A study on the activated carbon intelligent dosing system for urban sewage treatment plants based on BP neural network(基于BP神经网络的城镇污水厂活性炭自动投加系统研究)
近年来,活性炭吸附技术逐渐成为深度处理的主流技术,但粉末活性炭投加系统仍处于人工控制阶段,现场需要技术人员依靠经验确定活性炭投加量,易造成出水水质不稳定、活性炭药耗大等问题.以浙江省嘉善县某城镇污水处理厂的深度处理工艺为研究背景,以粉末活性炭投加系统为研究对象,针对活性炭投加控制系统滞后、非线性、复杂等问题,建立了 BP神经网络前馈预测-PID反馈控制的自动投加控制系统.实践证明,该系统具有较强的自适应能力和较高的控制精度,出水COD达标率较人工控制提高了 8.88%,活性炭日均消耗量削减了 16.61%,取得了较好的经济效益....
Main Authors: | FANGRongye(方荣业), SHIYubin(史宇滨), JIANGTing(蒋婷), LIWei(李威), SHIHuixiang(史惠祥) |
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Format: | Article |
Language: | zho |
Published: |
Zhejiang University Press
2018-07-01
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Series: | Zhejiang Daxue xuebao. Lixue ban |
Subjects: | |
Online Access: | https://doi.org/10.3785/j.issn.1008-9497.2018.04.014 |
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