摘要
在重金属离子检测仪器及其工作原理研究的基础上,对污水中重金属离子浓度测量方法进行了分析研究,分析了采用软测量技术的可行性和必要性,针对水质测量具有非线性、大时变和多滞后的特点,提出了基于BP神经网络的污水中重金属离子浓度软测量建模方法,建立了软测量模型,并通过仿真分析和实验验证了该方法的实用性。
Based on the research of the instruments of heavy metal ions dectection and their principles,the means of heavy metal ions detection are researched,and the feasibility and necessity of using the soft measuring technique is analyzed.According to the nonlinear,time-variable and seriously lag characters of water detection processes,a soft measuring model of heavy metal ion detection is proposed based on BP artificial neural networks.The results of simulation test and experimental research show that this model is applicable to detect the concentration of heavy metal ion in wastewater.
出处
《后勤工程学院学报》
2011年第3期53-57,86,共6页
Journal of Logistical Engineering University
基金
国家水体污染控制与治理科技重大专项资助项目(2008ZX07315-003)
重庆市自然科学基金资助项目(CSTC,2009BB7175)
关键词
BP神经网络
软测量
重金属离子
浓度检测
污水
BP neural network
soft-sensing
heavy metal ion
concentration detection
wastewater
