【作者】 张青；

【导师】 刘俊良；

【作者基本信息】 河北农业大学 ， 环境科学， 2013， 硕士

【摘要】 在全球水资源严重短缺的大背景下，水资源的循环利用已成为解决当前水资源危机的重要途径之一。城镇污水处理厂出水作为城市的第二水源，不仅水量稳定，而且具有很好的经济效益。随着我国十二五规划“节能减排”工作的深入开展，公众普遍关注的是污水处理厂的稳定运行及出水水质达标问题。2005年10月，国家环境保护总局向各省、自治区、直辖市环境保护局下发了关于执行《城镇污水处理厂污染物排放标准》的通知文件（环发〔2005〕110号）：北方缺水地区应执行中水回用，为防止水域发生富营养化，城镇生活污水处理厂出水排入国家和省确定的重点流域及湖泊、水库等封闭式、半封闭水域时，应执行《标准》中一级A标准；其他地区可执行《标准》中的二级标准，并可根据当地实际情况，逐步提高污水排放的控制要求。在对华北某城镇污水处理厂进行调研的基础上，分析该厂二沉池出水水质，采用曝气生物滤工艺对其尾水进行深度处理，由于出水水质浓度较低，故采用活性污泥接种挂膜法；后续采用Math Work公司提供的MATLAB7.0作为数值计算平台，运用BP人工神经网络工具箱，建立进水参数与出水指标的映射模型，以期为在线监控提供理论指导和生产经验。试验分为两个部分：第一部分，研究上向流曝气生物滤池处理低浓度二沉池出水效果。通过设定不同水力停留时间——1h、1.8h、2.5h、3.5h，不同气水比——1.5:1、2.5:1、3:1、3.5:1，不同温度——5¹4℃、15²0℃、21²9℃，综合对比反应器对污染物的去除效果，确定该系统最佳工艺参数为：水力停留时间2.5h、气水比3:1、温度在20℃以上。最优工艺参数条件下，系统对CODcr、NH₃-N、SS平均去除率分别为35.2%、57.2%、57.9%；出水平均浓度分别为43.0mg/L、4.1mg/L、5.6NTU。出水CODcr、NH₃-N、SS值均能满足《污水综合排放标准》（GB18918-2002）中一级A标准的要求，达到污水深度处理的目的。第二部分，基于BP神经网络的二级出水仿真研究。调整曝气生物滤池处于最佳工艺参数，选取连续监测运行的数据，以X=[T，CODcr，SS，NH₃-N，MLSS，DO]作为输入向量，Y=[CODcr，NH₃-N，SS]作为输出向量，运用BP人工神经网络工具箱，建立了BAF工艺出水CODcr、NH₃-N、SS的仿真模型，同时对仿真拟合值和实际值进行验证，当输入层神经元为6，隐含层神经元为11，输出层神经元为3，学习速率0.01，训练次数5000时，预测出水CODcr浓度最大相对误差为0.95%，MARE为0.58%；预测出水NH₃-N浓度最大相对误差为5.8%，MARE为2.8%；预测出水SS浓度最大相对误差为7.7%，MARE为5.3%。三个指标预测值与实际值的平均相对误差基本在5%以下，可以达到较好的预测精度。最后，通过权重分析，探究了各影响因素对出水参数的权重贡献，对出水CODcr预测模型，权重贡献依次为：DO>T>CODcr>MLSS>NH₃-N>SS；对出水NH₃-N模型，权重贡献依次为：T>NH₃-N>DO>CODcr>SS>MLSS；对出水SS模型，依次为：SS>MLSS>DO>NH₃-N>CODcr>T。DO、T占据权重贡献主要地位，这也与第一部分试验证明相吻合。前期试验工艺为城镇污水厂进行深度处理，未来提升出水水质，提供生产实际经验；后期仿真研究是在基于BAF的最优工况下，提供了一种预测出水水质的方法，为指导污水处理厂正常运行，实现尾水达标排放提供了决策依据。更多还原

【Abstract】 In the background of the global water shortage, water recycling has become oneof the important ways to solve the current water crisis. The effluent of the townsewage treatment plant as the second water resource of cities，which is not only thewater stability，but also very good economic benefits. With the work thoroughdevelopment of China’s the12th five-year plan "energy conservation and emissionsreduction”, the public is of common concern on the stable operation of sewagetreatment plant and water quality standards. In October2005, the state environmentalprotection administration of the provinces, autonomous regions and municipalitiesdirectly under the environmental protection agency issued a about the implementationof the urban sewage treatment plant pollutant discharge standard "notification file（environment and development[2005]no.110）:In order to prevent water eutrophication,urban sewage treatment plant effluent discharged into the national and provincial keyriver valleys and lakes, reservoirs, determining the closed, semi-closed waters, itshould carry out the level of A standard; in other regions, it can be performed level oftwo standards, and according to the local actual situation, gradually increasing of therequirements. of sewage discharge.Based on the investigation to the north of a town sewage treatment plant,analysis of two effluent water quality of the plant, using biological aerated filterprocess for advanced treatment of tail water. Because the water quality of lowconcentration, so use of activated sludge and biofilm method; Follow-up by MathWork’s MATLAB7.0as the numerical platform, using BP neural network toolbox,establish the mapping model of inlet parameters and indicators of water, in order toprovide theoretical guidance and production experience for the online monitoring.Follow-up by Math Work’s MATLAB7.0as the numerical platform, using BP neuralnetwork toolbox, establish the mapping model of inlet parameters and indicators ofwater, in order to provide theoretical guidance and production experience for theonline monitoring.The experiment consists of two parts. The first part: study on biologicalaerated filter to process two effluent effect of low concentration. By setting different hydraulic retention time-1H,1.8h,2.5h,3.5H, different ratio of gas andwater-1.5:1,2.5:1,3:1,3.5:1, different temperature5¹4℃、15²0℃、21²9℃,comprehensive comparison of the pollutant removal efficiency，to determine theoptimum process parameters of the system:Hydraulic retention time2.5h, the ratio of gas and water3:1, temperature above20℃. Under the optimal process parameters，the average removal rate of CODcr、NH₃-N and SS were35.2%、57.2%、57.9%;average effluent concentrations were43.0mg/L,4.1mg/L,5.6NTU.The effluent CODcr, NH₃-N, SS value can meet the "integrated wastewater discharge standard"（GB18918-2002） in a class A standards,to achieve the purpose ofd eep treatment of wastewater. The two part: simulation of secondary effluent based on BP neural network. Adjust aeration biological filter at the optimum technological parameters, selection of continuous monitoring operation data, X=[T,CODcr, SS, NH₃-N, MLSS, DO] as the input vector, Y=[CODcr, NH₃-N,SS]as the output vector. Application of BP artificial neural network toolbox,the effluent model of BAF process was established，at the same time, the simulationvalue and the actual value was verified. When input layer neurons is6, the hidden layer neurons11, output layer neurons3,learning rate0.01,training number5000,the maximum relative error for predicting effluent CODcr concentrationwas0.95%,the MARE was0.58%;the maximum relative error for predicting effluent NH₃-N concentration was5.8%,the MARE was2.8%; the maximum relative error for predicting effluent SS concentration was7.7%,the MARE was5.3%.The average relative error below for predicted value and actual valueof three indexes were under5%,so the method could be achieved better prediction accuracy.Finally,by weight analysis, it was explored the weight contribution of each factor. For prediction model of effluent CODcr, followed by:DO>T>CODcr>MLSS>NH₃-N>SS;for prediction model of effluent NH₃-N, followed by:T>NH₃-N>DO>CODcr>SS>MLSS; for prediction model of effluent SS,followedby:SS>MLSS>DO>NH₃-N>CODcr>T.DO and T occupied the main position of weightcontribution,which is consistent with the experimental results of first part.Preliminary test technology provided the production practical experience fordeep treatment of urban sewage plant and improving effluent water quality in thefuture; the latter simulation study was based on optimum conditions of the BAF, itprovided a method to predict the effluent quality for guiding normal operation ofsewage treatment plant, and provided a decision-making basis for realizing of tailwater discharging standards.更多还原