不同加工方法形成的304钢种试样表面在直读光谱分析上的数据差异探讨

运用单因子方差分析法设计直读光谱仪分析不同加工方法(不同水平)形成的304钢种的试样表面Cr、Ni等9个元素测试方法并对结果进行处理。对不同水平下的光谱分析数据在显著性水平α=0.05上是否存在差异进行了分析与探讨。     

国家标准样品在空气自动监测系统方面的应用

阐述了国家标准样品在空气自监测系统量值溯源中的重要作用。介绍了国家标准样品SO2标准钢瓶气在荧光SO2分析仪校准中的应用。     

LSSVM在指数寿命型小子样IC寿命预测的应用

针对传统寿命预测方法需要大量样本与现代高可靠集成电路（IC）在寿命试验中通常只有少量失效样本的矛盾,提出了基于最小二乘支持向量机（LSSVM）的指数寿命型小子样IC寿命预测方法。用蒙特卡罗方法研究了该方法在指数寿命型IC寿命预测应用中的可行性,同时与基于神经网络的预测方法相比,结果表明基于LSSVM的方法能更精确地预测小子样下IC的寿命,可为预测指数寿命型小子样IC的寿命提供一种新的有效途径。     

基于ML模型的样本量研究

在BL模型（2项选择Logit模型）样本量确定方法的基础上,分析推导ML模型（多项选择Logit模型）样本量的确定,对建立多项Logit模型开展相关调查确定样本容量具有指导作用。     

Abel逆变换的数值算法

针对电弧等离子体温度场分析中Abel逆变换的计算,提出了3种数值解法：三次样条插值法、Radon逆变换法以及离散数据曲线拟合法。通过对单峰型函数进行验证,分析了各种方法的特点,对3种方法在精度、程序实现性以及积分奇异点处理等方面进行了比较,指出它们在不同的实际温度场分析计算中各自的优势。     

基于SVR的旋转电弧焊接形态预测模型

本文提出了SVR算法建立旋转电弧焊接形态的算法。旋转电弧焊接过程是一个多因素耦合的过程,有必要建立关于旋转电弧焊接的焊缝形态预测模型。选择旋转频率,旋转半径,焊枪高度和焊接电流的四个主要变量作为模型的输入,焊缝的宽度和深度作为输出。试验结果表明,基于SVR建立的焊缝形态预测模型在小样本训练数据的情况下具有较高的精度。     

基于功率谱密度与随机配置网络的低压串联电弧故障检测

低压串联电弧电流为非平稳信号,故障特征区分度低且具有随机性,给电弧故障特征提取和准确检测带来困难,提出了基于功率谱密度与随机配置网络的低压串联电弧故障检测方法。首先,搭建了串联电弧故障发生平台,采集不同负载类型的电流数据,构建数据集。其次,采用功率谱密度对电流信号执行随机信号分析,实现对电流信号的定量化频域特征描述,增强故障电流与正常电流特征的区分度。然后,采用随机配置网络构建串联电弧故障检测模型,将功率谱密度特征用于随机配置网络的自适应训练学习,提升网络训练效率和模型故障检测能力。在本文构建的电流数据集上,串联电弧故障检测的平均准确率达到96.156 7%,证明了方法的有效性。     

Ultrasound effects on zinc recovery from EAF dust by sulfuric acid leaching

In this work, an ultrasound-assisted leaching process was studied for the recovery of zinc from electric arc furnace (EAF) dust, in which zinc was mainly present in the form of franklinite (60%). Hydrometallurgy is emerging as a preferred process for the recovery of a variety of metals, and the use of ultrasound could offer advantages over the conventional leaching process, especially for the dissolution of franklinite. Franklinite is a refractory phase that is difficult to leach and represents the main obstacle in conventional hydrometallurgy processing. Atmospheric leaching with different sulfuric acid concentrations (0.2-2.0 M) at two temperatures (323 and 353 K) was performed. The tests were conducted using both conventional and ultrasound-assisted leaching. After the leaching tests, the solid residues were characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques, whereas the leach liquor was analyzed by inductively coupled plasma spectroscopy (ICP). The use of ultrasound facilitated the dissolution of franklinite at low acid concentrations and resulted in a greater zinc recovery under all of the investigated operating conditions.     

New pyrometallurgical process of EAF dust treatment with CaO addition

The non-carbothermic zinc pyrometallurgical processing of electric arc furnace (EAF) dust was investigated on a laboratory scale. The main objective of this process was to convert highly stable zinc ferrite (ZnFe₂O₄), which accounts for more than half of total zinc in the EAF dust, into ZnO and Ca₂Fe₂O₅ by CaO addition. The EAF dust was mixed with CaO powder in various ratios, pressed into pellets, and heated in a muffle furnace in air at temperatures ranging from 700 to 1100℃ for a predetermined holding time. All ZnFe₂O₄ was transformed into ZnO and Ca₂Fe₂O₅ at a minimum temperature of 900℃ within 1 h when sufficient CaO to achieve a Ca/Fe molar ratio of 1.1 was added. However, at higher temperatures, excess CaO beyond the stoichiometric ratio was required because it was consumed by reactions leading to the formation of compounds other than ZnFe₂O₄. The evaporation of halides and heavy metals in the EAF dust was also studied. These components could be preferentially volatilized into the gas phase at 1100℃ when CaO was added.     

液相微萃取的概念及应用

液相微萃取是近十几年发展起来的一种新型的样品前处理技术,集采样、萃取和浓缩几个步骤于一体,具有快速、简便、绿色环保等优势,已被广泛应用于各个领域化学分析检测的样品前处理过程。文章对液相微萃取的概念、特点、技术分支及应用进行了介绍。