摘要：

以非离子表面活性剂OP为增溶、增敏剂,以5-Br-PADAP为显色剂,建立了同时测定废水中铁、镍、铜的小波包分析-简单递归神经网络(Elman神经网络)分光光度法。该方法采用小波包分析处理吸收光谱数据,以滤除信号中的噪声,然后用Elman神经网络进行数据解析。将此方法应用于模拟废水以及印染厂废水中Fe(Ⅲ)、Ni(Ⅱ)、Cu(Ⅱ)的测定,回收率分别可达97.5%～102.5%,结果令人满意。

关键词: 小波包分析, 简单递归神经网络, 废水

Abstract:

The method of simultaneous determination of Fe( Ⅲ), Ni ( Ⅱ) and Cu( Ⅱ) in wastewater by wavelet packets analysis-simple recurrent neural network spectrophotometry with 5-Br-PADAP as colorizing agent in the presence of nonionic surfactant OP to increase its solubility and sensibility has been established. The noise in the visible spectrum can be eliminated by wavelet packets analysis and the data are analyzed by Elman neural network. The proposed method has been applied to the determination of Fe( Ⅲ ), Ni ( Ⅱ ) and Cu( Ⅱ) in simulated and true wastewater respectively with satisfactory results. The recovery rates of Fe( Ⅲ),Ni( Ⅱ) and Cu( Ⅱ) ranged from 97.5%-102.5%.

Key words: wavelet packets analysis, simple recurrent neural network, wastewater

中图分类号: 

• O65