一种舰船光电装备光轴检测仪

为了在实验外场和装舰现场克服舰船光电装备多传感器光轴一致性标校中由于环境限制、舰船摇晃等造成的操作困难,提出一种舰船光轴检测仪方案。通过共光路和光谱转换技术实现激光光轴与可见光轴的耦合,激光像斑在可见光通道输出成像视频,依据像斑中心与装备十字刻线位置关系判断激光与可见光光轴的一致性。应用CAD/CAE技术对光轴检测仪的关键器件——光轴耦合单元进行仿真分析,得到-10℃~+40℃温度范围内的反射镜面平行性误差分别为13.576 332″和16.397 421;″整机环境实验结果表明,光轴检测仪本身精度误差小于20,″满足光电装备光轴的一致性要求。     

对阿基米德定律演示仪器的改进

改进了阿基米德定律演示实验装置。通过重新设计阿基米德定律演示实验仪的支架结构和溢水杯的出水口,使整套设备操作使用方便,效果明显提高。     

珀尔贴效应演示仪的研制

本文介绍了半导体致冷器件的原理,并依此原理研制了一台珀尔贴效应教学演示仪。     

小型图形文字显示器

本文介绍一种微处理器控制的显示器,采用五时显示管,显示方式为光栅式,可作为仪器仪表或过程控制中的显示部件。     

电热蒸发-直接进样-冷原子吸收光谱法测定土壤以及沉积物中汞

采用传统分析仪器测定汞元素,需要对样品进行化学消解,存在操作繁杂、效率低以及易交叉污染等问题。故建立了电热蒸发-直接进样-HGA-100测汞仪测定土壤以及沉积物中汞的方法,无需对样品进行化学前处理,降低环境污染。通过优化HGA-100测汞仪参数条件,汞质量浓度在0~20ng以及20~200ng,相关系数优于0.998,准确称量样品0.05g(精确至0.000 1g),方法检出限为0.5μg/kg,相对标准偏差1.6%~4.6%,加标回收率在90.1%~100%。方法用于对土壤和沉积物标准物质测定,结果与标准值相符。方法高效、准确,可用于测定土壤以及沉积物中的汞。     

利用Access数据库进行计量器具管理

介绍应用Access数据库进行计量器具管理的具体操作方法,包括有关数据表和查询表的设计、建立及使用方法。     

密闭微波消解-测汞仪法测定铜精矿中高含量的汞

建立了微波消解-测汞仪法测定铜精矿中高含量汞的分析方法。采用在密闭的环境下微波消解预处理铜精矿试样,既能保证试样溶解完全,又有效避免了高温溶样对易挥发元素汞的损失。在将铜精矿试液移取至于石英舟中,在氧气气氛中,试液在分解炉中经历干燥和高温热分解,汞被还原成汞原子,再被氧气流带进汞齐化管中进行汞齐化反应,其中的汞被选择性吸附,于900℃加热释放出汞蒸汽,汞蒸气被氧气流带入单波长光学吸收池进行原子吸收测量,测定结果的相对标准偏差为0.62~1.95%%(n=11),加标回收率为98.45%～100.45%,测定范围为0.60 μg/g~1000μg/g,可测定汞含量较高的铜精矿,且有效的延长了仪器的使用寿命。方法操作简单、快速稳定、重现性良好,适合于铜精矿中高含量汞的测定。     

Polynomial multivariate least‐squares regression for modeling nonlinear data applied to in‐depth characterization of chromatographic resolution

Well‐established, linear multivariate calibration methods such as multivariate least‐squares regression (MLR), principal component regression (PCR), or partial least squares (PLS) have two limitations: (i) measured data must be linearly related to the response variables and (ii) predictor variables x_{n = 1, …, N} cannot be coupled to each other. For evaluation of nonlinear data, however, these restrictions need to be overcome and thus polynomial multivariate least‐squares regression (PMLR or “response surfaces”) has been introduced here. PMLR is based on multivariate least squares but incorporates all combinations of predictor variables up to a user‐selected polynomial order (e.g., including u or v = 0). Because of the inclusion of such coupled terms and their powers, PMLR models are better adapted to model nonlinear data and can help to enhance the prediction step's accuracy and precision. PMLR has been based on MLR because it facilitates—unlike PCR or PLS—a physical and chemical interpretation of the predictors. Hence, the origins and the relevance of nonlinear and/or coupled predictors can be investigated. The details of the PMLR algorithm and its implementation are presented along with a method for model optimization utilizing gradients of response surfaces. Newly developed PMLR models up to quintic order have been applied to predict a chromatograph's peak resolution as a function of six‐instrument parameters. It has been demonstrated that PMLR is better capable than MLR and PCR to describe these nonlinear and coupled instrument parameters. In addition, the novel software tool has been utilized for model optimization to determine instrument parameters, which result in the best chromatographic resolution. Copyright © 2011 John Wiley & Sons, Ltd.