一种小电流下的引弧及稳弧方法

介绍一种小电流直流TIG焊中的引弧及稳弧方法，并对实现此功能的控制电路进行了详细的分析。简单介绍了此种小型焊机的特点及用途。     

埋弧焊方法的使用

通过对埋弧焊工作原理、特点和焊接工艺的介绍,提出了鸿源卷管的焊接参数,埋弧焊焊接缺陷及其防止措施。     

直流电弧炉长弧泡沫渣技术

本文指出了直流电弧炉采用长弧泡沫渣技术的必要性及该技术的发展现状，总结了炉渣物理性质，化学成分，温度和气源等对炉渣泡沫化的影响，并介绍了电炉泡沫渣的操作工艺及实际应用效果，对宝钢三期１５０ｔＤＣ－ＵＨＰ电弧炉的泡沫渣工艺提出了看法。     

Characteristics and classification of high-current fault arcs on distribution systems

When a fault occurs on transmission or distribution systems due to lightning or overvoltage, often an arc discharge occurs at the fault point. The arc discharge, which is caused by a fault current, has a high current, high temperature, strong light emission, etc., thus it sometimes causes heavy damages to electric power equipment. The arc discharge is influenced by the conditions around the arcs, i.e., gas, insulation materials, gap length, weather, etc. Also, the arc voltage along the arc column indicates the characteristics of the arc. If the voltage waveforms of the arcs caused by the fault on transmission or distribution systems are classified, it is possible to find the location and the equipment where the fault occurred. In this paper, the arc voltage data in 6-kV class XLPE cables and 6-kV class overhead lines are analyzed and an artificial neural network method is applied to classify the arc voltage waveforms. The results obtained from the six artificial neural networks developed show that the artificial neural network method is effective for classification of arc voltage waveforms if adequate input parameters are selected.     

Isometric Piecewise Polynomial Curves

The main preoccupations of research in computer-aided geometric design have been on shape-specification techniques for polynomial curves and surfaces, and on the continuity between segments or patches. When modelling with such techniques, curves and surfaces can be compressed or expanded arbitrarily. There has been relatively little work on interacting with direct spatial properties of curves and surfaces, such as their arc length or surface area. As a first step, we derive families of parametric piecewise polynomial curves that satisfy various positional and tangential constraints together with arc-length constraints. We call these curves isometric curves. A space curve is defined as a sequence of polynomial curve segments, each of which is defined by the familiar Hermite or Bézier constraints for cubic polynomials; as well, each segment is constrained to have a specified arc length. We demonstrate that this class of curves is attractive and stable. We also describe the numerical techniques used that are sufficient for achieving real time interaction with these curves on low-end workstations.     

真空阴极弧离子镀类金刚石碳（DLC）膜的碳弧稳定性研究

选用氩气、氩气加氢气、氩气加乙炔等气体作为介质，石墨作为靶材进行真空阴极弧离子镀来制备类金刚石碳膜。石墨电弧有其独特的电弧特性曲线，不同气体介质对碳弧特性的影响不同，磁场的大小对电弧的稳定性有很大作用，碳弧下基片偏流随电弧电压的增加而减小，试验得到表面光滑的类金刚石碳（DLC）膜，对膜的表面进行了SEM分析。     

立铣加工过程中的微元铣削力建模分析

针对单纯通过高速切削技术制造某些大型飞机零件过程中,存在难以控制的加工变形和较强表面残余拉应力分布等突出问题,以直齿和螺旋齿立铣加工过程为研究对象,基于微元切削机理,通过对刀齿铣削过程的分析,建立动态铣削加工仿真模型,导出铣削面积、铣削力、主轴扭矩、铣削功率与切削用量的关系.数值模拟结果与试验值较吻合,表明该模型可以实现动态铣削力预测,优化切削用量.     

基于暂态零序能量的配电网故障选线方法研究

针对中性点经消弧线圈接地系统发生单相接地故障时因故障边界复杂、随机,故障稳态分量小,零序瞬时功率倒相而导致传统的单一特征量选线方法失效问题,提出了一种新的基于暂态零序能量的选线方法。该方法通过一种数字滤波器来滤除暂态零序电流中的不对称分量和稳态工频分量,得到各条线路零序电流和母线零序电压的暂态纯故障分量,由此构造暂态零序能量,并根据暂态零序能量的大小和方向判断故障类型及线路,即发生单相接地故障时,非故障线路暂态零序能量的方向为正,故障线路暂态零序能量的方向为负,且其绝对值为其余线路暂态零序能量之和;发生母线接地故障时,母线暂态零序能量的大小为其余线路暂态零序能量之和。针对母线暂态零序能量受噪声影响大而导致选线灵敏度低的问题,提出将自动重合闸技术应用到该选线方法中的方案。Matlab仿真结果表明,该选线方法的准确性、可靠性较高。     

基于模糊神经网络的电弧炉控制系统及仿真

电极调节系统是电弧炉炼钢过程不可缺少的基本装备。目前常用的电极调节器大多是基于单相意识,导致电极调节中电极往往误动作,大大影响了电弧炉的运行效益。在模糊控制和神经网络的基础上,探索研究一种基于三相意识的电弧炉控制新方法,采用模糊神经网络调节器控制对电弧炉电极进行调节,控制弧流弧压稳定在一定范围之内,使电弧炉冶炼达到有功功率最大化,进一步提高电弧炉的综合运行效益,降低能耗、减轻对电网危害。并用matlab对模糊神经网络进行仿真。结果表明,本网络具有较快的训练速度和较高的泛化能力,满足电弧炉控制的要求,其控制性能优于常规电弧炉控制系统。     

The statistical modeling of surface roughness in high-speed flat end milling

Surface roughness is one of the most important requirements in machining process. The surface roughness value is a result of the tool wear. When tool wear increase, the surface roughness also increases. The determination of the sufficient cutting parameters is a very important process obtained by means of both minimum surface roughness values and long tool life. The statistical models were developed to predict the surface roughness.This paper presents the development of a statistical model for surface roughness estimation in a high-speed flat end milling process under wet cutting conditions, using machining variables such as spindle speed, feed rate, depth of cut, and step over. First- and second-order models were developed using experimental results of a rotatable central composite design, and assessed by means of various statistical tests. The highest coefficient of correlation (R_adj²) (88%) was obtained with a 10-parameter second-order model. Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting the probable effect of the tool wear on surface roughness. Thus, in order to enhance the estimation capability of the model, another independent variable was included into the model to account for the effect of the tool wear, and the total operating time of the tool was selected as the most suitable variable for this purpose. By inserting this new variable as a linear term into the model, R_adj² was increased to 94% and a good fit was observed between the model predictions and supplementary experimental data.In this study, it was observed that, the order of significance of the main variables is as X₅>X₃>X₄>X₁>X₂ (total machining time, depth of cut, step over, spindle speed and feed rate, respectively).