Knowledge-based diagnosis of partial discharges in power transformers
Knowledge-based diagnosis of partial discharges in power transformers
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DOI：
10.1109/t-dei.2008.4446759
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发表时间：
2008-02-01
影响因子：
3.1
通讯作者：
Gulski, E.
中科院分区：
文献类型：
--
作者：
Strachan, S. M.;Rudd, S.;Gulski, E.
在诊断专业知识和知识有限且不断发展的领域中，从原始状态监测数据中提取有意义的诊断信息是一个重大的研究挑战。高压发电厂局部放电的专家诊断和定位就是这样一个领域。本文介绍了一个基于知识的决策支持系统的功能，能够为工程师提供一个全面的诊断负责局部放电活动检测充油电力变压器的缺陷。从局部放电（PD）传感器捕获的工厂数据可以被处理以生成相位分辨局部放电（PRPD）模式。本文提出了一种方法，抽象的显着特征表征所观察到的PRPD模式。描述这些图案的视觉解释的捕获的知识可以应用于缺陷诊断和定位。基于知识的PRPD模式解释系统可以支持在线工厂状态评估和缺陷诊断，提出了一个全面的诊断检测到的PD活动和分类的缺陷源。本文还讨论了系统如何证明其诊断的PD活动，以提供专家更大的信心，在结果中，一个功能通常没有在“黑箱”模式识别技术。该系统所表现出的增量方法反映了PD专家对PRPD模式的视觉解释。本文介绍了如何实现这一功能系统。设计已经从PD专家采取的方法发展到PRPD模式的视觉解释。
The abstraction of meaningful diagnostic information from raw condition monitoring data in domains where diagnostic expertise and knowledge is limited and constantly evolving presents a significant research challenge. Expert diagnosis and location of partial discharges in High Voltage electrical plant is one such domain. This paper describes the functionality of a knowledge-based decision support system capable of providing engineers with a comprehensive diagnosis of the defects responsible for partial discharge activity detected in oil-filled power transformers. Plant data captured from partial discharge (PD) sensors can be processed to generate phase-resolved partial discharge (PRPD) patterns. This paper proposes a means of abstracting the salient features characterizing the observed PRPD patterns. Captured knowledge describing the visual interpretation of these patterns can be applied for defect diagnosis and location. The knowledge-based PRPD pattern interpretation system can support on-line plant condition assessment and defect diagnosis by presenting a comprehensive diagnosis of PD activity detected and classification of the defect source. The paper also discusses how the system justifies its diagnosis of the PD activity to offer the expert greater confidence in the result, a feature generally absent in 'black-box' pattern recognition techniques. The incremental approach exhibited by the system reflects that of a PD expert's visual interpretation of the PRPD pattern. The paper describes how this functional system. design has evolved from the approach taken by PD experts to the visual interpretation of PRPD patterns.