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首页> 外文会议>International Conference on Computer Engineering and Systems >Incipient Fault Detection of Electric Power Transformers Using Fuzzy Logic Based on Roger's and IEC Method
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Incipient Fault Detection of Electric Power Transformers Using Fuzzy Logic Based on Roger's and IEC Method

机译：基于Roger's和IEC方法的基于模糊逻辑的电力变压器早期故障检测

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摘要

Power transformer is an essential part in any power plant, so continuous check of its reliability should be kept up. Dissolved Gas Analysis (DGA) is one of the most important techniques for detecting incipient faults of transformer that immersed in insulation oil. Some widely used conventional techniques based on DGA such as Roger's and IEC methods were developed to diagnose faults of power transformers. These methods succeeded noticeably to detect transformer's faults. However, they fail to detect the fault type if the measured ratios of gases slightly deviated from the crisp boundaries of ranges assigned by these methods. An Artificial Intelligent technique based method called fuzzy logic approach, which is the field of study in this paper is used to overcome the above mentioned drawback by fuzzifying the boundaries of ranges defined by these techniques. This paper presents a comparison between the results of conventional Roger's, IEC methods and the proposed fuzzy logic.
机译：电力变压器在任何发电厂中都是必不可少的部分，因此应不断检查其可靠性。溶解气体分析（DGA）是检测浸入绝缘油中的变压器早期故障的最重要技术之一。开发了一些基于DGA的广泛使用的常规技术，例如Roger's和IEC方法，以诊断电力变压器的故障。这些方法显着成功地检测了变压器的故障。但是，如果测得的气体比例略微偏离了这些方法指定的范围的清晰边界，则它们将无法检测出故障类型。本文研究的基于人工智能技术的方法称为模糊逻辑方法，用于通过模糊这些技术定义的范围的边界来克服上述缺点。本文介绍了常规罗杰法，IEC方法和拟议模糊逻辑的结果之间的比较。

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