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Design of a fault diagnostic engine for power transformer using data mining

机译:基于数据挖掘的电力变压器故障诊断引擎设计

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摘要

The power transformer is one of the main components in a power transmission network. Major faults in these transformers can cause extensive damage which does not only interrupt electricity supply but also results in large revenue losses. Thus, these transformers are needed to be routinely maintained. Due to the large number of transformers of different makes and capacities, routine maintenance and diagnosis of such transformers are rather difficult as different transformers exhibit different characteristics and problems. Moreover, different climatic and operating conditions may not be able to draw correct conclusion to some problems. In Malaysia, the lack of local expertise makes dependency on foreign consultants imminent which are rather expensive. To help in overcoming such problems, a Software for Intelligent Diagnostics of Power Transformers known as ADAPT, using the technique of fuzzy logic is developed in this study. The technique allows the interpretation of the Dissolved Gas Analysis (DGA) to be performed routinely on the transformers. In order to ensure that all the transformers are diagnosed and maintained properly, a new intelligent diagnostic architecture known as Total Intelligent Diagnostic Solution (TIDS) has been developed to improve the diagnosis accuracy of the conventional DGA approaches. The TIDS structure has a main interpretation module which consists of Fuzzy TDCG and Fuzzy Key Gases and a supportive interpretation module which consists of Fuzzy Rogers Ratio and Fuzzy Nomograph. The TIDS structure is incorporated into the ADAPT software which allows for multiple diagnostic methods to reach an ultimate outcome especially when verified by four methods. This new architecture leads to the diagnostic of a wider range of transformer fault types and provides a more detail information about the transformer condition, thus help to reduce maintenance costs, prevent unnecessary force outages and avoid explosion danger.
机译:电力变压器是电力传输网络中的主要组件之一。这些变压器的重大故障可能会造成广泛的损害,这不仅会中断电力供应,还会导致大量的收入损失。因此,需要定期维护这些变压器。由于大量不同品牌和容量的变压器,这种变压器的日常维护和诊断相当困难,因为不同的变压器表现出不同的特性和问题。此外,不同的气候和操作条件可能无法得出某些问题的正确结论。在马来西亚,当地专家的缺乏使得对外国顾问的依赖迫在眉睫,这相当昂贵。为了帮助解决此类问题,本研究开发了一种使用模糊逻辑技术的电力变压器智能诊断软件ADAPT。该技术允许对变压器进行例行的溶解气体分析(DGA)解释。为了确保正确诊断和维护所有变压器,已开发出一种称为总智能诊断解决方案(TIDS)的新智能诊断体系结构,以提高传统DGA方法的诊断准确性。 TIDS结构具有一个主要的解释模块,该模块由Fuzzy TDCG和Fuzzy Key Gas组成;一个辅助的解释模块,由Fuzzy Rogers Ratio和Fuzzy Nomograph组成。 TIDS结构已集成到ADAPT软件中,该软件允许多种诊断方法达到最终结果,尤其是在通过四种方法进行验证时。这种新的体系结构可以诊断更广泛的变压器故障类型,并提供有关变压器状况的更多详细信息,从而有助于降低维护成本,防止不必要的用力中断并避免爆炸危险。

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