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针对电站锅炉烟气含氧量传统硬件测量方法成本昂贵、使用寿命短等缺陷,提出一种基于支持向量机的软测量方法。首先结合机理分析和数据相关性分析选取相关过程参数作为模型输入参数,使用遗传算法对支持向量机进行参数寻优,构建基于遗传算法参数优化的支持向量机(GA-SVM)软测量模型。实验结果表明:该模型能较好地反映烟气含氧量的变化趋势。 相似文献
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研究时间序列在水泥回转窑中的建模问题,水泥回转窑熟料的煅烧是一个涉及物理、化学反应的复杂多变量、多扰动非线性过程.针对最小二乘在多参数高阶时间序列模型中难以寻找到较好的系数组,从而不能建立较精确的时间序列模型的情况,采用传统遗传算法也很难寻找出最优参数组,当利用多岛遗传算法对其进行参数寻优时,只要适当地设置算法里的一些关键参数即能得出满意的组解.实验结果表明:经过多岛遗传算法寻优得出的参数建立的时间序列模型,其拟合度满足模型曲线的精度要求. 相似文献
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乙烯生产装置遗传网络模型的建立 总被引:3,自引:0,他引:3
王景芳 《化工自动化及仪表》2005,32(5):18-20
建立一种乙烯生产装置人工神经网络模型结构,设计一种遗传算法进行该模型参数的组合优化建模。示例表明:建好后的网络模型可对乙烯生产装置进行快速工艺参数优化,获得较优的操作数据。 相似文献
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运用改进的遗传算法估计发酵动力学模型参数 总被引:4,自引:0,他引:4
针对简单遗传算法(SGA)存在早熟,寻优效率偏低等缺点,提出了一种改进的遗传算法,并将它用于发酵动力学模型参数的估计,取得了满意的效果。 相似文献
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非线性动态液位软测量模型建立 总被引:3,自引:0,他引:3
王景芳 《化工自动化及仪表》2006,33(1):32-34
设计一种具有高度非线性逼近能力的人工神经网络模型结构,以遗传算法进行该模型参数的组合优化建模,解决连续搅拌反应釜动态液位测量问题. 相似文献
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基于微生物发酵动力学模型和丙酮丁醇发酵工艺的特点,由5组控制pH下的实验数据建立该发酵过程的动力学模型,采用改进的自适应遗传算法对模型的12个参数进行优化,并采用一组控制pH数据对模型进行了外推验证,结果表明,该模型能够较好地描述pH的丙酮丁醇间歇发酵过程. 相似文献
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为考虑发酵过程的质量变量和动态特征对于阶段划分的影响,提出了一种基于联合典型变量矩阵的多阶段发酵过程质量相关故障监测方法。首先,将历史三维数据沿批次方向展开,对每个时间片矩阵进行典型相关分析(canonical correlation analysis, CCA),得到融合过程变量和质量变量信息的联合典型变量矩阵,对其进行K均值聚类,实现基于静态特征的第1步划分;然后采用慢特征分析(slow feature analysis, SFA)算法提取表征过程动态性的慢特征,对其进行聚类实现第2步划分。最后综合分析两步划分结果,将生产过程划分为不同的稳定阶段和过渡阶段,并在划分的子阶段中分别建立CCA监测模型进行质量相关故障监测。该方法通过静态和动态特征的变化实现两步划分,准确区分强动态变化与阶段切换,有效提高质量相关的故障监测模型精度。青霉素仿真平台与大肠杆菌实际生产数据验证了所提方法的可行性和有效性。 相似文献
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本文研究了游离细胞连续发酵时应用 CO_2气提、活性炭吸附的乙醇发酵和分离动力学,考察了稀释率和进口葡萄糖浓度对发酵速率的影响,提出了包括 CO_2汽提乙醇速率的发酵动力学模型,研究了连续发酵时的稳态和动态过程,结果表明,CO_2气提有助于减少乙醇对酵母的抑制作用,发酵动力学模型可以较好地关联稳态时的发酵动力学数据,从中获得的模型参数可以用于预测动态过程中底物、微生物及产物的变化规律。对于所研究的过程,存在着最佳稀释率和进口糖浓度以获得最大发酵速率。 相似文献
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Multivariate statistical process monitoring methods are often used in chemical process fault diagnosis. In this article,(I) the cycle temporal algorithm(CTA) combined with the dynamic kernel principal component analysis(DKPCA) and the multiway dynamic kernel principal component analysis(MDKPCA) fault detection algorithms are proposed, which are used for continuous and batch process fault detections,respectively. In addition,(II) a fault variable identification model based on reconstructed-based ... 相似文献
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青霉素发酵过程具有较强的非线性、时变性、阶段性和不确定性,基于单一的软测量模型对产物浓度进行在线估计,难以满足系统对模型精度的要求。针对上述问题,提出一种改进密度峰值聚类的多模型软测量建模方法来估计青霉素发酵过程中的产物浓度。首先,引入相似度函数代替欧氏距离计算样本点的k近邻,并且计算样本点与其k近邻之间的共享近邻,进而利用样本点的k近邻及共享近邻重新定义样本点的局部密度。其次,利用样本点之间的k近邻关系来重新定义样本点的分配策略;通过改进的聚类算法得到各聚类子集,分别建立基于最小二乘支持向量机的软测量模型。Pensim仿真平台的验证结果表明,改进的聚类算法能够更加准确地对样本数据进行聚类,从而有效提高青霉素发酵过程软测量模型的估计精度。 相似文献
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On-line estimation of unmeasurable biological variables is important in fermentation processes, directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product. In this study, a novel strategy for state estimation of fed-batch fermentation process is proposed. By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model, a state space model is developed. An improved algorithm, swarm energy conservation particle swarm optimization (SECPSO), is presented for the parameter identification in the mechanistic model, and the support vector machines (SVM) method is adopted to establish the nonlinear measurement model. The unscented Kalman filter (UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process. The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process. 相似文献
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A dynamic model for a continuous extractive fermentation process is proposed. Using this model and the Iterative Dynamic Programming algorithm, optimal operating profiles are identified for process start-up from conventional fermentation operation. Under the optimal operating profile, profit during the transient operation accumulates at a rate approaching that of steady state operation. A sensitivity analysis investigating the effect of economic variations on the overall profit function shows that optimization of manipulated variable profiles primarily reduces the impact of substrate cost, so that the profit function approaches a linear function of the product value. 相似文献
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An adaptive control algorithm with rule-bases was developed for cell recycled continuous bioreactor. Ethanol fermentation
bySaccharomyces cerevisiae was used as a model system. Since the developed algorithm employed the fermentation model, it was possible to estimate the
physical state of the system. Five rule-bases were obtained from the experiments and used to adjust the control input. Good
control performance was observed using a rule-based STR (self-tuning regulator) compared to the result using conventional
STR. When disturbances were given, rule-based adaptive control scheme showed faster recovery of setpoint. The rule-based STR
developed in this study was stable, robust and showed good tracking performance. 相似文献
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The dynamic soft sensor based on a single Gaussian process regression (GPR) model has been developed in fermentation processes.However,limitations of single regression models,for multiphase/multimode fermentation processes,may result in large prediction errors and complexity of the soft sensor.Therefore,a dynamic soft sensor based on Gaussian mixture regression (GMR) was proposed to overcome the problems.Two structure parameters,the number of Gaussian components and the order of the model,are crucial to the soft sensor model.To achieve a simple and effective soft sensor,an iterative strategy was proposed to optimize the two structure parameters synchronously.For the aim of comparisons,the proposed dynamic GMR soft sensor and the existing dynamic GPR soft sensor were both investigated to estimate biomass concentration in a Penicillin simulation process and an industrial Erythromycin fermentation process.Results show that the proposed dynamic GMR soft sensor has higher prediction accuracy and is more suitable for dynamic multiphase/multimode fermentation processes. 相似文献