摘要： 随着经济的高速稳定发展，科学技术水平不断的提高，污水的处理处置能力不断的加强，废水处理中产生的污泥总量在日益提高。如何能经济、快速又能在不对环境造成二次污染的前提下处理污泥，是一个亟需解决的问题。目前，加速污泥水解有物理、化学和生物的方法，其中有热、碱、氧化等方法，这些方法能使细胞被有效的破解裂解，同时还能提高后续的处理效率。本文研究的主要内容是对制药废水的处理处置过程中产生的污泥进行加热、碱解和氧化预处理，从而达到提高污泥溶胞率和减量率的效果。考察的主要因素有温度、PH值、高铁酸钾投加量、反应时间等四个因素，继而通过测量预处理前水质的TCOD、SCOD和预处理后水质SCOD来计算污泥溶胞率，为了优化工艺，建立了以温度、PH值、高铁酸钾投加量、反应时间四个因素为自变量，污泥溶胞率为因变量的RBF神经网络模型，模型拟合效果较好，有助于对工艺进一步研究。

关键词： 污泥减量；热碱；高铁酸钾；RBF神经网络模型

Research On Biochemical Sludge Reduction

Abstract: With the rapid and stable development of economy, scientific and technological level have been continually improved, and the capacity of sewage treatment and disposal is constantly strengthened, and the total amount of sludge produced in wastewater treatment is also increasing. How to deal with residual sludge quickly, effectively and environmentally is an urgent problem. At present, such as chemical, physical, biological, accelerate sludge hydrolysis method, including heat, alkali and oxidation pretreatment method, not only effective in cell cracking, but also can strengthen the effect of subsequent processing sludge. The main content of this study is to pretreat the sludge produced in the process of pharmaceutical wastewater treatment, so as to improve the dissolution rate of residual sludge and reduce the sludge yield. The main factors are four factors, such as temperature, pH value, potassium ferrate dosage, reaction time, etc., and then calculate the sludge lysate rate by measuring the TCOD, SCOD and pre treated water quality SCOD before pretreatment. In order to optimize the process, four factors such as temperature, pH value, potassium ferrate dosage and reaction time are established. The RBF neural network model with independent variables and sludge dissolution rate as dependent variable has better fitting effect and is helpful to further study of the process.

Keywords: Biochemical Sludge Reduction; Thermokalite; Totassium ferrate; RBF neural network model

目录

摘要 i

Abstract i

目录 iv

1 绪论 1

1.1 污泥处理厂污泥的组成与性质 1

1.1.1 污泥处理厂污泥的组成 1

1.1.2 剩余污泥的性质 2

1.2 污泥减量技术概述 3

1.2.1 添加酶制剂的酶水解技术 3

1.2.2 机械破解 3

1.2.3 超声破解技术 4

1.2.4 臭氧氧化技术 5

1.2.5 电处理 5

1.2.6 微生物捕食 6

1.3 课题研究的意义及技术路线 6

1.3.1 课题目的与意义 6

1.3.2 课题技术路线 7

2 实验过程 8

2.1 实验步骤 8

2.1.1 实验过程 8

2.1.2 测量数据 8

2.1.3 分析方法 8

2.2 实验药品及仪器 9

2.2.1 实验药品 9

2.2.2 实验项目及其仪器 9

2.3 实验污泥 10

2.4 实验数据 10

2.4.1 温度为控制变量下的实验数据 10

2.4.2 Ph为控制变量下的实验数据 11

2.4.3 多因素实验数据 12

2.5 总结 13

3 影响因素分析 14

3.1 热解处理对污泥减量的影响 14

3.2 碱预处理对污泥减量的影响 14

3.3 反应时间对污泥减量的影响 15

3.4 化学氧化剂（高铁酸钾）对污泥减量的影响 16

4 基于RBF神经网络模型对工艺优化 18

4.1 RBF神经网络模型概述 18