Abstract:
Partial discharge (PD) detection and localization is one of the most effective methods in gas-insulated transmission lines (GIL) insulation fault diagnosis, which is impo...Show MoreMetadata
Abstract:
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 have shown, the average localization error of the proposed method is 19.69 mm, which is 54.8% lower than the one without VSs under the same conditions. The results reveal that this method compensates for the loss of localization accuracy caused by the reduction of ASs, which embodies value in practice.
Published in: IEEE Transactions on Instrumentation and Measurement ( Volume: 70)
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- IEEE Keywords
- Index Terms
- Local Method ,
- Adaptive Neuro-fuzzy Inference System ,
- Partial Discharge ,
- Virtual Sensors ,
- Partial Discharge Source ,
- Gas-insulated Transmission Lines ,
- Acoustic ,
- Simulation Model ,
- Support Vector Machine ,
- Localization Accuracy ,
- Safe Operation ,
- Optical Signal ,
- Localization Error ,
- Active Sensors ,
- Support Vector Machine Algorithm ,
- Inference System ,
- Digital Twin ,
- Ultra-high Frequency ,
- Optical Simulation ,
- Fingerprint Database ,
- Fingerprint Features ,
- Optical Detection ,
- Method In This Article ,
- Risk Of Failure ,
- Fuzzy System ,
- Membership Function ,
- Operation And Maintenance ,
- Light Irradiation ,
- Wireless Sensor Networks ,
- Optical Sensors
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Local Method ,
- Adaptive Neuro-fuzzy Inference System ,
- Partial Discharge ,
- Virtual Sensors ,
- Partial Discharge Source ,
- Gas-insulated Transmission Lines ,
- Acoustic ,
- Simulation Model ,
- Support Vector Machine ,
- Localization Accuracy ,
- Safe Operation ,
- Optical Signal ,
- Localization Error ,
- Active Sensors ,
- Support Vector Machine Algorithm ,
- Inference System ,
- Digital Twin ,
- Ultra-high Frequency ,
- Optical Simulation ,
- Fingerprint Database ,
- Fingerprint Features ,
- Optical Detection ,
- Method In This Article ,
- Risk Of Failure ,
- Fuzzy System ,
- Membership Function ,
- Operation And Maintenance ,
- Light Irradiation ,
- Wireless Sensor Networks ,
- Optical Sensors
- Author Keywords