莱芜黑猪肉中烟酸含量的测定

采用高效液相色谱法测定莱芜黑猪肉中烟酸的含量,并对提取方法及色谱条件等方面进行了改进,以Kromasil C_(18)柱为分离柱,甲醇–0.05mol/L磷酸二氢钾缓冲液(体积比5∶95)为流动相,柱温30℃,紫外检测器在波长261nm条件下检测,可以在4min左右完成分析。烟酸在1.0～25.0mg/L范围内有良好的线性关系(R=0.9998),相对标准偏差为0.62%(n=6),平均加标回收率为98.4%,检出限为2.0×10~(-4)g/kg,为准确测定莱芜黑猪肉中的烟酸含量提供了一种简便快捷的检测方法。     

小像元红外探测器读出电路设计研究

介绍了基于SMIC 0.18 μm 3.3 V工艺设计研究的第一款小像元红外探测器读出电路,间距10 μm,规模1024×1024。文章详细介绍了像素输入级以及列级、输出级运放的设计,为提高线性摆伏,设计选用了低阈值NMOS管nmvt 33,仿真分析证明低阈值管nmvt 33的噪声性能优于普通管n 33；版图设计对关键信号线和敏感点采取隔离处理措施,对像元间串扰进行了仿真分析,有效控制了信号串扰。电路经测试使用各项功能正常,最大电荷处理能力达到4.3 Me-,动态范围≥65 dB,读出速率达到10 MHz,性能指标满足设计要求。     

基于投影寻踪的径向基函数网络在参考腾发量预测中的应用

径向基函数网络(RBFN)已广泛应用于参考腾发量预测等领域，但常用的K均值聚类和自组织特征映射等方法在求取径向基函数网络隐层节点中心时存在较大不足。针对这一问题，本文引入投影寻踪方法，在投影降维的基础上实现对大量高维数据的聚类，建立了基于投影寻踪的径向基函数网络模型，并将该模型应用于山西潇河灌区参考腾发量的预测，研究了不同气象因子输入对参考腾发量预测精度的影响。结果表明，基于投影寻踪的径向基函数网络具有较强的适用性，只需使用最高温度、最低温度、日照时数和旬序数作为输入因子，就能以较高的精度预测参考腾发量。     

数量够不够,百姓看得见

针对我国定量包装商品的种类和数量迅速增加 ,百姓的日常生活已和定量包装商品行业密不可分 ,产品的数量够不够是老百姓最为关心的一个问题 ,国家质量技术监督局于 2 0 0 1年 4月发布了《定量包装商品生产企业计量保证能力评价规定》和《定量包装商品生产企业计量保证能力评价规范》。凡符合《规范》要求的生产企业可以在其生产的定量包装商品上使用全国统一的计量保证能力合格标志“Ｃ” ,有“Ｃ”标志的商品是经国家考核合格的企业生产的合格产品 ,该标志图形为外沿是正八边形 ,内沿是正方形。使用“Ｃ”标志时 ,应清晰易见 ,在正常使用条…     

吐丝圈径对大规格高碳盘条组织性能的影响

计算与分析了斯太尔摩冷线上盘条的吐丝圈径、搭接密度及"佳灵"装置横向布风曲线之间的关系,研究了吐丝圈径的大小对大规格82B盘条组织和性能的影响,确定了大规格82B盘条最小吐丝圈径应为980mm.     

Effects of modeling means on properties of monitoring models of spot welding quality

Analyzing and modeling the relation between monitoring information during welding and quality information of the joints is the foundation of monitoring resistance spot welding quality. According to the means of modeling, the known models can be divided into three large categories: single linear regression models, multiple linear regression models and multiple non-linear models. By modeling the relations between dynamic resistance information and welding quality parameters with different means, this paper analyzes effects of modeling means on performances of monitoring models of resistance spot welding quality. From the test results, the following conclusions can be drawn: By comparison with two other kinds of models, artificial neural network (ANN) model can describe non-linear and high coupling relationship between monitoring information and quality information more reasonably, improve performance of monitoring model remarkably, and make the estimated values of welding quality parameters more accurate and reliable.     

Effects of modeling means on properties of monitoring models o spot welding quality

Analyzing and modeling the relation between monitoring information during welding and quality information of the joints is the foundation of monitoring resistance spot welding quality.According to the means of modeling,the known models can be divided into three large categories:single linear regression models,multiple linear regression models and multiple nonlinear models.By modeling the relations between dynamic resistance information and welding quality parameters with different means,this paper analyzes effects of modeling means on performances of monitoring models of resistance spot welding quality. From the test results,the following conclustons can be drawn:By comparison with two other kinds of models,artificial neural network(ANN) model can describe non-linear and high coupling relationship between monitoring information and quality information more reasonably,improve performance of monitoring model remarkably,and make the estimated values of welding quality parameters more accurate and reliable.