基于粒子滤波的高浓度染料色泽软测量模型辨识方法

为了解决高浓度混合染料间歇染色过程织物色泽的在线测量问题,即非线性色泽软测量,提出了基于粒子滤波的软测量方法,该方法通过测定间歇染机内染液的吸光度,采用粒子滤波算法来估计该染液中各染料浓度,再根据染料浓度与织物色泽的软测量模型计算出染机内织物色泽。以3种活性染料拼染纯棉为例,对该方法的可行性进行验证。实例证明,基于粒子滤波的软测量方法的色泽估计值与人工离线实测值之间的色差值在1.0 CIELAB之内,模型的估计值能够满足工艺要求。因此,该方法是有效可行的。     

改进的同时测定法测定混合染液各组分浓度

针对常规同时测定法存在测定周期长且对于多峰吸光度曲线不适用的问题,提出一种改进的同时测定法测定混合染液中各组分的浓度。首先运用高斯逼近法拟合固定浓度下各单一染液的吸光度、波长的模型。然后根据朗伯-比尔定律推导出各单一染液的吸光度、波长与浓度的模型,并给出了求混合染液各组分含量的具体步骤。最后以3种活性染料的混合染液浓度测定说明算法的可行性和有效性。     

初始状态不确定的非线性过程系统状态估计的鲁棒粒子滤波方法

在过程系统的控制与故障检测等方面,状态估计发挥着重要作用。针对非线性过程系统状态估计过程中初始状态不确定性问题,提出一种鲁棒粒子滤波方法。该方法首先引入初始状态准确性间接判定准则,根据判定的结果来选择是否进行基于观测偏差反馈机制的初始状态迭代改进。初始值准确性较差时,可以通过初始状态迭代改进策略使最终的初始粒子更接近真实的初始状态,从而增加产生初始粒子的正确性概率,通过粒子滤波迭代得到更准确的状态估计结果。将提出的鲁棒粒子滤波方法与传统粒子滤波方法应用于两个非线性动态系统实例中,结果验证了所提出方法的有效性与鲁棒性。     

一种光度法测定双组分染料浓度的方法研究

采用光度法测定了含有曙红和桃红的混合染料的吸光度,并用最小二乘法计算两种染料的浓度。用分光光度计测定曙红和桃红的最大吸收峰,然后确定不同浓度的曙红溶液和桃红溶液的吸光度,绘制标准曲线并进行拟合,得到拟合方程。最后测定含曙红和桃红的混合染料的吸光度,由回归系数最小二乘估计法得到最大吸收波长处的吸光度-浓度方程,计算出两种染料的浓度,回收率在98%¹02%之间。该法具有快速、简捷实用等特点。{A514.5合成样=(1.097×10-1c曙红-7.000×10-4)+(4.860×10-2c桃红-2.200×10-3)A534合成样=(2.790×10-2c曙红+6.000×10-4)+(9.320×10-2c桃红+4.900×10-3)     

粒子滤波在复合材料容器损伤中的应用

介绍了声发射检测技术和粒子滤波的理论,通过粒子滤波算法,对复合材料压力容器损伤的声发射信号进行了分析并运用FPI准则进行声发射信号AR模型阶数的确定,建立了粒子滤波模型对信号进行消噪处理,提高了信噪比。     

测定双组分染料浓度的两种方法比较

对测定双组分染液中染料浓度的分光光度法进行了研究.介绍了利用解联立方程组和双波长法测试的原理和方法,对测试结果进行了分析、验证.实验表明,这两种方法测定双组分混合染料中染料含量,准确度较高,方法简单,具有一定的推广应用价值.     

非线性最优滤波采样计算方法述评

基于贝叶斯估计理论基础,从减小最优滤波算法计算量、提高计算效率的角度综述了GaussHermite滤波、扩展Kalman滤波、Sigma点Kalman滤波算法中的确定性采样计算方法以及粒子滤波算法中随机样本点粒子计算方法,指出:针对粒子滤波算法中采样函数设计、重采样技术、高斯近似法与粒子滤波法的有效融合来设计研究新型高效高精度粒子最优滤波算法,将成为未来Bayesian最优滤波理论方法研究的重要领域和发展方向,而构建区间粒子最优滤波理论算法不失为粒子滤波理论算法研究的新思路.     

干法腈纶短纤维上色率测定方法探讨

对腈纶上色率国标测定方法中染液的配制方法和染前、染后吸光度测定的染液稀释倍数问题进行了探讨,对检验数据进行了统计分析,提出了适合干法腈纶上色率测定的改进方法,提高了分析结果的准确度。     

模型有界失配下基于MAP准则的扩展集员粒子滤波方法

在非线性非高斯系统中,当状态转移模型存在有界失配时,采用粒子滤波往往无法获得理想的状态估计值。考虑有界失配对粒子的约束条件,提出一种基于MAP准则的扩展集员粒子滤波算法（MAP-ESMPF）。该算法采用扩展集员求取真实状态的可信域,并基于MAP密度函数的准则,定义优化方程,从而将可信域外的粒子映射到可信域内,保证了状态估计的精度。在数值仿真和连续搅拌反应釜（CSTR）过程中的仿真应用,验证了该算法的有效性。     

聚酰胺微胶囊缓释动力学性能的影响

通过对染料微胶囊缓释性能进行定量研究,制备出一种环保型分散染料微胶囊。文中使用紫外-可见分光光度计测定分散染料微胶囊中染料扩散到丙酮溶液中的吸光度,并通过非线性函数方程Boxlucasl对实验数据进行拟合,建立了与微胶囊缓释性能规律相适应的数学模型。通过对这一模型的分析,得到制备过程工艺条件对聚酰胺分散染料微胶囊缓释性能的影响规律,并得到制作环保型分散染料微胶囊所需要的条件。     

基于Unscented卡尔曼滤波器的管道泄漏的快速检测与定位

针对扩展卡尔曼滤波器(EKF)对非线性模型进行状态估计时,需要将非线性模型进行线性化,而天然气管道模型的非线性程度十分严重的情况,提出一种基于无偏卡尔曼滤波器(UKF)估计的管道泄漏检测与定位方法.该方法是一类用采样策略逼近非线性模型的方法,避免了线性化,并且不需要计算Jacob矩阵,UKF的收敛速度明显优于EKF,能够快速地检测出泄漏.仿真结果说明UKF在泄漏检测中相对于EKF的优势.     

Extended and unscented kalman filters for artificial neural network modelling of a nonlinear dynamical system

Recently, artificial neural networks, especially feedforward neural networks, have been widely used for the identification and control of nonlinear dynamical systems. However, the determination of a suitable set of structural and learning parameter value of the feed-forward neural networks still remains a difficult task. This paper is concerned with the use of extended Kalman filter and unscented Kalman filter based feedforward neural networks training algorithms. The comparisons of the performances of both algorithms are discussed and illustrated using a simulated example. The simulation results show that in terms of mean squared errors, unscented Kalman filter algorithm is superior to the extended Kalman filter and back-propagation algorithms since there are improvements between 2.45?C21.48% (for training) and 8.35?C29.15% (for testing). This indicates that unscented Kalman filter based feedforward neural networks learning could be a good alternative in artificial neural network models based applications for nonlinear dynamical systems.     

Determination of colour sensitivity of dye mixtures for disperse dyes

A method has been developed to quantify the colour sensitivity of a dye mixture. In this method, the concept of the colour sensitivity of matching recipes has been developed so that it covers variations, not only in dye concentrations, but also in dyeing parameters. Firstly, the 'individual colour sensitivity' of a dye mixture to a specific dyeing parameter was quantified by comparing the colour difference between the resulting shade from a normal dyeing condition and that produced by giving a change to the parameter. These resultant data were used to calculate the total colour sensitivity covering the factors, temperature, time and liquor ratio, with a model established based on CMC(2:1) equation. This calculated result simulates the reproducibility of a dye mixture in the dyeing application under certain accuracy of the dyeing process control. A set of dye recipes was applied by dyeing to verify the calculation with disperse dyes on polyester.     

Remaining useful life prediction of lithium-ion battery based on an improved particle filter algorithm

Because lithium-ion batteries are the main power source of industrial electronic equipment, their degradation process modelling and remaining useful life (RUL) prediction problems have attracted wide attention. The particle filter (PF) method has been successfully applied to suppress the model uncertainty and predict the RUL of the lithium-ion battery. In order to further enhance the stability of the PF method and realize a more satisfactory prediction result, a RUL prediction method based on the hybrid algorithm, which combines the PF algorithm and extended unbiased finite impulse response (EFIR) filter, is proposed. Firstly, the state space model of capacity degradation for the lithium-ion battery is established, and the model parameters are estimated by the extended Kalman filter (EKF) algorithm. Secondly, a preliminary battery capacity is predicted by using a regularized particle filter. The preliminary predictions with large deviations are diagnosed and repaired by combining the EFIR filter and diagnostic strategy. Finally, the optimized RUL prediction results of the lithium-ion battery are extrapolated based on the failure threshold. The experiment results demonstrate that the proposed method has good stability and accuracy in predicting the RUL of a lithium-ion battery.     

Prediction of dye concentrations in a three‐component dye mixture solution by a PCA‐derivative spectrophotometry technique

Derivative spectrophotometry is one of the most important techniques that can be used to determine the dye concentration. In addition, principal component analysis (PCA) is a linear method to condense the dimensionality of large numbers of absorbance spectra. In this work, PCA and derivative spectrophotometry techniques are used to improve the accuracy of Beer's law prediction of the concentrations in three‐component dye mixtures. The performance of the new method is compared with the normal Beer's law by calculation absolute error, relative error, and ternary relative error of prediction. As obtained results indicate, the prediction accuracy of dye concentration prediction in PCA‐derivative spectrophotometry method is higher than normal Beer's law method. © 2009 Wiley Periodicals, Inc., Col Res Appl, 2010.     

基于自适应EKF算法的输出融合软仪表设计

在化工过程中,作为观测关键质量参数的重要手段,软仪表技术受到了广泛的关注。目前,关于软仪表的研究主要集中在建模技术上。然而,化工过程复杂多样,仅使用软测量模型进行质量变量的估计易出现预估效果不稳定、随机偏差大等现象。为此,文献提出了一系列的改进算法,但仍存在计算复杂、算法抗干扰能力差等问题。本文提出一种基于自适应扩展Kalman滤波(EKF)的输出融合软仪表设计方法,利用Kalman滤波算法对软测量模型预估数据和现场观测进行数据融合,校正软测量模型预估偏差;并在输出融合软仪表背景下,设计了一种含衰减因子的观测噪声统计估计器,将其与滤波算法相结合,构成自适应EKF算法,以提高融合软仪表的输出精度及抗干扰性能。通过仿真实验对所提出的算法进行了全面分析,并将该算法应用于小型实验装置,验证了算法的实用性及有效性。     

Property evaluation and control in a semibatch MMA/MA solution copolymerization reactor

This article deals with the property control of polymer product in a semibatch MMA/MA copolymerization reactor by applying the extended Kalman filter (EKF) based nonlinear model predictive control (MPC). In addition to the feeding of the more reactive monomer, the solvent is continuously supplied so as to maintain the viscosity of the reaction mixture within a reasonable range. This measure then provides favorable conditions not only for the on-line estimation with the EKF but also for the performance of the EKF based nonlinear MPC. Indeed, the improved performance of the state estimator is confirmed by experiment under isothermal and nonisothermal conditions over a prolonged reaction time. On the basis of the estimated state, the EKF based nonlinear MPC is implemented to the semibatch reactor to produce copolymers with desired properties. The experimental results clearly demonstrate the superiority of the present control strategy compared to the result of our previous work obtained without having additional feed of solvent.     

延迟焦化加热炉热效率的机理建模与实时估计应用

在延迟焦化装置中，焦化炉热效率是操作先进性关键评价指标，然而实际工业生产中难以在线测得加热炉热效率。本文基于机理建模，推导了管式加热炉状态空间预测模型。为降低干扰影响，提出了一种基于粒子滤波的联合估计方法来修正加热炉热效率模型预测，并分析了其收敛性。实际应用结果证实了所提方法的可行性和有效性，为实现延迟焦化装置先进控制奠定了基础。