To investigate the inhomogeneous distribution of electric fields in insulating equipment and components, five nonlinear-conductance composite materials based on epoxy resin (EP) (nano-SiC/EP, nano-ZnO/EP, micro-ZnO/EP, nano-SiC/ZnO/EP, and nano-micro-SiC/ZnO/EP), were prepared using nano-SiC, nano-ZnO, and micro-ZnO particles as fillers. The mass fractions of the inorganic fillers were 1, 3, and 5 wt%, respectively. The direct current (DC) voltage characteristics of the composites showed that the electrical conductivities and nonlinear coefficients of the composites utilizing single-filler types increased with increasing inorganic filler content. Under the same conditions, the conductivity and nonlinear coefficient of SiC/EP were both larger than those of the nano-ZnO/EP and micro-ZnO/EP. However, the nonlinear coefficient of the composites was significantly affected by the simultaneous addition of the two inorganic fillers, micro-ZnO and nano-SiC. When the content ratio of micro-ZnO to nano-SiC was 2:3, the nonlinear coefficient of the composite reached a maximum value of 3.506, significantly higher than those of the other samples. Compared with the nano-SiC/EP, micro-ZnO/EP and nano-ZnO/EP composites with 5 wt% inorganic filler, the nonlinear coefficient of the two-filler composite was greater by a factor of 0.82, 2.48, and 5.01, respectively.
The synergistic effects of zinc oxide (ZnO) Micro/Nano particles simultaneously filled in low-density polyethylene (LDPE) on the space charge characteristics and electrical properties has been investigated by melt blending micro-scale and nanoscale ZnO additive particles into LDPE matrix to prepare Micro-ZnO, Nano-ZnO, and Micro-Nano ZnO/LDPE composites. The morphological structures of composite samples are characterized by Polarizing Light Microscopy (PLM), and the space charge accumulations and insulation performances are correlated in the analyses with Pulse Electronic Acoustic (PEA), DC breakdown field strength, and conductance tests. It is indicated that both the micro and nano ZnO fillers can introduce plenty of heterogeneous nuclei into the LDPE matrix so as to impede the LDPE spherocrystal growth and regularize the crystalline grains in neatly-arranged morphology. By filling microparticles together with nanoparticles of ZnO additives, the space charge accumulations are significantly inhibited under an applied DC voltage and the minimum initial residual charges with the slowest charge decaying rate have been achieved after an electrode short connection. While the micro-nano ZnO/LDPE composites acquire the lowest conductivity, the breakdown strengths of the ZnO/LDPE nanocomposite and micro-nano composite are, respectively, 13.7% and 3.4% higher than that of the neat LDPE material.
Low-density polyethylene (LDPE) is one of the most comprehensive products used as insulation materials in power equipment. How to improve its dielectric properties by doping inorganic particles in LDPE has always been the focus of many researchers. In this paper, silica (SiO2) particles and montmorillonite (MMT) particles were added to LDPE, the order of adding particles was changed, and different micro-nano composites was made. The crystallization characteristics of composites were analyzed, the curves of the conductance current with the change of field intensity were analyzed, and the space charge distribution of each material were investigated. The results of crystallization show that the crystalline properties and crystallinity of the composites are higher than the matrix LDPE, the addition of SiO2 particles increases the composites’ crystallinity significantly, and the intercellular spacing of micro-nano composites is the smallest among all materials. The curve of conductance current versus electric field intensity shows that the tightness of the crystal structure can effectively hinder the movement of the molecular chain, inhibit carrier migration, while shortening the free travel of electrons, thereby reducing the electric conduction current of the material. The experimental results of the space charge accumulation curve further show that the compact crystal structure of the material is beneficial to the dissipation of space charge in the dielectric.
Low-density polyethylene (LDPE) is an important thermoplastic material which can be made into films, containers, wires, cables, etc. It is highly valued in the fields of packaging, medicine, and health, as well as cables. The method of improving the dielectric property of materials by blending LDPE with inorganic particles as filler has been paid much attention by researchers. In this paper, low-density polyethylene is used as the matrix, and montmorillonite (MMT) particles and silica (SiO2) particles are selected as micro and nano fillers, respectively. In changing the order of adding two kinds of particles, a total of five composite materials were prepared. The crystallization behavior and crystallinity of five kinds of composites were observed, the εr and tanδ changes of each material were investigated with frequency and temperature, and the power frequency (50 Hz) AC breakdown performance of materials were measured. The differential scanning calorimetry (DSC) and X-ray diffraction (XRD) results show that the crystallinity of the composites is higher than that of LDPE. Experimental data of dielectric frequency spectra show that the dielectric constants of micro–nano composites and composites with added MMT particles are lower than LDPE, the dielectric loss of composites can be improved by adding MMT particles. The experimental data of dielectric temperature spectra show that the permittivity of SiO2-MMT/LDPE is still at a low level under the condition of 20~100 °C. In terms of breakdown field strength, the SiO2/LDPE composite material increased by about 17% compared with the matrix LDPE, and the breakdown field strength of the materials SiO2-MMT/LDPE and MMT-SiO2/LDPE increased by about 6.8% and 4.6%, respectively.
Montmorillonite (MMT)/low-density polyethylene (LDPE) nanocomposites have excellent partial discharge resistance and electrical tree resistance compared with pure LDPE. However, the MMT/LDPE nanocomposites have low breakdown strength due to the poor compatibility between nano-MMT and LDPE. In order to improve the breakdown strength of the MMT/LDPE composites without changing the LDPE matrix, an MMT/SiO 2 /LDPE multielement composite was prepared by melt blending, and its breakdown strength and electrical tree resistance properties were investigated. The results show that the MMT/SiO 2 /LDPE multielement composite has excellent breakdown strength and electrical tree resistance properties compared with the MMT/LDPE composite. The reasons for the excellent insulation properties of the MMT/SiO 2 /LDPE multielement composites were analyzed by exploring the effects of MMT and SiO 2 on the microstructure and trap characteristics of LDPE.
In order to analyze the partial discharge (PD) characteristics of a liquid/solid composite medium in an oil-filled submarine cable terminal; we have designed five discharge models including needle-plate, plate-to-plate air gap, surface, slide-flash and suspension potential. At the same time, the ultrasonic signals of PD have been extracted through the typical fault model research platform of oil-filled submarine cable equipment. First, we use SureShrink threshold wavelet denoising to suppress the ultrasonic signal noise. Secondly, through the multi-scale analysis of the signal, the energy distribution maps of five different types of PD are obtained; the analysis found that needle-plate discharge, suspension discharge, and slide-flash discharge have better resolution; and plate-to-plate air gap discharge and creeping discharge have similar characteristics and are not easy to distinguish. Finally, we designed six characteristic parameters of the ultrasound signal, and screened three feature quantities by a back propagation (BP) neural network to distinguish between plate-to-plate air gap discharge and surface discharge. In summary, the method of combining multi-scale analysis and neural networks is used to distinguish the five discharge types by extracting the characteristic values of the characteristic signals.
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