变压器油中溶解气体在线监测及故障诊断系统研究

【作者】 黄德祥；

【导师】 曹建；

【作者基本信息】 中南大学 ， 物理电子学， 2004， 硕士

【摘要】 变压器在线监测及故障诊断技术,对提高电力系统的安全稳定性具有十分重要的意义,其中基于油中溶解气体分析的在线监测技术是变压器在线监测中最普遍,也是最重要的技术。目前已投入使用的油中溶解气体在线监测系统普遍存在一些不足,如检测气体种类少、准确度及精确度不高、体积大、成本高等。 本文对变压器油色谱在线监测及故障诊断系统进行了研究,分析了其它色谱在线监测方法的种种不足,对其进行了改进,设计了一套变压器油在线监测系统,能够及时、准确地监测变压器油中溶解的各种特征气体,实时地反映设备的运行状态,并对故障诊断算法进行了仿真。提出了将基于MEMS技术的微型热导池检测器用于变压器油在线监测系统当中。为了提高监测设备灵敏度、增加分离度和可靠性,并减小设备体积,通过理论分析和大量的实验,结合检测器特点,确定了气相色谱柱所用的固定相,以及柱内径、柱长、柱压、样气量等各项操作参数。 根据电站高电压设备和在线监测技术的特点,提出了一种基于数据融合的数据处理算法,该算法用分布图法剔除疏失误差,并用基于递推估计的数理统计方法对采样数据进行处理,既滤除了干扰又保留了测量数据的局部与全局特性。通过实验比较,证明了该算法的有效性。 在获得真实可靠的监测数据的基础上,还进行了运行状态预测的故障诊断方法的探讨,提出了基于BP神经网络的故障诊断方法,建立了一个诊断模型,并对该模型进行了仿真,仿真结果表明该算法明显优于传统IEC三比值法等故障诊断方法,能够比较准确地定性和定量地对故障做出判断,为电力运营部门提供有用的决策依据。更多还原

【Abstract】 Techniques for on-line monitoring and fault diagnosis of transformer play an important role in improving the security and the stability of the power system, and that of on-line monitoring based on dissolved gas analysis in the transformer oil is the most popular and important techniques in the fields of on-line monitoring of transformer. Some universal defects exit in the running products, for instance, only a few kinds of gases can be detected, the accuracy is not enough, the monitoring equipment is large in volume, and the cost is high.The paper is concerned with the chromatography on-line monitoring and fault diagnosis system. To overcome the insufficiency of other on-line monitoring methods, this paper has made it improved. And based on the analysis, a gas monitoring system of transformer oil is designed in this paper. The system can accurately monitor the characteristic gases dissolved in the transformer oil, reflecting the running states of the transformer real-timely. This paper also studies and emulates the algorithm of the fault diagnosis. A method using micro-volume thermal conductivity detector based on MEMS technology is presented in this paper. To improve the sensitivity of the monitoring equipment, increase the segregation degree and stability, and reduce the volume of the equipment, based on theory analysis and experiments, considering the characteristic of the detector, the stationary phase and operating conditions, including column internal diameter, column length, column pressure and sample quantity are determined.According to the characteristic of the high voltage equipments and the on-line monitoring technology, an algorithm based on data fusion is put forward in this paper. The negligence errors are eliminated by the method of distribution diagrams, and the statistical method based on recurrence estimation are used to the sample data processing. The algorithm remains the local and global characteristics of the measured data. The results of experiments have proved the validity of the method.On the basis of getting the true and reliable monitoring datum, the methods of diagnosis algorithm based on state predicting are alsodiscussed in this paper. A method based on BP artificial neural network is presented. A diagnosis model is also designed and emulated. The results of the emulations show that the algorithm is obviously better than that of the traditional three-ratio method, and the algorithm can accurately makes good judgments on the faults base on qualitative and quantitative analysis.更多还原