Preparation and properties of Ce0.8Ca0.2O1.8 anode material by glycine-nitrate process

Ce0.8Ca0.2O1.8（CDC82） anode material was prepared by glycine-nitrate process（GNP）. Thermogravimetric（TG） analysis and differential scanning calorimetric（DSC） methods were adopted to characterize the reaction process of CDC82 material. X-ray diffractometry（XRD）, scanning electron microcopy（SEM）, direct current four probe （four-probe DC） and temperature process reduce（TPR） techniques were adopted to characterize the properties of CDC82 material. After the precursor was sintered at 750℃ for 4 h, CDC82 material with pure-fluorite structure and nanometer size was obtained. The total conductivity of CDC82 changes little with temperature in air at 50-850℃, and the maximum value is 0.04 S/cm at 750 ℃. The total conductivity wholly becomes larger when the atmosphere changes from air to hydrogen, which greatly increases with increasing temperature and reaches the maximum value of 1.09 S/cm at 850 ℃. Some impurities such as CeMg and La203 exist after the mixture of CDC82 anode and La1-xSrxGa1-yMgyO3-δ （LSGM） electrolyte material is sintered at 1 200 ℃ for 15 h. The CDC82 material as anode material has excellent catalytic property for hydrogen and methane.     

Prediction of Al（OH）3 fluidized roasting temperature based on wavelet neural network

The recycle fluidization roasting in alumina production was studied and a temperature forecast model was established based on wavelet neural network that had a momentum item and an adjustable learning rate. By analyzing the roasting process, coal gas flux, aluminium hydroxide feeding and oxygen content were ascertained as the main parameters for the forecast model. The order and delay time of each parameter in the model were deduced by F test method. With 400 groups of sample data （sampled with the period of 1.5 min） for its training, a wavelet neural network model was acquired that had a structure of {7^-21^-1}, i.e., seven nodes in the input layer, twenty-one nodes in the hidden layer and one node in the output layer. Testing on the prediction accuracy of the model shows that as the absolute error ±5.0 ℃ is adopted, the single-step prediction accuracy can achieve 90% and within 6 steps the multi-step forecast result of model for temperature is receivable.     

红外线测温系统在矿用高强度圆环链连续中频热处理中的应用

阐述了在矿用高强度圆环链连续中频热处理中红外线测温的一些关键问题,建立了红外线在线测温系统,实现了对热处理工艺的精确控制.结果表明,采用红外线在线测温后,矿用高强度圆环链热处理后的合格率明显提高.     

氟化钙对单晶硅片磨削用树脂结合剂金刚石砂轮磨削性能的影响

在单晶硅片磨削用树脂结合剂金刚石砂轮中分别添加不同体积分数的固体润滑剂氟化钙(CaF₂),评估其对砂轮表面结构、砂轮磨损量、磨床主轴电流的影响,并测量和计算单晶硅片的表面粗糙度和表面损伤层厚度。结果显示:随CaF₂用量增加,磨床主轴电流、砂轮磨损量、单晶硅片的表面粗糙度值和表面损伤层厚度均下降;当CaF₂体积分数为25%时,主轴电流降至约6.4 A,砂轮磨损量降到每片0.448 6 μm,单晶硅片的表面粗糙度R_a、R_y和R_z分别为0.056 μm、0.382 μm和0.396 μm,表面损伤层厚0.559 6 μm。加入CaF₂固体润滑剂可有效改善树脂金刚石砂轮的性能,提高单晶硅片表面的加工质量,且CaF₂体积分数为25%时效果最佳。      

砂轮表面磨粒出露高度对轴承钢磨削振动的影响

为探究砂轮表面磨粒形态对磨削振动的影响规律,提高磨削加工质量,构建了磨削振动模型并推导磨粒形态-接触刚性-磨削振动的对应关系,开展修整-磨削试验,通过试验分析并验证不同磨粒形态对磨削振动信号RMS和工件表面波纹特征W_a影响的差异。结果表明:在不影响砂轮锋利性的前提下,表征磨粒出露高度的砂轮AH值减小约58%,则RMS值和W_a值分别减小约47%和57%;在相同磨粒出露高度条件下,磨粒钝化的比例约20%,则RMS和W_a分别减小约22%和30%;同时,适度减小磨粒出露高度,磨粒适度钝化,有助于增大磨粒与工件接触面积,改善磨削振动,提高磨削加工质量。且提出的磨削振动模型与试验结果相符。      

钢结构制造中焊接变形的控制方法

着重介绍了桥梁、建筑、船舶、压力容器等钢结构制造中经常遇到的一个比较棘手的问题--焊接变形的控制方法和解决方案.     

Q345型中厚钢板拼接中优化焊缝的工艺措施

从焊材的合理选择、焊接方法的合理选用、坡口形式的合理制定、焊接过程控制、采用多层多道焊接、制定合理的焊接顺序等方面,介绍了Q345型中厚钢板拼接中优化焊缝的工艺措施.     

利用镶套技术提高冷镦模具寿命的设计方法

在金属压力加工生产中,针对一些企业采用整模结构的冷镦模具疲劳寿命极低的现状,提出以多层镶套膜替代整体模具,通过改变冷镦模具受力方式,使冷镦件模具达到较高寿命的设计方法.以螺栓圆头的冷镦试验结果为依据,以应力分析方法为基础,应用力学有关理论,导出了生产实践中实用的镶套模具设计原理与经验公式,并举例说明了该方法的具体应用.     

计算机控制管道焊接机器人屏蔽技术

在电弧强干扰下管道焊接机器人抗干扰设计成为管道焊接过程稳定性关键,其中管道焊接机器人屏蔽技术是主要影响因素之一。通过对管道焊接机器人电磁场屏蔽、屏蔽线、双绞线和屏蔽双绞线屏蔽原理分析,提出屏蔽完整性,面板孔、电连接器、电路板屏蔽和多层屏蔽等措施。提高屏蔽材料的屏蔽效能要考虑金属平板材料性质、电磁场源性质、电磁场源与金属平板的距离、屏蔽体接地等状况。以上研究成果可为管道焊接机器人制造提供理论和实践上参考依据。     

高铝锌基合金直齿圆锥齿轮的挤压铸造工艺

利用挤压铸造技术生产高铝锌基合金直齿圆锥齿轮，齿面精度能够得到保证。适用于工作环境较好，载荷不是很大条件下的高铝锌基合金直齿圆锥齿轮，可减少设备投资、减少工序工时，从而大大降低生产成本，具有很高的经济效益和社会效益。