以3种不同的动物（3*10）血样以及21个人血液作为分析对象，采用主成分分析（PCA）结合拉曼光谱进行血液定性识别检测，通过矢量归一化对拉曼信号进行预处理，以及杠杆值与残差值得分图剔除异样点，使得人与动物血样的识别率均高于95%，并在此基础上进一步采用PCA进行动物血样之间的识别，使得个体的识别率高于90%。实验结果表明PCA在血液识别检测中具有较好的应用前景和可行性，该方法也可以为刑侦、生命科学等应用领域提高借鉴。

In the paper 3 kinds of animal for a total of 30 animal blood samples and 21 human blood samples were chosen as the typical tested objects. Principle component analysis (PCA) method was employed to quickly identify the species of blood samples based on Raman spectroscopy. Vector normalization was used to preprocess the Raman spectroscopy signal. According to the plot of Leverage value vs. Studentized residue, outlier sample was detected and removed. By the PCA method, the correct rate between animal blood samples and human blood samples was up to 95% based on PC1and PC2. Further on the basis of PC4 and PC5, the correct rate of identification the animal blood sample was above 90%. The experiment results showed that the PCA method had good application prospects and feasibility to identify the species of blood samples. This method provided a reference for processing the similar problems in the field of forensic science and life science.