Particle Swarm Optimization-based BP Neural Network for UHV DC Insulator Pollution Forecasting

In order to realize the forecasting of the UHV DC insulator's pollution conditions, we introduced a PSOBP algorithm. A BP neural network (BPNN) with leakage current, temperature, relative humidity and dew point as input neurons, and ESDD as output neuron was built to forecast the ESDD. The PSO was used to optimize the the BPNN, which had great improved the convergence rate of the BP neural network. The dew point as a brand new input unit has improved the iteration speed of the PSOBP algorithm in this study. It was the first time that the PSOBP algorithm was applied to the UHV DC insulator pollution forecasting. The experiment results showed that the method had great advantages in accuracy and speed of convergence. The research showed that this algorithm was suitable for the UHV DC insulator pollution forecasting

Molecular Dynamics Simulation and Experimental Studies on the Thermomechanical Properties of Epoxy Resin with Different Anhydride Curing Agents

An investigation of the relationship between the microstructure parameters and thermomechanical properties of epoxy resin can provide a scientific basis for the optimization of epoxy systems. In this paper, the thermomechanical properties of diglycidyl ether of bisphenol A (DGEBA)/methyl tetrahydrophthalic anhydride (MTHPA) and DGEBA/nadic anhydride (NA) were calculated and tested by the method of molecular dynamics (MD) simulation combined with experimental verification. The effects of anhydride curing agents on the thermomechanical properties of epoxy resin were investigated. The results of the simulation and experiment showed that the thermomechanical parameters (glass transition temperature (Tg) and Young’s modulus) of the DGEBA/NA system were higher than those of the DGEBA/MTHPA system. The simulation results had a good agreement with the experimental data, which verified the accuracy of the crosslinking model of epoxy resin cured with anhydride curing agents. The microstructure parameters of the anhydride-epoxy system were analyzed by MD simulation, including bond-length distribution, synergy rotational energy barrier, cohesive energy density (CED) and fraction free volume (FFV). The results indicated that the bond-length distribution of the MTHPA and NA was the same except for C–C bonds. Compared with the DGEBA/MTHPA system, the DGEBA/NA system had a higher synergy rotational energy barrier and CED, and lower FFV. It can be seen that the slight change of curing agent structure has a significant effect on the synergy rotational energy barrier, CED and FFV, thus affecting the Tg and modulus of the system

Research on Partial Discharge Source Localization Based on an Ultrasonic Array and a Step-by-Step Over-Complete Dictionary

Partial discharge (PD) in electrical equipment is one of the major causes of electrical insulation failures. Fast and accurate positioning of PD sources allows timely elimination of insulation faults. In order to improve the accuracy of PD detection, this paper mainly studies the direction of arrival (DOA) estimation of PD ultrasonic signals based on a step-by-step over-complete dictionary. The simulation results show that the step by step dictionary can improve the operation speed and save signal processing time. Firstly, a step-by-step over-complete dictionary covering all the angles of space is established according to the expression of the steering vector for a matching pursuit direction finding algorithm, which can save computation time. Then, the step-by-step complete dictionary is set up according to the direction vector, and the atomic precision is respectively set to 10°, 1° and 0.1°. The matching pursuit algorithm is used to carry out the sparse representation of the received data X and select the optimal atom from the step-by-step complete dictionary, and the angle information contained in atoms is DOA of the PD sources. According to the direction finding results, combined with the installation location of the ultrasonic array sensor, the spatial position of a partial discharge source can be obtained using the three platform array location method. Finally, a square ultrasonic array sensor is developed, and an experimental platform for the ultrasonic array detection of partial discharges is set up and used to carry out an experimental study. The results show that the DOA estimation method based on a step-by-step over-complete dictionary can improve the direction finding precision, thereby increasing the subsequent positioning accuracy, and the spatial position estimation error of the PD source obtained under laboratory conditions is about 5 cm, making this a feasible method

Application Research of the Sparse Representation of Eigenvector on the PD Positioning in the Transformer Oil

The partial discharge (PD) detection of electrical equipment is important for the safe operation of power system. The ultrasonic signal generated by the PD in the oil is a broadband signal. However, most methods of the array signal processing are used for the narrowband signal at present, and the effect of some methods for processing wideband signals is not satisfactory. Therefore, it is necessary to find new broadband signal processing methods to improve detection ability of the PD source. In this paper, the direction of arrival (DOA) estimation method based on sparse representation of eigenvector is proposed, and this method can further reduce the noise interference. Moreover, the simulation results show that this direction finding method is feasible for broadband signal and thus improve the following positioning accuracy of the three-array localization method. And experimental results verify that the direction finding method based on sparse representation of eigenvector is feasible for the ultrasonic array, which can achieve accurate estimation of direction of arrival and improve the following positioning accuracy. This can provide important guidance information for the equipment maintenance in the practical application

Enhanced thermal conductance and electrical insulation of AlN/PMIA composite paper via nano splitting of matrix and size grading of fillers

Poly-(meta-phenylene isophthal-amide) (PMIA) is regarded as an ideal insulating medium for electronic devices owing to its excellent chemical stability and breakdown strength. However, the poor thermal conductivity limited the application under complex electrical-thermal environment. In this work, the size-graded AlN/PMIA composite papers were fabricated, with a multi-scale structure of matrix and fillers, and maintain qualified stability, mechanical strength and electrical insulation properties. With doping 40 wt% of 10 μm AlN and 10 wt% of 200 nm AlN, the optimum paper with in-plane (λ∥) and out-of-plane (λ⊥) of optimal paper reached thermal conductivity of 17.3 W/(mK) and 1.96 W/(mK) is obtained, and the breakdown strength increased to 69 kV/mm. The improvement mechanism brought by size-graded fillers was further revealed by the co-simulation of finite element method and loop nesting algorithm.</p

Micro-Structure and Thermomechanical Properties of Crosslinked Epoxy Composite Modified by Nano-SiO2: A Molecular Dynamics Simulation

Establishing the relationship among the composition, structure and property of the associated materials at the molecular level is of great significance to the rational design of high-performance electrical insulating Epoxy Resin (EP) and its composites. In this paper, the molecular models of pure Diglycidyl Ether of Bisphenol A resin/Methyltetrahydrophthalic Anhydride (DGEBA/MTHPA) and their nanocomposites containing nano-SiO2 with different particle sizes were constructed. The effects of nano-SiO2 dopants and the crosslinked structure on the micro-structure and thermomechanical properties were investigated using molecular dynamics simulations. The results show that the increase of crosslinking density enhances the thermal and mechanical properties of pure EP and EP nanocomposites. In addition, doping nano-SiO2 particles into EP can effectively improve the properties, as well, and the effectiveness is closely related to the particle size of nano-SiO2. Moreover, the results indicate that the glass transition temperature (Tg) value increases with the decreasing particle size. Compared with pure EP, the Tg value of the 6.5 &Aring; composite model increases by 6.68%. On the contrary, the variation of the Coefficient of Thermal Expansion (CTE) in the glassy state demonstrates the opposite trend compared with Tg. The CTE of the 10 &Aring; composite model is the lowest, which is 7.70% less than that of pure EP. The mechanical properties first increase and then decrease with the decreasing particle size. Both the Young&rsquo;s modulus and shear modulus reach the maximum value at 7.6 &Aring;, with noticeable increases by 12.60% and 8.72%, respectively compared to the pure EP. In addition, the thermal and mechanical properties are closely related to the Fraction of Free Volume (FFV) and Mean Squared Displacement (MSD). The crosslinking process and the nano-SiO2 doping reduce the FFV and MSD value in the model, resulting in better thermal and mechanical properties

Structure, microparameters and properties of crosslinked DGEBA/MTHPA: A molecular dynamics simulation

Investigating the relationship between microstructure and macroscopic properties of epoxy resin (EP) materials for high-voltage insulation at the molecular level can provide theoretical guidance for the synthetic design of EP. Here, using diglycidyl ether (DGEBA) as the resin matrix and methyl tetrahydrophthalic anhydride (MTHPA) as the curing agent, a set of crosslinked EP molecular models at different curing stages were constructed based on the proposed crosslinking method. We studied the influences of crosslinking density on micro-parameters and macro-properties employing molecular dynamics (MD) simulations. The results indicate that crosslinking of DGEBA/MTHPA is a contraction and exothermic process. The structural parameters and macroscopic properties are closely related to the degree of crosslinking. With the increase of crosslinking density, the mean square displacement (MSD) of the system decreases, and the segment motion in the models is weakened gradually, while, the fractional free volume (FFV) first decreases and then increases. In addition, the thermal and mechanical properties of DGEBA/MTHPA have a significant dependence on the crosslinking density. Increasing crosslinking density can improve the glass transition temperature (Tg), reduce the coefficient of thermal expansion (CTE), and enhances the static mechanical properties of DGEBA/MTHPA system. Furthermore, the relationship between microparameters and properties has been fully investigated. Free volume is an important factor that causes thermal expansion of DGEBA/MTHPA. Moreover, there is a negative correlation between MSD and mechanical moduli. By elevating temperature, the decline in mechanical moduli may be due to the exacerbated thermal motion of the molecules and the increasing MSD values