Accurate partial discharge (PD) localization is essential for the condition assessment and maintenance of power cables. Frequency-domain reflectometry (FDR) has shown considerable potential for double-end PD localization. Traditional FDR typically selects valid frequency bands by setting thresholds based on the spectral amplitude at the head and tail ends, making it difficult to accurately evaluate the contribution of phase information from different frequency components to PD localization. When certain frequency bands are affected by noise interference, the resulting phase changes may fail to accurately reflect the propagation path difference between the head and tail signals, thereby disrupting the coherent superposition during the spatial inversion process. To address this issue, a frequency-domain weighted FDR localization method based on the local linear characteristics of the unwrapped transfer-function phase is proposed. First, valid PD pulses are extracted using double-end propagation characteristics; then, frequency-domain reliability weights are constructed based on the local slope and the linear fitting residual of the unwrapped transfer-function phase to adaptively weight the contributions of different frequency components in the FDR spatial inversion. Simulation and experimental results demonstrate that when local phase anomalies exist within the effective frequency band, the proposed method effectively suppresses spurious peaks and sidelobes caused by unreliable frequency components, thereby improving the localization performance of FDR-based PD localization under complex interference conditions.
An algorithm for the automatic identification of many defect typologies supporting Partial Discharges (PD) in different insulation systems of AC rotating machines is presented in this paper. It relies on a subset of robust parameters that describe features of PD-pulse phase and height distributions, with identification rules organized into a tree structure. Navigation through the tree is performed using fuzzy logic to account for fuzziness in the identification procedure. Fuzzy predicates thus assign Phase-Resolved PD patterns to the defect typologies. The membership values are also provided as output to consider even more than one option. Some application examples obtained from testing complete coils and stator bars are discussed.
Ice accretion on overhead transmission lines threatens mechanical reliability and electrical performance. Superhydrophobic surfaces offer a passive anti-icing strategy, but achieving uniform surface modification on multilayer helically stranded aluminum conductors and maintaining durability under harsh environmental conditions remain challenging. In this study, nanoporous superhydrophobic surfaces are fabricated on JL/LB20A-240/30 aluminum-clad steel-reinforced stranded conductors through anodization followed by low-surface-energy modification. The modified conductor exhibits a static water contact angle of 160.71° and an ice adhesion strength of 0.88 kPa. After 3 h of exposure to low-temperature and high-humidity conditions, the contact angle remains at 151°, while the ice adhesion strength increases slightly to 0.91 kPa. Under cyclic environmental exposure combined with repeated ice detachment, the ice adhesion strength remains below 1 kPa for up to 39 h but increases to 10.12 kPa at 60 h and 25.46 kPa at 66 h. In laboratory-simulated glaze-icing tests, ice accretion is reduced by 53.2% and 27.9% relative to the bare and coated conductors, respectively. Corresponding reductions of 43.1% and 20.7% are observed under natural icing conditions. High-current temperature-rise and corona discharge tests reveal a lower steady-state temperature and a higher corona inception voltage for the modified conductor than for the bare conductor. These findings demonstrate enhanced anti-icing performance while maintaining favorable electrical characteristics under the investigated conditions.
Reported bubble inception temperatures in transformer winding insulation often differ considerably, even under seemingly similar test conditions. This paper investigates possible causes of these discrepancies and presents an experimental methodology to study the influence of selected parameters on bubble inception temperature. A novel evaluation method based on the paper moisture content at bubble inception is introduced to account for moisture migration during heating. Experiments on non-thermally upgraded Kraft paper–mineral oil insulation systems show that neither the temperature rise rate nor the number of paper layers significantly affects the bubble inception temperature, whereas moisture migration should not be neglected. An updated bubble inception model and a probability-based framework are also proposed to assess the likelihood of bubble inception as a function of temperature and paper moisture content.
High-sensitivity, real-time and on-line detection of SF6 decomposition products is a key means to determine the type and severity of faults in gas-insulation equipment. This review analyzes the decomposition mechanism and main SF6 decomposition products. The practicability of decomposition products detection in fault diagnosis is verified by practical cases. As a novel photoacoustic spectroscopy gas detection method, fiber optic photoacoustic sensing (FOPAS) technology has the advantages of strong immunity to electromagnetic interference, high sensitivity, long-distance signal transmission, no background interference and fast response. This technology can reach the detection limit of ppm or even ppb level, and has great application potential in identifying trace characteristic gases produced by SF6 decomposition at the initial stage of equipment failure. The FOPAS technology utilizes optical cantilevers based on F-P interference to achieve high-sensitivity detection of weak sound wave, with both excitation light and detection light transmitted by optical fibers. Three demodulation methods of Fabry-Pérot (F-P) cavity length are compared. The white light interferometry (WLI) demodulation method in spectral domain is emphatically analyzed. The specific applications of FOPAS technology in the detection of SF6 decomposition products are reviewed. In addition, FOPAS technology can monitor the concentration of decomposition products and internal environmental parameters of gas-insulation equipment at the same time without additional electrical sensors. Finally, the challenges and future development direction of FOPAS technology in this field are discussed.
