摘要
针对加药过程中反馈滞后性、非线性相关性和干扰因素多的特点,以及传统比例积分微分(PID)控制器存在响应速度慢、二次扰动高及抗干扰能力弱的问题,设计了一种新型智能次氯酸钠投加方案,以满足净水加氯工艺对出水余氯质量浓度和加药量的要求.新型智能加氯方案中,使用ControlLogix系统作为下位机,在下位机中嵌入模型预测控制(MPC)模块;模型预测控制模块中使用水厂的历史数据建立预测模型,在模拟实际应用中进行模型训练,并在控制模块中整合了水厂的经验公式,实现了加药系统的智能控制.研究结果表明:水厂出水余氯质量浓度较稳定,为0.97~1.16 mg·L^(-1);与传统加氯方案相比,新型智能加氯方案中次氯酸钠溶液每小时消耗量降低了0.5%~1.0%.
To solve the problems of feedback lag,nonlinear correlation and interference factors in the dosing process and the problems of the traditional proportion integration differentiation(PID)controller with slow response speed,high secondary disturbance and weak anti-interference ability,a new intelligent sodium hypochlorite dosing scheme was designed to meet the requirements of chlorine concentration and dosage of effluent in the chlorination process for water purification.In the new intelligent chlorination scheme,ControlLogix system was used as the lower machine,and model predictive control(MPC)module was embedded in the lower machine.In the model predictive control module,the historical data of the water plant was used to build the prediction model,and the model training was carried out in the simulation practical application.In the control module,the empirical formula of the water plant was integrated to realize the intelligent control of the dosing system.The results show that the residual chlorine concentration is stable at the range of 0.97-1.16 mg·L^(-1).Compared with the traditional chlorination scheme,the consumption of sodium hypochlorite solution per hour in the new intelligent chlorination scheme is reduced by 0.5%-1.0%.
作者
毛卫平
刘志浩
MAO Weiping;LIU Zhihao(School of Mechanical Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013,China)
出处
《江苏大学学报（自然科学版）》
CAS
北大核心
2023年第2期229-234,共6页
Journal of Jiangsu University：Natural Science Edition
关键词
净水加氯工艺
水处理方法
模型预测控制
模型训练
次氯酸钠投加
chlorination process for water purification
water treatment method
model predictive control
model training
sodium hypochlorite dosing
