Emerging trends for determining incipient faults by dissolved gas analysis

Kingshuk Chatterjee, V. K. Jadoun, R. Jarial
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引用次数: 5

Abstract

Dissolved Gas Analysis has been one of the most extensively used tools for health monitoring of power transformers. Since its introduction, researchers have been working on to increase its ability to predict the incipient faults more accurately. DGA methods have been shifting from off-line to online monitoring, and interpretation techniques from key gas and ratio methods to graphical methods and more advanced methods. But presently, the DGA data is used to interpret more detailed information about the faults like severity of the fault or involvement of solid insulation. In this paper, an effort has been made to cover some of such emerging techniques in the field of DGA along with issues like stray gassing problem, scheduling DGA inspection etc. With the development of alternate insulating liquids, DGA of such liquids is gaining importance and have been proactively covered in this paper. Further, the extensive implementation of AI techniques for more flexible interpretation of DGA data is also evaluated through this paper.
用溶解气体分析确定早期断层的新趋势
溶解气体分析已成为电力变压器健康监测中应用最广泛的工具之一。自从它被引入以来,研究人员一直致力于提高它更准确地预测早期断层的能力。DGA方法已经从离线监测转向在线监测,解释技术从关键气体和比率方法转向图形方法和更先进的方法。但目前,DGA数据用于解释故障的更详细信息,如故障的严重程度或涉及固体绝缘。本文主要介绍了DGA领域的一些新兴技术,以及杂散放气问题、DGA检测调度等问题。随着交替绝缘液体的发展,交替绝缘液体的DGA越来越受到重视,本文已对其进行了积极的研究。此外,本文还对人工智能技术的广泛实施进行了评估,以更灵活地解释DGA数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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