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首页> 外文期刊>Chemometrics and Intelligent Laboratory Systems >A real-time hyper-accuracy integrative approach to peak identification using lifting-based wavelet and Gaussian model for field mobile mass spectrometer
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A real-time hyper-accuracy integrative approach to peak identification using lifting-based wavelet and Gaussian model for field mobile mass spectrometer

机译：基于提升小波和高斯模型的现场移动质谱仪实时超高精度积分方法

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摘要

Field mobile mass spectrometer is pivotal apparatus for real-time qualitative and quantitative analyses of chemical substances in situ environment pollution detection. To solve spectrum peak signal interfered by complicated noise, and to recognize irregular peak shape as well as quick monitoring, a real-time denoising and hyper-accuracy peak identification integrative approach for field mobile mass spectrometer using lifting-based wavelet transform (LWT) and Gaussian model has been developed. First, LWT was applied to eliminate the noise and to search for mass peak parameters in raw spectral peak data. Then, fitting the irregular mass peaks with Gaussian multi-peaks, a regular spectrum signal was obtained for further processing. Both of synthetic and apparatus experiment results show that LWT is a fast and effective denoising and peak identification method and retained the original peak features. The denoising effect (SNR/RMSE) by LWT was superior to Savitzky-Golay method used widely by experimental mass spectrometer, and the processing time was shortened obviously. Moreover integrated with Gaussian fitting algorithm, the peak parameters (the peak area A, centroid c, and half peak's width w) had been optimized. As the result, qualitative and quantitative accuracies of FMMS increased consequently. In addition, the approach achieved data compression.
机译：现场移动质谱仪是用于现场化学污染物质实时定性和定量分析的关键设备。为了解决复杂噪声干扰下的频谱峰值信号，识别不规则的峰值形状并进行快速监控，采用基于举重的小波变换（LWT）的现场移动质谱仪的实时降噪和超高精度峰值识别集成方法。高斯模型已经开发出来。首先，应用LWT消除噪声并在原始光谱峰数据中搜索质量峰参数。然后，用高斯多峰拟合不规则质量峰，获得规则频谱信号以进行进一步处理。合成和仪器实验结果均表明，LWT是一种快速有效的降噪和峰识别方法，并且保留了原始的峰特征。 LWT的去噪效果（SNR / RMSE）优于实验质谱仪广泛使用的Savitzky-Golay方法，并且处理时间明显缩短。此外，结合高斯拟合算法，优化了峰参数（峰面积A，质心c和半峰宽w）。结果，FMMS的定性和定量精度随之提高。另外，该方法实现了数据压缩。

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