电力变压器绝缘油中溶解气体区域概率分析方法

Ming-Jong Lin
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摘要

变压器绝缘油在电力变压器中发挥着极其重要的作用,用于绝缘、消弧、冷却和其他用途。然而,它的另一个重点是分析油中的溶解气体,以监测内部运行状况,这也是预防性维护的职责所在。本文采用正态分布理论和美国国家标准规范(以下简称 ANSI/IEEE C57.104)进行重组,作为诊断工具。将规范中正常、谨慎和异常三个阶段的每种气体的范围都纳入异常阶段,并将其分为相等的 1000 个不同值,作为定性正态分布的母体。然后根据这些定性正态分布参数计算出基准值。检测数据必须通过 "气相色谱法 "产生溶解气体。 最后,将基准值与溶解气体进行比较,找出异常概率值,作为设备维护评估的诊断工具。该方法使用 EXCEL 应用软件开发,并通过实例反复测试和验证,以确认其可行性和高准确性。此外,还从文献[11]中提取了 10 例事故数据,并与实际维护结果进行了对比。ANSI/IEEE C57.104 的准确率为 80%,而本概率法的准确率为 90%。因此,这种诊断方法可以取代传统的多阶段判断,用单一的概率值来表示。 基于技术分享,特将开发过程写成技术文章,供电力工程领域的学者和电气维护人员参考。设计方法:利用 EXCEL 软件和 ANSI/IEEE C57.104 的判别规则制作定性正态分布。 设计目的:作为绝缘油中溶解气体的诊断工具。 设计效果:概率法优于传统方法;它具有这些功效--准确性和可行性,可与经过试验和测试的实际案例相媲美。
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The Method of the Probability Analysis of Area with Dissolved Gases in Power Transformer Insulating Oil
Transformer insulating oil plays an extremely important role in power transformers and is used for insulation, arc suppression, cooling and other purposes. However, its other focus is on dissolved gases analysis in the oil to monitor internal operating conditions, which is the responsibility of preventive maintenance. This paper uses the normal distribution theory and the American National Standard Specification (hereinafter referred to as ANSI/IEEE C57.104) to reorganize as a diagnostic tool. The range of each gas from three stages of the specification - normal, caution, and abnormal are incorporated to a stage of abnormal, which divide into equal different values of 1000 as the maternal body of a qualitative normal distribution. Then the benchmark is been calculated from those parameters of a qualitative normal distribution. The data of detection has to pass through "Gas chromatography” to generate dissolved gases.  At last, the benchmark value compares with dissolved gases to find the abnormal probability value as a diagnostic tool in maintenance evaluation of equipment. This method was developed using EXCEL application software, and repeatedly tested and verified with examples to confirm its feasibility and high accuracy. In addition, 10 cases accident data were extracted from the literature [11], and compared with the actual maintenance results. The accuracy was 80% for ANSI/IEEE C57.104 and 90% for this probability method. Therefore, this diagnostic method can replace the traditional multi-stage judgment and be represented by a single probability value to show.  Based on technology sharing, the development process is specially written into a technical article as reference by scholars and electrical maintenance personnel in the field of power engineering. Design Methods: Making a qualitative normal distribution employs EXCEL software and the discriminative rule of ANSI/IEEE C57.104.  Design Purpose: As a diagnostic tool with dissolved gases in insulating oil.  Design Effectiveness: Probability Method is better than traditional; it has those efficacies - the accuracy and feasibly and compete with tried and tested actual case.
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