通过分析变压器油中水分的相关理论,建立了基于神经网络的变压器油中水分监测模型;该模型不仅可以评估变压器油中的微水含量,而且通过比较油中微水含量的模型计算值与其测量值,可以发现变压器中导致油中微水含量异常变化的故障。并通过模拟实验验证了该模型的准确性。
The transformer oil is an important liquid dielectric material in the transformer; it plays the roles of insulation, cooling and extinction of arc. The presence of moisture can deteriorate transformers’insulation performance drastically. Severely, it can lead to some catastrophic accidents such as insulation breakdown and transformer burnout. Through the control of moisture content in oil, it can not only prevent insulation strength from decreasing to dangerous level, but also evaluate the whole insulation status of transformers, and estimate the leak tightness of the apparatuses. Hence, the on-line monitoring of moisture in transformer oil is of great significance to the operation safety of transformers.
     The generation reasons of moisture in oil, the mechanism of moisture dynamics in the transformer oil, and paper-oil moisture equilibrium is studied in the paper. Also the moisture states existing in oil and the hazard to transformer insulation property is analyzed. Considering the disadvantage and limitation of current measurements of moisture in oil, a detailed scheme of on-line monitoring for moisture in oil is proposed.
     Considering the study status of sensors and the requirement of on-line monitoring, the polyimide-based capacitive humidity sensor is selected as moisture sensor. The on-line monitoring system for moisture in transformer oil is developed. Through the conversion of the output of sensor, data sampling of moisture and temperature signals are realized with the computer serial ports. The performance of sensor in the transformer oil condition is studied.
     According to the analysis of the relevant theoretical foundation of moisture in transformer oil, a moisture-in-oil monitoring model based on neural network is put forward in the paper. This model can not only estimate moisture in transformer oil, but also can detect faults which can cause the abnormal variation of water content in the transformer oil through comparing the value of estimated moisture with the measured ones. And the validity of the model confirmed through simulation experiments.
引文
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