锌溶液中痕量Cu^(2+)、Co^(2+)的检测光谱预处理方法

Spectral Pretreatment Method for Detection of Trace Cu^(2+) and Co^(2+) in Zinc Solution

针对同时检测锌溶液中痕量Cu^(2+)、Co^(2+)浓度存在的灵敏度低、有效波段窄、光谱信号覆盖严重的问题,提出了一种多目标优化分数阶微分预处理方法。首先根据光谱特点确定影响Cu^(2+)、Co^(2+)同时检测的覆盖度和失真度,并拟合微分阶次与指标的函数关系、约束条件,然后基于多目标粒子群优化算法求解,最后对多目标优化微分阶数方法进行验证。结果表明:所提方法可以重构完全被覆盖的低灵敏度、窄有效波段的离子波峰,解决光谱信号被完全覆盖的问题,并在最大程度降低求导滤波的失真度,降低Cu^(2+)、Co^(2+)的光谱覆盖率。

As for the simultaneous detection of trace Cu2+ and Co2+ in zinc solution, there exist the problems of low sensitivity, narrow effective band and serious spectral signal coverage. Thus, a multi-objective optimization fractional differentiation pretreatment method is proposed. First, the coverage degree and distortion degree in the simultaneous detection of Cu2+ and Co2+ are determined according to the spectral characteristics, and the functional relationship and constraints of differential order and index are fitted. Then, the established optimization problem is solved by the multi-objective particle swarm optimization algorithm. This multi-objective differential order optimization method is finally verified. The results show that the proposed method can be used to reconstruct the completely covered ion wave peaks with low sensitivity and narrow effective bands, and to solve the complete spectral coverage problem. Moreover, it can be used to minimize the distortion degree of differential filtering and reduce the spectral coverage of trace Cu2+and Co2+to the maximum extent.