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Noise reduction of fast,repetitive GC/MS measurements using principal component analysis (PCA)

机译:使用主成分分析(PCA)进行快速,重复的GC / MS测量的噪声降低

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摘要

Principal component analysis (PCA) was applied to the noise reduction of low ppb level benzene, toluene,ethyl benzene xylene (BTEX) type gas chromatography/mass spectrometry (GC/MS) measurements (i.e.BTEX) with a fast,repetitive GC/MS system. The first three prinal components (PCs) accounting for approximately 60-80% of the total variance in the original data could be attributed to chemical components,whilst the remaining PCs were found to be due to noise. Reconstruction of the data from the first three PCs resulted in noise reduction with improved signal fidelity. The results of PCA were comparable with those achieved by a Fourier transform method.
机译:主成分分析(PCA)通过快速,重复的GC / MS用于降低低ppb级苯,甲苯,乙苯二甲苯(BTEX)型气相色谱/质谱(GC / MS)测量(ieBTEX)的噪声系统。前三个主要成分(PC)约占原始数据总方差的60-80%,可能归因于化学成分,而其余PC则归因于噪声。前三台PC的数据重建可以降低噪声并提高信号保真度。 PCA的结果与通过傅立叶变换法获得的结果相当。

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