|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | 基于感知-决策-评估的污水处理智能曝气方法显示文摘作为污水处理的核心工艺,生物曝气环节的稳定性受进水水质、水量等因素的影响较大,且电能消耗高。对曝气过程进行优化控制有利于提高污水处理系统的性能。提出一种基于工况感知-自主决策-性能评估方法的污水处理曝气优化控制策略。将K-means聚类算法与注水原理相结合,对入水数据进行入水工况感知;采用最小二乘支持向量机(LS-SVM)与神经网络反向传播算法(BPNN)建立软测量模型,并结合PSO全局寻优算法求解当前入水的溶解氧浓度优化设定值;将所得曝气池溶解氧浓度优化设定值输入仿真模型中进行性能评估,由仿真评估的结果优化更新工况感知与决策控制部分。经仿真验证,优化系统在出水达标且出水水质与原系统相差不到2%的情况下,经济指标下降10%~15%,节能效果显著。 | 袁沐坤 于广平 刘坚 李健 | 2022 | 工业水处理2022，42，4： | 1 |
| 2 | Fuzzy super-twisting sliding mode control for municipal wastewater nitrification process显示文摘A fuzzy super-twisting algorithm sliding mode controller is developed for the dissolved oxygen concentration in municipal wastewater nitrification process. First, a fuzzy neural network(FNN) model is designed to approach the oxygen dynamics with unmeasurable disturbances, then the established model consists of the nominal system model and the modelling error. Second,based on the FNN model, a super-twisting sliding mode controller is employed to stabilize the nominal system and to suppress the modelling error. Moreover, the stability of the system is investigated and an adaption law is applied to ensure the robustness of the closed-loop system. Finally, the comparison experiments on benchmark simulation model no. 2(BSM2) of wastewater treatment show the advantages of the proposed method in multiple-units oxygen concentration control. | HAN HongGui WANG Tong SUN HaoYuan WU XiaoLong LI Wen QIAO JunFei | 2022 | Science China(Technological Sciences)2022，65，10： | 1 |
| 3 | 城市生活垃圾焚烧过程二次风量智能优化设定方法显示文摘垃圾焚烧过程二次风量通常是依据人工经验设定,具有主观随意性,使污染物排放浓度不达标.针对此问题,提出一种二次风量智能优化设定方法.首先,建立二次风量的案例推理预设定模型、设定值的评价与学习模型;其次,建立工艺指标的随机配置网络预测模型;接着,建立基于径向基神经网络自学习模糊推理的智能补偿模型;最后,将二次风量预设定模型、工艺指标预测模型、智能补偿模型以及设定值的评价与学习模型有机集成,设计二次风量智能优化设定方法的结构与功能,并给出算法实现.采用某垃圾焚烧厂历史数据进行实验,结果表明,所提方法获得的二次风量设定值波动程度更小,按此设定值运行的控制系统可以减少污染物排放浓度,促进垃圾焚烧过程运行优化目标的实现. | 丁晨曦 严爱军 王殿辉 | 2024 | 控制与决策2024，39，1： | 0 |
| 4 | Double-cycle weighted imputation method for wastewater treatment process data with multiple missing patterns显示文摘Due to sensor malfunctions and communication faults,multiple missing patterns frequently happen in wastewater treatment process(WWTP).Nevertheless,the existing missing data imputation works cannot stand multiple missing patterns because they have not sufficiently utilized of data information.In this article,a double-cycle weighted imputation(DCWI)method is proposed to deal with multiple missing patterns by maximizing the utilization of the available information in variables and instances.The proposed DCWI is comprised of two components:a double-cycle-based imputation sorting and a weighted K nearest neighbor-based imputation estimator.First,the double-cycle mechanism,associated with missing variable sorting and missing instance sorting,is applied to direct the missing values imputation.Second,the weighted K nearest neighbor-based imputation estimator is used to acquire the global similar instances and capture the volatility in the local region.The estimator preserves the original data characteristics as much as possible and enhances the imputation accuracy.Finally,experimental results on simulated and real WWTP datasets with non-stationarity and nonlinearity demonstrate that the proposed DCWI produces more accurate imputation results than comparison methods under different missing patterns and missing ratios. | HAN HongGui SUN MeiTing WU XiaoLong LI FangYu | 2022 | Science China(Technological Sciences)2022，65，12： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员