摘要
水样中金属元素快速、准确的测试方法研究具有现实意义。为此，在pH值为1．50的硝酸-硝酸钾溶液环境中，应用BP神经网络对方波溶出伏安数据进行处理，建立了铜、铅、镉、锌4种金属离子同时测定的神经网络测试模型，并应用该测试模型检测了水样中的4种金属离子。结果表明，该神经网络测试模型能够较好地解决金属离子之间的相互作用和伏安信号干扰问题，测量结果比较准确，具有一定的应用和研究价值。
It is practically significant for studying on analysis methods for rapidly and easily determining trace metals in water. In this paper the stripping vohammetric responses were obtained in the solutions containing varying concentrations of Cu , Pb , Cd , and Zn by square wave stripping voltammetry in supporting electrolytes of KNO3 ＆ HNO^pH1.5）. A BP neural network was utilized to cope with the analysis results and trained to model the relationship between responses and concentrations in the situation of simultaneous determination of the four heavy metals. The results of the water sarmple show that neural network can be used to solve the problems of significant complications due to interaction of metal cations. Based on comparatively accurate testing results, this method has practical applications and research values.
关键词
神经网络
方波溶出伏安法
铜
铅
镉
锌
Neural network
Square wave stripping vohammetry
Cu
Pb
Cd
Zn
