为了提高检验鉴定效率、降低检验鉴定成本, 实现对案件现场车用保险杠碎片的快速无损检测, 采用了基于红外指纹光谱结合牛顿插值多项式、光谱求导和判别分析的车用保险杠鉴别方法。采集并获取奥迪等6种品牌共计40个不同型号的车用保险杠样本的红外光谱, 选择牛顿多项式插值、光谱求导等方法建立了判别模型。结果表明, 基于指纹区波段建立的判别模型总体准确率(80.0%)高于全波段模型(77.5%), 指纹区光谱结合4次牛顿插值多项式处理后的判别准确率可到85%, 经1阶导数处理后判别准确率可达100%, 以判别函数DF1和DF2作为判别轴构建判别分类模型, 6种品牌的样本均实现了100%的准确区分; 红外指纹光谱结合4次牛顿插值多项式、1阶导数和判别分析可实现车用保险杠品牌快速、无损鉴别, 且模型检测精度高。该方法具有普适性和一定的借鉴意义。

In order to improve the efficiency of identification, reduce the cost of detection, and realize the rapid and non-destructive classification of the automotive bumper fragments, a rapid and accurate identification method about the automotive bumper was proposed based on infrared fingerprint spectroscopy, Newton interpolation polynomial, spectral derivation, and discriminant analysis. Infrared spectra of six kinds of brands of bumper samples including 40 different versions were acquired in this paper, and a discriminant model was established by taking Newton polynomial interpolation, spectral derivation, and other methods into account. The results show that the overall accuracy rate of the discriminant model based on the fingerprint zone (80.0%) is higher than that of the full-band model (77.5%). The accuracy rate of the discriminant based on fingerprint spectroscopy combined with 4th Newton interpolation polynomial processing can reach 85%. Selecting DF1 and DF2 as the discriminant axis to construct the discriminant classification model, the accuracy rate of the discriminant can be promoted to 100%. In summary, combining infrared fingerprint spectroscopy, 4th Newton interpolation polynomial, first derivative and discriminant analysis, the new method has higher accuracy in detecting the automotive bumper, and provides a new idea and reference for the identification of other physical evidence in the forensic science.