【摘要】：針對污水處理過程出水氨氮(ammonia nitrogen,NH4-N)難以實(shí)時(shí)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(luò)(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(shí)現(xiàn)了出水NH4-N的實(shí)時(shí)檢測。首先,采集和預(yù)處理相關(guān)過程變量的實(shí)際運(yùn)行數(shù)據(jù),通過主元分析法篩選出與出水NH4-N相關(guān)性較強(qiáng)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(guān)參數(shù)進(jìn)行修正。最后,將基于IT2FNN的出水NH4-N軟測量模型應(yīng)用于實(shí)際污水處理過程。實(shí)驗(yàn)結(jié)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(shí)時(shí)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(xué)信息學(xué)部;計(jì)算智能與智能系統(tǒng)北京市重點(diǎn)實(shí)驗(yàn)室;
【基金】：國家自然科學(xué)基金項(xiàng)目(61622301,61533002) 北京市教育委員會科研計(jì)劃項(xiàng)目(KZ201410005002,km201410005001)~~
【分類號】：X832;TP183

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