“M+N”理论从误差理论的角度阐明了光谱分析中外界干扰因素即“N”因素对于测量精度的影响, 并给出了提高测量精度的方法。 通过采用实测变电压光源光谱数据与多组分线性吸收谱仿真模型相结合的方法, 构造了三组分的理想混合溶液并选择光源电压作为影响被测组分浓度测量精度的“N”因素, 分别设定了不同信噪比下的两组各三种不同的校正集与预测集样本“N”因素分布方式, 得出了对于系统误差类“N”因素而言, 校正集与预测集的“N”因素分布范围对组分浓度的预测精度具有一定影响的结论。 实验结果验证了“M+N”理论中“N”因素用于提高测量精度的可行性, 同时为其他测量系统减小外界干扰提高测量精度提供了理论指导。

Based on the error theory, “M+N” theory illustrates the effect of “N” factor such as external disturbance in the spectral analysis and provides a method to improve measurement accuracy. Multi-component ideal simulation model was established using the method that combines source spectra measured under different voltage with multi-component linear absorption spectral model. Meanwhile, source voltage was chosen as the “N” factor influencing the accuracy of measured component concentration. “N” factor distribution mode of samples was set to two groups with three different modes under different signal-to-noise ratio. It is concluded that prediction accuracy of component concentration is certainly influenced by “N” factor distribution range of calibration set and prediction set, which is system error. It was verified by the experimental results that “N” factor can be used to improve measurement accuracy based on “M+N” theory. Moreover, this research supplies a theoretic guidance for reducing interference and improving measurement accuracy of complex measurement system.