有色冶金工业废水电化学深度净化过程协调优化方法

The electrocoagulation-based deep purification technology is the most important treatment process for industrial wastewater of non-ferrous metallurgy. Due to the complexity of reaction mechanism, process coupling and the frequent large fluctuations of the concentrations and the flow of the industrial wastewater, it is difficult to realize the optimal operation of the whole treatment process, which leads to high consumption of energy, high chemical reagent consumption and large loss of electrode plate. Especially, the treated industrial wastewater of non-ferrous metallurgy is hard to steadily meet the requirements of discharge standard, and there usually exists large hidden danger of environmental pollution. Considering the problems mentioned above, we will investigate the coordination optimization methods of the electrocoagulation-based deep purification process for industrial wastewater of non-ferrous metallurgy. Based on the analysis of reaction mechanism, we will establish the kinetic model of electrocoagulation reaction system based on the correlated mass transfer equation and the probability distribution. The prediction model of removal efficiency of the heavy metal will be studied by effectively integrating with the chemical reaction mechanism-based prediction model and the prediction model using trend analysis based on the case-based reasoning method. Then, the multi-objective optimization method of the electrocoagulation process with the minimum power consumption and the minimum loss of electrode plate will be studied. Finally, the coordination optimization methods of the whole electrocoagulation-based deep purification process based on hierarchical optimization will be investigated to guarantee the optimal operation of the whole treatment process. It is greatly significant to guarantee the treated industrial wastewater of non-ferrous metallurgy to steadily meet the discharge standard and reduce the production costs of the wastewater treatment.

电化学深度净化是有色冶金工业废水处理的重要工艺。由于净化过程反应机理复杂、多工序关联耦合以及有色冶金工业废水成份、流量大幅度波动频繁，过程优化运行困难，造成生产能耗高、药剂消耗高以及极板损耗大，难以保证处理后废水的稳定达标排放，环境污染隐患大。为此，本项目开展有色冶金工业废水电化学深度净化过程协调优化方法研究。从反应机理出发，研究基于传质关联方程和概率分布描述的电化学反应体系动力学模型；建立基于极板损耗量的去除效率估计机理模型和基于趋势分析的去除效率案例推理预估模型，并将两者有机集成，实现电化学处理过程重金属离子去除效率的预估。在此基础上，提出面向电耗与极板损耗最小的电化学处理过程多目标优化方法和基于分层优化的深度净化全流程协调优化方法，实现有色冶金工业废水电化学深度净化过程的优化运行。本项目研究对确保废水稳定达标排放、降低废水处理生产成本具有重要意义。

有色冶金工业废水电化学深度净化过程中多种重金属离子共存且互相影响严重、反应机理复杂、多工序关联耦合、流量与pH值等因素波动频繁，使得过程优化运行困难，导致生产电耗高、药剂消耗高和极板损耗大，且难以保证处理后的废水稳定达标排放，造成环境污染隐患大等问题。为此，本项目开展有色冶金工业废水电化学深度净化过程协调优化方法研究。首先，提出了一种高精度的基于特征区间联合-灵敏度因子的多重金属离子浓度检测方法；然后，在分析研究电化学处理过程反应机理的基础上，建立了重金属离子电化学反应动力学模型，并提出了基于数据的误差补偿方法；针对电化学反应器除杂性能逐渐降低的问题，分析多影响因素与去除率关系，研究建立了基于数据驱动的反应器去除率LSTM-ARIMA预测模型；在此基础上，围绕重金属废水处理生产过程中的实际需求，提出了面向成本最优的电化学废水处理过程优化控制方法、基于多工序参数反向优化分配的电导率预调节方法、基于模糊分数阶PID的中和过程pH值稳定控制策略和基于操作模式动态匹配的全流程协调优化方法。采用工业现场数据对所提方法进行了有效性验证，实验结果表明节能效果明显，实现了有色冶金工业废水电化学深度净化过程的优化运行。本项目研究对确保废水稳定达标排放、降低废水处理生产成本具有重要意义。.项目执行过程中，发表论文10篇，授权国家发明专利8项，获得国家知识产权局专利优秀奖1项。