A Novel Optical Localization Method for Partial Discharge Source Using ANFIS Virtual Sensors and Simulation Fingerprint in GIL

作者：Yiming Zang, Yong Qian, Hui Wang, Antian Xu, Xiaoli Zhou, Gehao Sheng, Xiuchen Jiang · 发表于：IEEE Transactions on Instrumentation and Measurement · 年份：2021 · DOI：10.1109/tim.2021.3097856 · 被引用次数：40 · 研究领域：High voltage insulation and dielectric phenomena、Power Transformer Diagnostics and Insulation、Non-Destructive Testing Techniques

Partial discharge (PD) detection and localization is one of the most effective methods in gas-insulated transmission lines (GIL) insulation fault diagnosis, which is important to the early troubleshooting and safe operation. Compared with the widely used ultrahigh frequency (UHF) and acoustic PD localization methods, the PD localization method based on optical signals has good resistance to electromagnetic and acoustic interference. However, the current optical localization method comes with several shortcomings: narrow detection range, requiring field experiments to accumulate data, and installing a large number of sensors, which renders low feasibility. Therefore, this article proposes a PD localization method utilizing virtual sensors (VSs) and optical simulation fingerprint. Based on the idea of the digital twin, this method constructs a fingerprint database through optical PD simulation in an equal-sized GIL simulation model, which solves the difficulty of fingerprint collection in actual equipment. Meanwhile, this article predicts the detection value of the VS through the adaptive neuro-fuzzy inference system (ANFIS) to greatly reduce the installation of the actual sensor (AS). Finally, through the support vector machines (SVMs) algorithm, the detection fingerprint that includes the virtual and actual detection values matches with the fingerprint database. The location corresponding to the optimal matching result is recorded as the localization result. As experiments ha...