基于FGCN的针铁矿沉铁过程建模

针铁矿沉铁过程是由多个连续反应器级联,并且包含氧化反应、还原反应以及中和反应等一系列复杂化学反应的复杂过程,具有强非线性、不确定性的特点,难以建立精确的数学模型。提出一种基于模糊灰色认知网络(fuzzy gray cognitive network,FGCN)的针铁矿沉铁过程的建模方法。根据专家经验和历史数据,建立针铁矿沉铁系统的模糊灰色认知网络模型,利用带终端约束的非线性Hebbian学习算法(nonlinear Hebbian learning,NHL)对权值进行学习。在不同程度的不确定性环境下对系统进行分析,结果表明模糊灰色认知网络能够在不确定性高的环境下对复杂工业系统进行有效模拟,收敛到一个灰度为零或者灰度很小的灰数平衡点,利用白化函数得到一个准确的控制输出。     

多反应器级联的沉铁过程pH优化控制

针对沉铁过程多反应器级联、离子浓度检测滞后及工况变化频繁导致pH优化控制困难的问题,提出了一种基于多反应器级联的沉铁过程pH优化控制方法。该方法基于入口工况划分与氧气变化量预设定各个级联反应器的pH,并针对影响焙砂添加量的两个主要因素：pH和亚铁离子浓度,建立了基于沉铁过程化学反应机理和物料平衡的焙砂添加量模型;考虑到沉铁过程机理复杂及离子浓度检测滞后影响焙砂的准确添加,引入了氧化还原电位（oxidation-reduction potential,ORP）,并提出一种基于ORP和pH变化量的焙砂模糊修正模型。仿真结果证明了该方法的有效性,为针铁矿法沉铁过程的稳定运行创造了条件。     

多反应器级联的沉铁过程pH优化控制

针对沉铁过程多反应器级联、离子浓度检测滞后及工况变化频繁导致pH优化控制困难的问题,提出了一种基于多反应器级联的沉铁过程pH优化控制方法。该方法基于入口工况划分与氧气变化量预设定各个级联反应器的pH,并针对影响焙砂添加量的两个主要因素:pH和亚铁离子浓度,建立了基于沉铁过程化学反应机理和物料平衡的焙砂添加量模型;考虑到沉铁过程机理复杂及离子浓度检测滞后影响焙砂的准确添加,引入了氧化还原电位(oxidation-reduction potential,ORP),并提出一种基于ORP和pH变化量的焙砂模糊修正模型。仿真结果证明了该方法的有效性,为针铁矿法沉铁过程的稳定运行创造了条件。     

基于参数自整定模糊控制器的沉铁过程pH值稳定控制

针对沉铁过程存在的非线性、强耦合导致溶液pH值难以稳定控制的问题,分析了沉铁过程的工艺及其反应动力学机理。研究了锌焙砂添加量与pH值之间的关系,并根据工艺对pH值的要求,计算沉铁过程所需添加的焙砂量。在此基础上,采用参数自整定模糊控制器对锌焙砂添加量进行补偿调节,从而实现pH值的稳定控制。仿真结果表明：所提出的参数自整定模糊控制器效果良好,为沉铁过程pH值的稳定控制提供了一种切实可行的方法。     

针铁矿促进剩余污泥厌氧消化中的脱氮除碳

剩余污泥厌氧消化因其较低的能源转化率使其发展有所受限,且污泥中高浓度有机质也会影响脱氮效果。理论上,在含铁(Ⅲ)（氢）氧化物的厌氧消化系统中,微生物能通过异化铁还原去除有机物和氨氮（Feammox）,但两者同步去除还有待验证。因此本研究通过向污泥厌氧消化系统中添加针铁矿,探究铁(Ⅲ)（氢）氧化物对同步脱氮除碳的影响。结果显示,随着针铁矿添加量的增加,反应器中有机物浓度逐渐减少。当添加50mmol/L针铁矿时,甲烷累积产量达到695.1mL,相较于没有添加针铁矿的厌氧系统提升了30.3%;TS/VS去除率也提升了21.1%/33.8%,说明针铁矿可有效促进污泥减量化。添加针铁矿的反应器中总氮去除率也有一定提升,当针铁矿添加50mmol/L时,去除率达到21.0%。以上结果表明,添加针铁矿可以在污泥厌氧消化中起到同时脱氮除碳的效果。     

剪切强化针铁矿沉铁过程晶体生长规律研究

采用X射线衍射光谱(XRD)、扫描电子显微镜(SEM)、电感耦合等离子发射光谱法(ICP)等分析方法,考察了ZnSO4-FeSO4体系下剪切强化针铁矿法除铁,在均相成核、异相成核过程中针铁矿渣的晶型结构、微观形貌、元素赋存的变化规律,并于真实溶液中验证剪切强化针铁矿法除铁的规律性。结果表明,剪切强化均相成核,沉铁渣初期无明显的针铁矿晶体特征,均为类圆球状的无定形晶核,渣中铁品位、锌含量波动大,分别由前期43.13wt%和4.57wt%增至57.76wt%和6.12wt%。模拟溶液中,异相成核初期以晶种的二次长大的方式为主,有效避免大量无定形相产生,相比均相成核晶体尺寸更大、结晶度更高,且最终沉铁渣铁品位为58.65wt%,锌含量为5.60wt%。相比模拟溶液,性质复杂的真实溶液针铁矿晶体生长发育更难控制,但能确保以针铁矿晶体析出,且沉铁渣中铁、锌含量分别控制在57.63wt%和5.90wt%。采用工业氧化锌烟尘作为中和剂,得到最终的沉铁渣含铁52.59wt%、含锌6.93wt%。本研究为针铁矿法在工业中的应用与成核方式的选择进一步提供了理论依据。     

模糊神经网络在CO_2汽提塔液位预测中的研究

二氧化碳汽提塔液位系统是一个复杂非线性过程,本文基于一种新型复合型模糊神经网络,对该液位系统的建模和预测进行了研究。仿真实验表明,该网络在复杂非线性过程中具有较好的性能,为实现模糊神经网络在化工生产过程中的应用提供了思路和方法。     

锌冶炼渣浸出模拟液铁沉降试验研究

实验研究了不同反应条件的铁沉降效率及锌、镉损失率。结果表明,氧气做氧化剂pH为3.0~3.5时,反应7 h后,铁沉降效率不高,仅达到34%,锌、镉损失率随反应时间的增加而增加。铁沉降效率随pH及温度的升高而增大,SEM和XRD分析表明,pH为3.0时的沉铁渣中主要成分是针铁矿。     

基于ELM的一类不确定性纯反馈非线性系统的Backstepping自适应控制

针对一类不确定性纯反馈非线性动力学系统,在中值定理、Backstepping控制的基础上,提出一种基于极限学习机（ELM）的自适应神经控制方法。ELM随机确定单隐层前馈网络（SLFNs）的隐含层参数,仅需调整网络的输出权值,能以极快的学习速度获得良好的推广性。在每一步的Backstepping设计中,应用ELM网络对子系统的未知非线性项进行在线逼近,通过Lyapunov稳定性分析设计的权值参数自适应调节律,可以保证闭环非线性系统所有信号半全局最终一致有界,系统的输出收敛于期望轨迹的很小邻域内。将所设计的控制方法应用于化工过程中的连续搅拌反应釜（CSTR）非线性系统实例中,仿真结果表明了控制方法的有效性。     

基于时延挖掘模糊时间认知图的化工过程多变量时序预测方法

模糊认知图(fuzzy cognitive maps, FCM）作为一种复杂系统的建模工具,能够对系统的非线性和不确定性进行处理。由于工业过程变量间往往存在着时间延迟,传统的FCM模型难以处理这类多变量的时间序列数据,建立的预测模型往往不能反映系统内各变量真实的因果关系,从而导致预测结果的解释性差、准确度低等问题。为此,提出了一种时延挖掘模糊时间认知图(time-delay-mining fuzzy time cognitive maps, TM-FTCM),它使用互相关函数(cross-correlation function,CCF)从数据中挖掘时延信息,并通过在推理机制中添加自我影响因子和偏置及优化转换函数等参数,有效地解决了由于工业过程变量间的时延导致的预测模型不准确等问题。通过数值仿真实例及实际化工过程数据,验证了所提方法的有效性。     

Image processing and analysis for determination of concentrations of powder mixtures

The quality of the pharmaceutical powder mixing strongly influences the potency and properties of the tablets. Furthermore, in order to optimize powder mixing processes, fast and accurate methods are sought for determining the concentration of powder mixtures. This work describes an optical method based on an image processing system to determine concentration of powders in a mixture that can be sensed by its gray-level values.The methodology was developed utilizing univariate and multivariate gray image analysis. The effect of difference in mean gray value (DMGV) on the precision and accuracy of the vision system was determined. The results that were obtained from the vision system were compared to those obtained with near-infrared spectroscopy.The multivariate gray image analysis methodology using frequency of each gray-level value (Φ) of gray scale as the independent variables obtained the best predictions. The vision system produced high precision with a standard deviation of about 1.7% w/w and a 2.6% relative standard deviation. The accuracy indicated by the root mean standard error of prediction (RMSEP) was around 1.7% w/w. The mixtures analyzed with the vision system and the near-infrared spectrometer yielded similar results. Analysis of all results confirms that the vision system is an adequate technology for determination of powder mixture concentrations.     

Assessing the sensitivity of modelled estimates of N2O emissions and yield to input uncertainty at a UK cropland experimental site using the DailyDayCent model

Biogeochemical models such as DailyDayCent (DDC) are increasingly used to help quantify the emissions of green-house gasses across different ecosystems and climates. For this use they require parameterisation to represent a heterogeneous region or are site specific and scaled upwards. This requires information on inputs such as climate, soil, land-use and land management. However, each input has an associated uncertainty, which propagates through the model to create an uncertainty in the modelled outputs. To have confidence in model projections, an assessment of how the uncertainty in inputs propagated through the model and its impact on modelled outputs is required. To achieve this, we used a pre-defined uncertainty range of key inputs; temperature, precipitation, clay content, bulk density and soil pH, and performed a sensitivity and uncertainty analysis, using Monte Carlo simulations. This allowed the effect of measurement uncertainty on the modelled annual N₂O emissions and crop yields at the Grange field experimental site to be quantified. Overall the range of model estimates simulated was relatively high and while the model was sensitive to each input parameter, uncertainty was driven by the sensitivity to soil pH. This decreased as the N fertiliser application rate increased, as at lower N application rates the model becomes more sensitive to other drivers of N mineralisation such as soil and climate inputs. Therefore, while our results indicate that DDC can provide a good estimate of annual N₂O emissions and crop yields under UK conditions, reducing the uncertainty in the input parameters will lead to more accurate simulations.     

Analysis and prediction of the width of spreading carbon fiber tow based on gray system theory

This article studied the effects of the speed of spreading fiber and tension of spreading fiber on the width of spreading carbon fiber tow. Based on the single tension of spreading fiber, the univariate gray prediction model GM (1,1) was established, which showed high feasibility and accuracy. Under different tensions of spreading fiber, the intrinsic correlation of the width sequence were analyzed and the multivariate gray prediction model MGM(1,n) was established to predict width of spreading fiber. By transforming the identity of multiple factors in the uncertainty system, it can overcome the limitation that multiple factors develops without keeping same pace. The analysis shows that there is an intrinsic correlation between the widths of spreading fiber tow under different tensions of spreading fiber. Based on the gray correlation degree and the adjacent sequence, the gray prediction model established has high numerical precision. There is good guiding significance for precision optimization in actual production.     

用标度方程预测沥青质沉淀点

研究了用标度方程预测沥青质没淀点的可行性,并将其推广应用至高压注气体系和沉淀剂/溶剂/原油体系。结果表明,对常压正构烷烃体系和高压注气体系,标度方程可以通过较易测定的沥青质沉淀量准确预测较难测定的沥青质的沉淀点;对常压正构烷烃体系的和沉淀剂/溶剂/原油体系,标度方程可通过正构烷烃沥青质沉淀点数据准确预测其它正构烷烃沥青质的沉淀点。     

溶解和离子交换反应中K+的快速测定

离子溶液中快速传递及反应动力学过程的跟踪研究在实验上较为困难 ,为此基于离子选择性电极建立溶液中离子活度即时采集系统 ,并结合活度系数模型准确计算离子浓度 .该方法测定速度快 ,最小间隔为 1s,且所得离子浓度最大偏差小于 2 % .用此方法测定了硫酸钾溶解过程以及钛酸钾离子交换反应过程中钾离子浓度的变化 ,获得传统方法难以测定的数分钟内相关动态过程受溶剂、pH值的影响结果 .该方法可推广应用于研究其他各种动态过程 (如溶解、结晶、沉淀、离子交换、吸附和扩散等过程 )     

The influence of shear forces on clay modification with oppositely charged polyelectrolytes

The interaction between the oppositely charged polymers poly(dimethyldiallylammonium chloride) (PDADMAC) and poly(maleic acid‐co‐styrene) in the presence of clay can be used for strong surface modification. Different methods were applied for characterizing each step of the reaction and the properties of the modified material. By characterizing the formation of the pure polyelectrolyte complex in solution as well as the three component system (two polyelectrolytes in presence of clay) with polyelectrolyte titration and comparing these results with the total carbon content, it was shown that a significant quantity of a soluble, positively charged polyelectrolyte complex is formed in the system. The strong cationic surface charge is obtained by precipitation of this complex on clay. It was found that the conditions of reaction (type of stirrer, time) strongly influence the particle properties like particle size and adsorption behavior/surface charge. The higher surface charge and the greater diameter of particles was obtained with an anchor stirrer, whereas the formation of larger particles and the precipitation of the complex is prevented by the stronger shear forces of the leaf stirrer.     

计算机视觉检测系统在絮凝处理中的应用

絮凝法是废水处理过程中应用最广泛的一种方法。絮凝剂的性质直接影响絮凝效果。作者对计算机视觉检测系统在废水絮凝处理过程中的应用进行了研究。首先介绍了计算机絮凝检测系统的构成及设计原理和方法．然后通过对两种絮凝剂在模拟废水中的絮凝沉淀实验,用计算机视觉检测系统的图像获取功能对絮凝的全过程进行跟踪拍摄,并利用计算机图像处理技术对絮体图像进行分析,找出与絮体沉降特性有关的图形参数．得到絮体图像灰度值与溶液浊度之间的关系曲线,并提出利用絮体图像灰度直方图来判定絮凝沉淀的终点的方法,为絮凝过程的自动化控制提供依据。     

煤灰熔融温度的准确测定

在煤的各项工业分析中,煤灰熔融性是动力用煤和气化用煤的一个重要质量指标,准确测定煤灰熔融性对生产运行十分重要。采用不同的制作煤灰灰锥的方法测定煤灰的熔融性温度。     

Use of gray system theory in product‐color planning

A quantitative evaluation method for the CIE color‐planning activity within the product design cycle is proposed in this article. The questionnaire‐based process that is traditionally employed to obtain objective color psychology tends to be time‐consuming. Accordingly, this study proposes the use of gray system theory to overcome this problem. In the CIE color system, colors are defined by three primary colors, R (red), G (green), and B (blue). Using these three principal hues with fixed equigap sequences to simulate specific basic color samples is an efficient means of investigating unicolor images on a personal computer. However, a gray relational generating operation can be used to simulate colors beyond these basic samples and to predict the corresponding membership values for semantic words. In addition, the gray clustering operation is introduced to predict the overall color image evaluation of multicolored products. The predicted evaluation results of the gray system theory and a back‐propagation neural network are both compared with experimentally verified results. The results indicate that the gray forecasting model is the more effective means of predicting the image evaluation, and therefore, the method is adopted within the color‐planning activity. Although this study takes the example of the Internet‐aided color planning of a baby walker as a case study, the proposed method can also be used on other products. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 222–231, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20009