The 500 kV oil-filled ac submarine cables in the networking project of China’s southern coast are large capacity, ultrahigh-voltage cross-sea submarine power cables, which are 31 km long and bundled with submarine optical cables. Temperature monitoring on submarine cables is of great significance in controlling the ampacity and ensuring operational reliability. Referring to the submarine cables’ structural characteristics and setting conditions, a temperature monitoring system is established based on the Brillouin optical time-domain analysis (BOTDA) distributed optical fiber sensing technology. The thermal circuit model IEC60287 is modified and used to calculate internal temperature distribution. Moreover, an onshore simulation experimental platform is established on the same cables as the networking project with a special sealing and joint structures designed for filling oil and adding load, proving the accuracy of the temperature monitoring system and the calculation method. Finally, one example of the on-site operation and maintenances data is presented to show the actual working condition of the temperature monitoring system.

Fault detection based on external leakage flux can address various faults, such as short-circuit faults in stators and rotors. External leakage flux sensing technology, as a noninvasive method, has been attracting increasing attention and research. However, for a high-power doubly fed induction generator (DFIG), the external leakage flux signals of the generator are easily overwhelmed by a strong noise background, and the fault diagnosis and recognition of stator interturn short circuit (S-ITSC) and rotor ITSC (R-ITSC) are complicated, which limit the practical engineering application of leakage flux sensing technology. Aiming at addressing ITSC faults in DFIGs, this article proposes a method for fault feature extraction and recognition of stator and rotor short circuits based on variational mode decomposition (VMD) and the refined composite multiscale dispersion entropy (RCMDE) analytical method for the external flux leakage of the generator. The optimized parameters of VMD are selected automatically by the genetic algorithm (GA), and VMD is adopted to adaptively decompose the external leakage flux signals into a series of intrinsic mode function (IMF) components. The evaluation criterion based on the correlation number in the frequency domain combined with the autocorrelation function is used to select the best IMF components with clear features. Two different components are chosen to reconstruct the flux leakage signal. The characteristic frequency of the reconstructed signal is analyzed by the Hilbert–Huang transform (HHT) and the total harmonic effective value of the characteristic component. To effectively identify and diagnose the generator S-ITSC and R-ITSC faults, RCMDE is used for the flux leakage reconstructed signal. The experimental results under different stator and rotor short-circuit levels show that this diagnosis method can effectively extract the weak feature information from the external flux leakage signals and perform fault feature extraction and recognition for stator and rotor short circuits.

Inter-turn short circuit fault (ITSCF) can be a great threat for the safety and effectiveness of the generator. In this paper, a simulation model with the experimental platform is established to diagnose the ITSCF in stator windings. A simulation model based on the Finite Element Method (FEM) is designed in ANSYS. Stator current is used for calculating the Root-Mean-Square (RMS) value, phase difference, symmetrical components, Park’s vector trajectory’s and Total Harmonic Distortion (THD). It was found that when ITSCF happened, three phase currents in stator is no longer symmetrical. The ratio of negative to positive sequence of current raises from 0.40 to 14.18 in simulation and 0.52 to 19.89 in the experiment from normal condition to 7 turns shorted. The same trend was seen in Park’s vector trajectory analysis where the eccentricity raises from 0.03 to 0.65 in simulation and 0.14 to 0.75 in the experiment. Phase difference of the three phases is at 120° degree deviation as the ITSCF occurs in stator winding. THD also increased with the increase in the fault level. The results show a good consistency of simulation with experimental results. It was found that the analysis performed in this research are major indications for serious fault in DFIG.

This paper reports on ageing behaviors of polypropylene (PP) and its composites that are used as nuclear cable insulation under gamma-ray irradiation. Isotactic polypropylene (iPP), block polypropylene (bPP), and iPP/elastomers blends are employed to prepare the test samples. The samples are irradiated by a Cobalt-60 gamma source with a maximum dose of 1000 kGy, and then trap distribution and AC breakdown strength are measured. Structural changes in the samples are estimated by high-temperature gel permeation chromatograph (GPC), differential scanning calorimetry (DSC), X-ray diffraction (XRD), scanning electron microscope (SEM), and Fourier transform infrared spectroscopy (FTIR) measurements. The results indicate that, as the total dose increases, the energy of trap centers becomes shallower and the AC breakdown strength tends to decrease. The molecular weight, crystallinity and melting point of samples decrease whereas the oxidation degree increases. It is suggested that the ageing of samples is highly associated with the degradation of material structure caused by gamma-ray irradiation, and with the addition of elastomers, the irradiation resistance of PP is improved.