A spatiotemporal evolution model of a short-circuit arc to a secondary arc based on the improved charge simulation method

The initial shape of the secondary arc considerably influences its subsequent shape.To establish the model for the arcing time of the secondary arc and modify the single-phase reclosing sequence,theoretical and experimental analysis of the evolution process of the short-circuit arc to the secondary arc is critical.In this study,an improved charge simulation method was used to develop the internal-space electric-field model of the short-circuit arc.The intensity of the electric field was used as an independent variable to describe the initial shape of the secondary arc.A secondary arc evolution model was developed based on this model.Moreover,the accuracy of the model was evaluated by comparison with physical experimental results.When the secondary arc current increased,the arcing time and dispersion increased.There is an overall trend of increasing arc length with increasing arcing time.Nevertheless,there is a reduction in arc length during arc ignition due to short circuits between the arc columns.Furthermore,the arcing time decreased in the range of 0°-90°as the angle between the wind direction and the x-axis increased.This work investigated the method by which short-circuit arcs evolve into secondary arcs.The results can be used to develop the secondary arc evolution model and to provide both a technical and theoretical basis for secondary arc suppression.

Patterning single-layer materials by electrical breakdown using atomic force microscopy

The development of nanoelectronics and nanotechnologies has been boosted significantly by the emergence of 2D materials because of their atomic thickness and peculiar properties,and developing a universal,precise patterning technology for single-layer 2D materials is critical for assembling nanodevices.Demonstrated here is a nanomachining technique using electrical breakdown by an AFM tip to fabricate nanopores,nanostrips,and other nanostructures on demand.This can be achieved by voltage scanning or applying a constant voltage while moving the tip.By measuring the electrical current,the formation process on single-layer materials was shown quantitatively.The present results provide evidence of successful pattern fabrication on single-layer MoS2,boron nitride,and graphene,although further confirmation is still needed.The proposed method holds promise as a general nanomachining technology for the future.

Estimating the yield stress of soft materials via laser-induced breakdown spectroscopy

Taking three typical soft samples prepared respectively by loose packings of 77-,95-,and 109-μm copper grains as examples,we perform an experiment to investigate the energy-dependent laser-induced breakdown spectroscopy(LIBS)of soft materials.We discovered a reversal phenomenon in the trend of energy dependence of plasma emission intensity:increasing initially and then decreasing separated by a well-defined critical energy.The trend reversal is attributed to the laser-induced recoil pressure at the critical energy just matching the sample's yield strength.As a result,a one-to-one correspondence can be well established between the samples'yield stress and the critical energy that is easily obtainable from LIBS measurements.This allows us to propose an innovative method for estimating the yield stress of soft materials via LIBS with attractive advantages including in-situ remote detection,real-time data collection,and minimal destructive to sample.

Optimization of short-circuit transition parameters of Q235B steel GMAW based on orthogonal gray relational analysis

In gas metal arc welding(GMAW)process,the short-circuit transition was the most typical transition observed in molten metal droplets.This paper used orthogonal tests to explore the coupling effect law of welding process parameters on the quality of weld forming under short-circuit transition,the design of 3 factors and 3 levels of a total of 9 groups of orthogonal tests,welding current,welding voltage,welding speed as input parameters:effective area ratio,humps,actual linear power density,aspect ratio,Vickers hardness as output paramet-ers(response targets).Using range analysis and trend charts,we can visually depict the relationship between input parameters and a single output parameter,ultimately determining the optimal process parameters that impact the single output index.Then combined with gray the-ory to transform the three response targets into a single gray relational grade(GRG)for analysis,the optimal combination of the weld mor-phology parameters as follows:welding current 100 A,welding voltage 25 V,welding speed 30 cm/min.Finally,validation experiments were conducted,and the results showed that the error between the gray relational grade and the predicted value was 2.74%.It was observed that the effective area ratio of the response target significantly improved,validating the reliability of the orthogonal gray relational method.

Partitioning Calculation Method of Short-Circuit Current for High Proportion DG Access to Distribution Network

Aiming at the problemthat the traditional short-circuit current calculationmethod is not applicable to Distributed Generation(DG)accessing the distribution network,the paper proposes a short-circuit current partitioning calculation method considering the degree of voltage drop at the grid-connected point of DG.Firstly,the output characteristics of DG in the process of low voltage ride through are analyzed,and the equivalent output model of DG in the fault state is obtained.Secondly,by studying the network voltage distribution law after fault in distribution networks under different DG penetration rates,the degree of voltage drop at the grid-connected point of DG is used as a partition index to partition the distribution network.Then,iterative computation is performed within each partition,and data are transferred between partitions through split nodes to realize the fast partition calculation of short-circuit current for high proportion DG access to distribution network,which solves the problems of long iteration time and large calculation error of traditional short-circuit current.Finally,a 62-node real distribution network model containing a high proportion of DG access is constructed onMATLAB/Simulink,and the simulation verifies the effectiveness of the short-circuit current partitioning calculation method proposed in the paper,and its calculation speed is improved by 48.35%compared with the global iteration method.

Estimating the grain size of microgranular material using laser-induced breakdown spectroscopy combined with machine learning algorithms

Recent work has validated a new method for estimating the grain size of microgranular materials in the range of tens to hundreds of micrometers using laser-induced breakdown spectroscopy(LIBS).In this situation,a piecewise univariate model must be constructed to estimate grain size due to the complex dependence of the plasma formation environment on grain size.In the present work,we tentatively construct a unified calibration model suitable for LIBS-based estimation of those grain sizes.Specifically,two unified multivariate calibration models are constructed based on back-propagation neural network(BPNN)algorithms using feature selection strategies with and without considering prior information.By detailed analysis of the performances of the two multivariate models,it was found that a unified calibration model can be successfully constructed based on BPNN algorithms for estimating the grain size in the range of tens to hundreds of micrometers.It was also found that the model constructed with a priorguided feature selection strategy had better prediction performance.This study has practical significance in developing the technology for material analysis using LIBS,especially when the LIBS signal exhibits a complex dependence on the material parameter to be estimated.

Phase field model for electric-thermal coupled discharge breakdown of polyimide nanocomposites under high frequency electrical stress

In contrast to conventional transformers, power electronic transformers, as an integral component of new energy power system, are often subjected to high-frequency and transient electrical stresses, leading to heightened concerns regarding insulation failures. Meanwhile, the underlying mechanism behind discharge breakdown failure and nanofiller enhancement under high-frequency electrical stress remains unclear. An electric-thermal coupled discharge breakdown phase field model was constructed to study the evolution of the breakdown path in polyimide nanocomposite insulation subjected to high-frequency stress. The investigation focused on analyzing the effect of various factors, including frequency, temperature, and nanofiller shape, on the breakdown path of Polyimide(PI) composites. Additionally, it elucidated the enhancement mechanism of nano-modified composite insulation at the mesoscopic scale. The results indicated that with increasing frequency and temperature, the discharge breakdown path demonstrates accelerated development, accompanied by a gradual dominance of Joule heat energy. This enhancement is attributed to the dispersed electric field distribution and the hindering effect of the nanosheets. The research findings offer a theoretical foundation and methodological framework to inform the optimal design and performance management of new insulating materials utilized in high-frequency power equipment.

Characteristics of laser-induced breakdown spectroscopy of liquid slag

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Integrated Experimental and Simulation Investigation of Breakdown Voltage Characteristics Across Electrode Configurations in SF_(6) Circuit Breakers

This study investigates the breakdown voltage characteristics in sulfur hexafluoride(SF6)circuit breakers,employing a novel approach that integrates both experimental investigations and finite element simulations.Utilizing a sphere-sphere electrode configuration,we meticulously measured the relationship between breakdown voltage and electrode gap distances ranging from 1 cm to 4.5 cm.Subsequent simulations,conducted using COMSOL Multiphysics,mirrored the experimental setup to validate the model’s accuracy through a comparison of the breakdown voltage-electrode gap distance curves.The simulation results not only aligned closely with the experimental data but also allowed the extraction of detailed electric field strength,electric potential contours,and electric current flow curves at the breakdown voltage for gap distances extending from 1 to 4.5 cm.Extending the analysis,the study explored the electric field and potential distribution at a constant voltage of 72.5 kV for gap distances between 1 to 10 cm,identifying the maximum electric field strength.A comprehensive comparison of five different electrode configurations(sphere-sphere,sphere-rod,sphere-plane,rod-plane,rod-rod)at 72.5 kV and a gap distance of 1.84 cm underscored the significant influence of electrode geometry on the breakdown process.Moreover,the research contrasts the breakdown voltage in SF6 with that in air,emphasizing SF6’s superior insulating properties.This investigation not only elucidates the intricate dynamics of electrical breakdown in SF6 circuit breakers but also contributes valuable insights into the optimal electrode configurations and the potential for alternative insulating gases,steering future advancements in high-voltage circuit breaker technology.

Stability analysis of CO_(2)gas shielded welding short-circuit transition process based on GMAW dynamic model

Base on the arc phase and short-circuit phase and their relationship, the paper considers the changes of the extension of wire, the arc length, liquid bridge resistance and mass of liquid bridge, combines the improved “mass-spring” model with the loop model of welding power system, puts forward the critical judgment condition of droplet transition, and establishes a more accurate dynamic model for describing the short-circuit transition process. The dynamic changes of short-circuit transfer frequency, welding current and voltage, contact droplet and residual droplet equivalent radius and droplet equivalent radius at different wire feeding speeds were calculated and analyzed, and compared with the experimental results. It shows that the fluctuation of droplet displacement, velocity and wire extension length at the optimal arc starting point is the smallest. The smaller the initial liquid bridge curvature radius is, the better the stability of short-circuit transfer is.

Self-absorption effects of laser-induced breakdown spectroscopy under different gases and gas pressures

The self-absorption effect is one of the main factors affecting the quantitative analysis accuracy of laser-induced breakdown spectroscopy.In this paper,the self-absorption effects of laserinduced 7050 Al alloy plasma under different pressures in air,Ar,and N2have been studied.Compared with air and N2,Ar significantly enhances the spectral signal.Furthermore,the spectral self-absorption coefficient is calculated to quantify the degree of self-absorption,and the influences of gas species and gas pressure on self-absorption are analyzed.In addition,it is found that the spectral intensity fluctuates with the change of pressure of three gases.It can also be seen that the fluctuation of spectral intensity with pressure is eliminated after correcting,which indicates that the self-absorption leads to the fluctuation of spectral intensity under different pressures.The analysis shows that the evolution of optical thin spectral lines with pressure in different gases is mainly determined by the gas properties and the competition between plasma confinement and Rayleigh–Taylor instability.

A data selection method for matrix effects and uncertainty reduction for laser-induced breakdown spectroscopy

Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal uncertainty.By selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification performance.When applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,respectively.These results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.

Influence of the electrolyte conductivity on the critical current density and the breakdown voltage

The work investigates influence of the electrolyte conductivity on the onset of partial contact glow discharge electrolysis(CGDE)in a water electrolysis.Critical current density(CCD)and breakdown voltage were measured together with in situ observation of hydrogen bubble behavior,whose influence has not been focused on.For a fixed current during normal electrolysis,hydrogen coalescence adjacent to cathode surface was invigorated at a lower conductivity.Photographic analyses elucidated the hydrogen coalescence characteristics by quantifying size and population of detached hydrogen bubbles.The CCD increased about 104% within given range of conductivity(11.50-127.48 mS·cm^(-1))due to impaired bubble coalescence,which delays hydrogen film formation on the cathode.Meanwhile,decreasing trend of breakdown voltage was measured with increased conductivity showing maximum drop of 74%.It is concluded that onset of partial CGDE is directly affected by hydrodynamic bubble behaviors,whereas the electrolyte conductivity affects the bubble formation characteristics adjacent to cathode electrode.

Matrix effect suppressing in the element analysis of soils by laser-induced breakdown spectroscopy with acoustic correction

Laser-induced breakdown spectroscopy(LIBS)has been used for soil analysis,but its measurement accuracy is often influenced by matrix effects of different kinds of soils.In this work,a method for matrix effect suppressing was developed using laser-induced plasma acoustic signals to correct the original spectrum,thereby improving the analysis accuracy of the soil elements.A good linear relationship was investigated firstly between the original spectral intensity and the acoustic signals.The relative standard deviations(RSDs)of Mg,Ca,Sr,and Ba elements were then calculated for both the original spectrum and the spectrum with the acoustic correction,and the RSDs were significantly reduced with the acoustic correction.Finally,calibration curves of MgⅠ285.213 nm,CaⅠ422.673 nm,SrⅠ460.733 nm and BaⅡ455.403 nm were established to assess the analytical performance of the proposed acoustic correction method.The values of the determination coefficient(R~2)of the calibration curves for Mg,Ca,Sr,and Ba elements,corrected by the acoustic amplitude,are improved from 0.9845,0.9588,0.6165,and 0.6490 to 0.9876,0.9677,0.8768,and 0.8209,respectively.The values of R~2 of the calibration curves corrected by the acoustic energy are further improved to 0.9917,0.9827,0.8835,and 0.8694,respectively.These results suggest that the matrix effect of LIBS on soils can be clearly improved by using acoustic correction,and acoustic energy correction works more efficiently than acoustic amplitude correction.This work provides a simple and efficient method for correcting matrix effects in the element analysis of soils by acoustic signals.

Design optimization of high breakdown voltage vertical GaN junction barrier Schottky diode with high-K/low-K compound dielectric structure

A vertical junction barrier Schottky diode with a high-K/low-K compound dielectric structure is proposed and optimized to achieve a high breakdown voltage(BV).There is a discontinuity of the electric field at the interface of high-K and low-K layers due to the different dielectric constants of high-K and low-K dielectric layers.A new electric field peak is introduced in the n-type drift region of junction barrier Schottky diode(JBS),so the distribution of electric field in JBS becomes more uniform.At the same time,the effect of electric-power line concentration at the p-n junction interface is suppressed due to the effects of the high-K dielectric layer and an enhancement of breakdown voltage can be achieved.Numerical simulations demonstrate that GaN JBS with a specific on-resistance(R_(on,sp)) of 2.07 mΩ·cm^(2) and a BV of 4171 V which is 167% higher than the breakdown voltage of the common structure,resulting in a high figure-of-merit(FOM) of 8.6 GW/cm^(2),and a low turn-on voltage of 0.6 V.

Detection and quantification of Pb and Cr in oysters using laser-induced breakdown spectroscopy

The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.

Research on Inter-turn Short-circuit Fault Diagnosis Method Based on High Frequency Voltage Residual for PMSM

Inter-turn fault is a serious stator winding short-circuit fault of permanent magnet synchronous machine(PMSM). Once it occurs, it produces a huge short-circuit current that poses a great risk to the safe operation of PMSM. Thus, an inter-turn short-circuit fault(ITSCF) diagnosis method based on high frequency(HF) voltage residual is proposed in this paper with proper HF signal injection. First, the analytical models of PMSM after the ITSCF are deduced. Based on the model, the voltage residual at low frequency(LF) and HF can be obtained. It is revealed that the HF voltage residual has a stronger ITSCF detection capability compared to the LF voltage residual. To obtain optimal fault signature, a 3-phase symmetrical HF voltage is injected into the machine drive system, and the HF voltage residuals are extracted. The fault indicator is defined as the standard deviation of the 3-phase HF voltage residuals. The effectiveness of the proposed ITSCF diagnosis method is verified by experiments on a triple 3-phase PMSM. It is worth noting that no extra hardware equipment is required to implement the proposed method.

LIBS结合图像筛选方法提高钢铁中Cu、Cr、Mn元素检测稳定性研究

优质特种钢材和低端粗钢之间的性能差异主要受其构成元素种类及其成分含量的影响,因此,如何快速准确地对物质成分进行定性及定量分析对钢铁产品的质量评估至关重要。针对传统方法难以实现对钢铁合金成分的快速准确检测的难题,采用激光诱导击穿光谱(LIBS)结合等离子体图像信息的方法,通过快速地对不同元素的特征光谱强度与激发生成的等离子体图像进行采集,分析两者之间的相关性,并通过提取的图像特征信息的异常值剔除了部分无效光谱数据,进而实现了对钢铁成分的高精度分析。通过分析延迟时间和激光能量等不同实验条件对元素特征光谱强度及其对应等离子体图像的影响规律,不仅证明了等离子体图像与光谱之间存在相关性,还利用等离子体图像特征信息的局部最优值确定了最优延迟时间、激光能量分别为1000 ns与50 mJ,并根据图像特征的平均阈值来筛选无效光谱数据。结果表明,图像筛选优化数据后,各元素谱线校准模型的决定系数(R^(2))分别从原始数据的0.978、0.986、0.957、0.935提升至0.995、0.997、0.968、0.957,且其定标曲线对未知样品元素的预测浓度相对标准偏差(RSD)下降为原始数据预测浓度RSD的50%左右。由此可知采用LIBS结合图像筛选方法可以减少定量分析的误差,提高预测结果精确度。

便携式激光诱导击穿光谱仪测定土壤中重金属

土壤重金属污染对农作物生长和人体健康都有严重危害,现场快速检测对土壤重金属污染调查、应急监测具有重要意义。采用自主研发的土壤重金属激光诱导击穿光谱现场快速检测仪对矿区周边土壤进行现场检测分析,以835个不同基质土壤的光谱数据建立定标数据库,通过支持向量机建立回归模型对土壤重金属元素含量进行定量反演。现场检测获取的全波段光谱波动在15%以内,Cd、Cr、Cu、Ni、Pb和Zn等6种元素光谱强度相对标准偏差平均值为6.31%。将检测结果与实验室电感耦合等离子体质谱法分析对比,6种元素的皮尔逊相关系数r在0.8501~0.9829,检测结果80%以上处于±30%相对误差区间分布。对比结果表明自主研发的土壤重金属激光诱导击穿光谱现场检测仪可以满足现场快速检测需求。