四氯化碳生产中氯化反应的回火原因分析与对策

探讨了四氯化碳生产中氯化反应的回火原因及避免回火的对策 ,解决了生产中的实际问题     

热光双稳态的临界入射功率与临界温升

本文考虑到F—P腔夹层介质和后反射镜均具有一定的吸收时,推导出产生热致色散光学双稳态的临界入射光功率P_c和临界温升△T_c的数学解析表达式。理论计算的 △T_c值与实验值非常符合。为了得到最佳光学双稳态回线和避免腔内的纵向温度梯度,夹层介质和后反射镜应具有一定的匹配吸收。     

Selection of optimized features for fusion of palm print and finger knuckle‐based person authentication

The impact of digital technology in biometrics is much more efficient at interpreting data than humans, which results in completely replacement of manual identification procedures in forensic science. Because the single modality‐based biometric frameworks limit performance in terms of accuracy and anti‐spoofing capabilities due to the presence of low quality data, therefore, information fusion of more than one biometric characteristic in pursuit of high recognition results can be beneficial. In this article, we present a multimodal biometric system based on information fusion of palm print and finger knuckle traits, which are least associated to any criminal investigation as evidence yet. The proposed multimodal biometric system might be useful to identify the suspects in case of physical beating or kidnapping and establish supportive scientific evidences, when no fingerprint or face information is present in photographs. The first step in our work is data preprocessing, in which region of interest of palm and finger knuckle images have been extracted. To minimize nonuniform illumination effects, we first normalize the detected circular palm or finger knuckle and then apply line ordinal pattern (LOP)‐based encoding scheme for texture enrichment. The nondecimated quaternion wavelet provides denser feature representation at multiple scales and orientations when extracted over proposed LOP encoding and increases the discrimination power of line and ridge features. To best of our knowledge, this first attempt is a combination of backtracking search algorithm and 2D²LDA has been employed to select the dominant palm and knuckle features for classification. The classifiers output for two modalities are combined at unsupervised rank level fusion rule through Borda count method, which shows an increase in performance in terms of recognition and verification, that is, 100% (correct recognition rate), 0.26% (equal error rate), 3.52 (discriminative index), and 1,262 m (speed).     

Design of robotic visual servo control based on neural network and genetic algorithm

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP algorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.     

低碳钢显微结构的EBSD表征

近年来,新开发的电子背散射衍射技术将多晶材料的显微组织、微区成分与结晶学数据分析联系起来,能对晶界类型、取向、位向差和结构及其分布进行观察、统计测定和定量分析,从而建立了晶界结构、取向和织构等与多晶材料性能的定量和半定量关系,成为现代材料研究的重要实验技术。笔者结合低碳钢生产中的一些实际问题,扼要介绍了电子背散射衍射技术中的晶体取向图在多晶材料显微结构表征中的应用。     

基于MODWT和BP神经网络的微电网故障诊断方法

近年来,随着微电网技术的持续发展,电力用户对其供电可靠性的要求也不断提高,因此微电网故障诊断研究也变得越来越重要。提出了一种基于极大重叠离散小波变换(MODWT)和反向传播(BP)神经网络的微电网故障诊断新方法,并通过仿真与算例进行了验证。结果表明:该方法能快速、准确地识别出故障类型,且不受故障初始相位角和过渡电阻等因素的影响;与现有的基于离散小波变换和反向传播神经网络的诊断方法相比所提出的方法可以提供更好的故障分类精度。     

带材的纠偏控制

本文对带钢生产线上常见的带材跑偏现象，进行了详细的分析。对带钢跑偏的原因，进行了研究。同时，对带钢跑偏应采取的措施，也给出了相应的方法。     

高压粉末制样-X射线荧光光谱法测定海洋沉积物中28种组分

常规粉末压片制样是一种简单、高效的绿色环保制样技术,但是应用于某些沉积物样品制备存在样片表面粗糙和粉末容易脱落的问题。实验采用高于常规的压力进行样品制备,建立了X射线荧光光谱法(XRF)分析海洋沉积物样品中包括硫、氧化钠、氧化镁、三氧化二铝、二氧化硅、五氧化二磷、氧化钾、氧化钙、二氧化钛、氧化锰、三氧化二铁、钴、镍、铜、锌、钒、铬、镓、铌、锆、钇、锶、铷、铅、钡、镧、钕和铪在内的28种主、微量组分的方法。探讨了压力为300 kN和1 600 kN时的制样效果,并尝试引入BP神经网络模型利用其非线性拟合能力校正主量组分的基体效应。结果表明,采用1 600 kN压力制备的样片,表面致密、光滑、不龟裂和不掉粉,制样重复性和测试精密度也有较大提高。以55个有证标准物质中17种组分的数据集为训练样本,建立了海洋沉积物样品中主、微量组分的遗传算法-BP神经网络预测模型。按照实验方法对各组分含量相对较低的实际样品连续测试12次,计算得方法的检出限在 0.63～634 μg/g之间;精密度试验结果表明,各组分测定值的相对标准偏差(RSD, n=7)为0.16%～25.1%。方法用于海洋沉积物实际样品分析,其分析结果与国标法的测定结果吻合,能够满足海洋沉积物样品中多种组分准确分析的要求。     

电机铁芯冲片模冲槽废料回跳问题分析与解决

分析了电机铁芯冲片上嵌线槽在高速冲制过程中废料回弹的原因 ,并从凸、凹模结构形式及润滑油的使用等方面介绍了解决废料回弹的方法。     

水下隧道穿越管道保护效果测试评价

本文通过对四川气田北干线涪江隧道穿越管道阴极保护电参数的现场测试，取得了实际可信的基础数据，验证了处于水下隧道洞内的穿越段管道，能得到陆上强制电流阴极保护系统的有效保护，保护电流所必经的岩石层和锚喷钢筋混凝土层对保护电流没有构成屏蔽的结论，对管道工程设计和运行管理具有指导作用。