UHF partial discharge localisation method in substation based on dimension-reduced RSSI fingerprint

• Published in: IET generation, transmission & distribution Vol. 12; no. 2; pp. 398 - 405
• Main Authors: Li, Zhen, Luo, Lingen, Sheng, Gehao, Liu, Yadong, Jiang, Xiuchen
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 30.01.2018
• Subjects: antiinterference; clustering algorithm; dimension‐reduced RSSI fingerprint map; interference suppression; partial discharge detection; partial discharge measurement; pattern clustering; PD detection; probabilistic approach; probability; received signal strength indicator; Research Article; scene analysis method; stability; substation; substations; time‐difference technique; UHF detectors; UHF measurement; UHF partial discharge localisation method; UHF PD localisation method; ultrahigh frequency technique; wireless sensor networks; wireless UHF sensor; PD detection; interference suppression; wireless sensor networks; clustering algorithm; probability; scene analysis method; antiinterference; received signal strength indicator; ultrahigh frequency technique; substations; probabilistic approach; UHF PD localisation method; wireless UHF sensor; UHF partial discharge localisation method; dimension-reduced RSSI fingerprint map; partial discharge measurement; pattern clustering; UHF detectors; substation; UHF measurement; time-difference technique; stability; partial discharge detection
• ISSN: 1751-8687; 1751-8695
• DOI: 10.1049/iet-gtd.2017.0601

Ultra-high frequency (UHF) technique is chosen for partial discharge (PD) detection due to its excellent anti-interference and stability. The existing UHF PD localisation methods are mainly based on time-difference technique, that suffer high hardware cost due to the high sampling rate requirement. The wireless UHF sensors together with the scene analysis methods, i.e. received signal strength indicator (RSSI) fingerprint, provide us a low hardware cost and high environmental adaptability solution for PD localisation in substation. The proposed PD localisation method here is divided into two stages. In the offline stage, the RSSI fingerprint map is established by site survey. In the online stage, the position of PD source is estimated by a probabilistic approach. To reduce the influence of noise, the RSSI fingerprints are transformed to a low-dimensional subspace, while the most of redundant noise is discarded. Furthermore, the PD heterogeneity and interference in the offline stage are also discussed and solved by normalisation and clustering algorithm, respectively. A filed test is performed and the results indicate that the mean localisation error is 1.87 m and 82.6% localisation errors are <3 m. The workload in the offline stage is also reduced ∼50%.