Raman spectroscopy has the advantages of non-contact, non-destructive, low cost and high throughput, and has been paid more attention to in the analysis of multi-component systems. Independent component analysis (ICA) is not only a multivariate statistical method, but also a blind separation method. It can solve the estimated source spectra of each component in the system only by measuring the mixed spectra without prior knowledge. However, when there is significant overlap between the source spectra, ICA separation results are not reliable. In this paper, an improved ICA qualitative analysis algorithm is proposed, which is based on the derivation of the spectrum of the system, ICA separation, and then separation after removing components step by step (Derivation, Separation,Culling and Separation, DSCS-ICA),the approximate estimation of the source spectrum is obtained by separation, and the qualitative analysis of the system is realized, which solves the problem of poor separation performance of the existing ICA algorithm caused by spectral overlap.According to the formula of ibuprofen capsule, 12 samples of ibuprofen capsule were prepared with different proportions of five components, including ibuprofen, stearic acid, polyvinylpyrrolidone K30, starch and sucrose, and their Raman spectral data were collected. The components (ICS ) were solved by DSCS-ICA method, and the ICS was compared with the source spectrum, and the correlation coefficient r was used to judge the consistency between ICSand the source spectrum. The results show that, compared with FastICA, the effect of DSCS-ICA is significantly improved, and the correlation coefficient r of ICSand the source spectrum is above 0.99, which shows that the results have good reliability and correspondence. This case can provide reference for the reverse study of drug prescription ingredients, and can be applied to the qualitative analysis of other multi-component systems.