【作者】 董丽华；

【导师】 赵新华；

【作者基本信息】 天津大学 ， 环境工程， 2004， 硕士

【摘要】 管网中的细菌再生长及其所带来的问题日益得到了人们的关注和重视,本文以某高校校园管网为研究对象,系统、深入的研究了配水管中细菌再生长现象的预测及其控制措施。在对细菌再生长的机理及影响因素分析的基础上,并结合水质测定的需求,制定了校园管网的水质监测方案。为了解微生物指标的潜在生长趋势,本文创新性的将细菌总数和大肠杆菌的培养时间延长为72小时。通过对十个监测点长时间连续取样、检测和分析研究,取得了大量的水质资料,对管网水质有了一定的了解,同时对个水质指标与细菌再生长的相关关系也有了定性的认识。通过对因变量自身及各种统计分析方法的使用条件进行分析,选用线性回归和Logistic回归进行预测,然而前者结果并不理想。然后创新性的选用Logistic回归模型并结合主成分分析法对细菌总数(HPC)这一二分变量的超标概率进行预测。该模型是运用SAS统计软件的Analysis模块来实现的。首先,运用Logistic回归的逐步选择法对原变量进行回归,得到了一个单变量(仅含铁)的预测模型。在将模型判别概率设为0.5或0.85时,其预测精度均在90%以上。为消除各个指标之间的共线性,又对原变量进行主成分分析,以分析得到的前几个主成分为自变量建立了主成分Logistic回归预测模型。与前一模型比较该模型更能体现细菌再生长的机理,预测精度也令人满意,都在90%以上。但两者都可以应用于实际,且效果较好。视具体情况,恰当的选择上述两个模型,对细菌超标的概率做出准确的预测,就能够更精确的指导实践,从而达到水质预警的作用。最后,指出了配水管网水质预测的必要性,并结合细菌再生长现象产生的原因,从提高水处理措施、控制管道腐蚀、冲洗管网以及加强管网二次供水设施的管理等方面提出输配管网细菌再生长的控制措施,更多还原

【Abstract】 Because the disadvantage result of bacterial regrowth,people have been began toconcern about the regrowth of bacteria in water distribution system.An example ofTianjin University distribution system,the paper studied the problem of bacterialregrowth and restraining measures in detail.Based on the analysis of the mechanism and influencing fators of bacterialregrowth, we established the testing scheme. In order to learn the potential trend ofgrowth,the paper extend the culture time of HPC and coliform to 72hr.After thecontinuous sampling and analysis,we obtained a lot of the data about the water qualityand knowed the water quality and the correlation among the water quality data.By analyzing characteristics of response variable and the applying conditions ofstatistical methods,the paper chose linear regression and Logistic Regression model.Itturned out that the former didn’t achieve a real result.The Logistic Regression is fit forthe two level Response Variable (HPC) which is achieved by the SAS statisticalsoftware. Firstly, regarding primary water quality data as the explanatory variables,gain a single viable model (only including Fe) by the stepwise selection,which has aexcess precision of 90% when the determinant probability is supposed 0.5 or 0.85.Inorder to eliminate the co-linearity among water qualities, the paper applied thePrincipal Components Analysis(PCA) to the primary water quality data,then establishanother water quality prediction model,in which the three Principal Components areregarded as the explanatory variables. Compared to the former, the latter can moreaccurately embody the mechanism of bacterial regrowth and also have a goodprecision . In conclusion,considering the reasons of bacterial regrowth, the paper pointedout the significances of water quality pridictiont, and brought forward some measurespreventing bacterial regrowth, which involved enhancing water treatment ,controllingerosion ,flushing pipelines and reinforcing management etc.更多还原