Lubricating oil component detection algorithm based on characteristic peaks

Abstract:
Based on the point data obtained by NMR technology, the NMR spectrogram analysis model is established, and the original file output of the NMR spectrometer is first identified, converted, and the spectrum is established. Then the established spectrogram is analyzed, and the results are obtained by using the model proposed in this paper. Based on the material detection algorithm of the characteristic peak and the similarity analysis algorithm, the model in this paper not only considers the relationship between the number of characteristic peaks, the chemical displacement corresponding to the known substance, and the characteristic peak of the unknown sample but also considers the influence of the peak intensity of the characteristic peak on the experimental results. This model analyzes and detects the NMR spectra of various known lubricant additives and unknown samples. The experimental results obtained from multiple dimensions are more comprehensive and reliable than those obtained by the traditional Nei coefficient and non-uniformity methods.