光谱学与光谱分析, 2017, 37 (12): 3664, 网络出版: 2018-01-04   

时频域分形维数分析的光谱信号重叠峰解析算法

Implementation of Overlapping Peak Separation Algorithm for Absorption Spectra by Fractal Dimension Analysis in Time-Frequency Domain
作者单位
1 武汉大学电子信息学院, 湖北 武汉 430079
2 电网环境保护国家重点实验室, 中国电力科学研究院, 湖北 武汉 430074
摘要
由于光谱谱线存在自然展宽、 多普勒展宽、 碰撞展宽等, 使混合气体中多种成分的吸收光谱信号出现相邻谱峰重叠现象, 给混合气体组成成分的定性或定量检测带来较大的困难。 现有的方法在获取先验知识、 处理精度、 运算效率等方面存在不足。 提出基于时频域分形维数分析的光谱信号重叠峰解析算法, 结合小波的多尺度观测能力和分形的自相似度的度量能力, 识别、 定位和解析光谱信号中的重叠峰。 首先利用小波对具有重叠谱峰的光谱信号进行光谱频率域和尺度域的分析, 然后对该时频域的光谱信号在同一光谱频率下的多尺度数据进行自相似性度量和分形计算。 逐频率计算后得到光谱信号在频率域的分形维数曲线。 该曲线体现了光谱信号在不同尺度的自相似性, 其极值位置与光谱信号的各独立峰的位置具有相关性。 依据此特性, 结合分形曲线的特征参数, 最后利用神经网络解析出对应混合气体成分的混叠在一起的各个独立谱峰。 该方法利用小波的多分辨率特性, 对信号进行不同尺度的精细度量。 分形模型则提高了系统解析复杂信号的能力, 对重叠程度高的多谱峰重叠信号也有很强的处理能力。 借助人工神经网络, 实现了整个算法的自动测量。 通过实验结果分析, 验证了算法的有效性, 并讨论影响算法效果的主要因素。
Abstract
Because of the natural broadening, Doppler broadening, and collision broadening of spectral lines, multiple adjacent peaks in the absorption spectrum signal of mixed gas with multiple components are often overlapping, which makes the qualitative or quantitative analysis of hybrid gas composition difficult. Existing methods have deficiencies in obtaining a prior knowledge, accuracy, and computational efficiency. An overlapping peak separation algorithm for absorption spectra is proposed in this paper, which can identify, locate, and parse independent peaks overlapped in the spectral signal by combining the multiscale observation of wavelet and the self-similarity measure of fractal. Firstly, spectral signal with overlapping peaks was transformed to the time-frequency domain by wavelet, so we can analyze it in light frequency and scale domain. Secondly, the self-similarity of the multi-scale data of the spectral signal at a specified frequency was measured by fractal analysis, which was performed at every frequency in a frequency range of interest to acquire a fractal dimension curve. The fractal dimension curve reflected the self-similarity of the spectral signal at different scales, and the locations of local extremum of the curve were related to the position of the independent peaks. Finally, according to the fact and the feature parameters of the fractal dimension curve, independent peaks generated from mixed gas composition were separated from the spectral signal by an artificial neural network. The proposed algorithm in the paper carried on the fine analysis on the spectral signal at different scales using the multiresolution characteristic of the wavelet, and improved the analytical ability to parse the independent peaks with a high degree of overlap. The automatic measurement of the entire algorithm was realized using the artificial neural network. The validity of the proposed algorithm was verified by the analysis of experimental results, and the main factors that affected the algorithm were discussed.

陶维亮, 刘艳, 王先培, 吴琼水. 时频域分形维数分析的光谱信号重叠峰解析算法[J]. 光谱学与光谱分析, 2017, 37(12): 3664. TAO Wei-liang, LIU Yan, WANG Xian-pei, WU Qiong-shui. Implementation of Overlapping Peak Separation Algorithm for Absorption Spectra by Fractal Dimension Analysis in Time-Frequency Domain[J]. Spectroscopy and Spectral Analysis, 2017, 37(12): 3664.

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