Smart sensing for spatially-coupled PD detection, including ultra-wide-band antenna in the VHF/UHF band (50~800MHz) and Analog RF front end with high sensitivity (≤-70dBm) and wide dynamic signal receiving range (≥80dB)
Edge intelligence for real-time RF pulse detection and instant RF pulse identification
Machine learning for pulse signal clustering, feature extraction and recognition
Interreference and noise reduction
Received Signal Strength Indicator (RSSI) and Differential Time of Arrival (DTOA) combined PD source localisation
Mauro Palo, Benjamin Schubert, Jianguo Wei, and Weilin Liu, “Clustering-based Discrimination of Multiple Partial Discharge Sources: Examples from a Case Study”, 13th IEEE PES PowerTech Conference, Milano, Italy, June 2019.
Benjamin Schubert, Jianguo Wei, Yong Zhang, Braulio Gomez Saavedra, Mauro Palo, and Weilin Liu, “A Distributed Data Acquisition System for Long-term Recording of Occasional Signals in the UHF Range”, 2018 International Conference on Power System Technology (POWERCON), Guangzhou, China, Nov. 2018.
Benjamin Schubert, Mauro Palo, and Thomas Schlechter, “Review of UHF-Based Signal Processing Approaches for Partial Discharge Detection”, Computer Aided Systems Theory – EUROCAST 2017. Lecture Notes in Computer Science, vol 10672. Springer, Cham. Jan. 2018, pp. 219-226.
Thomas Schlechter, Benjamin Schubert, and Mario Ludwig, “Review of UHF based Signal Processing Approaches for Partial Discharge Detection”, EUROCAST 2017, Computer Aided Systems Theory, Gran Canaria, Spain, Feb. 2017.