【摘要】：針對污水處理過程出水氨氮(ammonia nitrogen,NH4-N)難以實時檢測的問題,提出了一種基于區(qū)間二型模糊神經(jīng)網(wǎng)絡(interval type-2 fuzzy neural networks,IT2FNN)的軟測量方法,建立了出水NH4-N的軟測量模型,實現(xiàn)了出水NH4-N的實時檢測。首先,采集和預處理相關過程變量的實際運行數(shù)據(jù),通過主元分析法篩選出與出水NH4-N相關性較強的過程變量。其次,利用IT2FNN建立所選變量與出水NH4-N的軟測量模型,通過梯度下降算法對模型相關參數(shù)進行修正。最后,將基于IT2FNN的出水NH4-N軟測量模型應用于實際污水處理過程。實驗結果表明,提出的出水NH4-N軟測量方法不僅能夠?qū)崿F(xiàn)污水處理過程出水NH4-N的實時檢測,而且具有較高的檢測精度。
[Abstract]:In order to solve the problem that it is difficult to detect effluent ammonia nitrogen (ammonia nitrogen,NH4-N) in wastewater treatment process, a soft sensing method based on interval two fuzzy neural network (interval type-2 fuzzy neural networks,IT2FNN) is proposed. The soft sensing model of effluent NH4-N is established, and the real time detection of effluent NH4-N is realized. Firstly, the actual operation data of related process variables are collected and pretreated, and the process variables with strong correlation with effluent NH4-N are screened out by principal component analysis (PCA). Secondly, the soft sensing model of selected variables and effluent NH4-N is established by IT2FNN, and the related parameters of the model are modified by gradient drop algorithm. Finally, the effluent NH4-N soft sensing model based on IT2FNN is applied to the actual sewage treatment process. The experimental results show that the proposed soft sensing method of effluent NH4-N can not only realize the real-time detection of effluent NH4-N in sewage treatment process, but also has high detection accuracy.
【作者單位】： 北京工業(yè)大學信息學部;計算智能與智能系統(tǒng)北京市重點實驗室;
【基金】：國家自然科學基金項目(61622301,61533002) 北京市教育委員會科研計劃項目(KZ201410005002,km201410005001)~~
【分類號】：X832;TP183

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