光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2010年
4期
975-978
,共4页
拉曼光谱%定性分析%特征提取%纤维
拉曼光譜%定性分析%特徵提取%纖維
랍만광보%정성분석%특정제취%섬유
Raman spectroscopy%Feature extraction%Fiber%Qualitative analysis
拉曼光谱作为快速、无损的检测技术受到越来越广泛的关注,已经成功的应用于过程监控、质量监测、考古鉴定等领域.针对纺织纤维拉曼光谱的特性,提出了一种基于特征提取的拉曼光谱定性鉴别方法.该方法通过直接测取织物、纤维的激光拉曼光谱,并结合光谱预处理技术与特征峰提取、匹配识别方法,能够定性地鉴别织物、纤维的成分归属,对纺织品检验中的难点化学纤维成分的鉴别效果尤其显著.利用94份测试样品对织物成分中普遍存在的4种纤维品种--涤纶、腈纶、锦纶和粘胶进行了鉴别以验证算法的有效性.实验结果表明,该鉴别方法快速、有效,并具有很好的扩展性能,且该方法属纯粹的光学方法,需要样品量少、无需前处理,测试过程对样品无损,不产生化学污染物,适宜对各类织物成分的定性鉴别,突破了现有检测方法存在的局限.
拉曼光譜作為快速、無損的檢測技術受到越來越廣汎的關註,已經成功的應用于過程鑑控、質量鑑測、攷古鑒定等領域.針對紡織纖維拉曼光譜的特性,提齣瞭一種基于特徵提取的拉曼光譜定性鑒彆方法.該方法通過直接測取織物、纖維的激光拉曼光譜,併結閤光譜預處理技術與特徵峰提取、匹配識彆方法,能夠定性地鑒彆織物、纖維的成分歸屬,對紡織品檢驗中的難點化學纖維成分的鑒彆效果尤其顯著.利用94份測試樣品對織物成分中普遍存在的4種纖維品種--滌綸、腈綸、錦綸和粘膠進行瞭鑒彆以驗證算法的有效性.實驗結果錶明,該鑒彆方法快速、有效,併具有很好的擴展性能,且該方法屬純粹的光學方法,需要樣品量少、無需前處理,測試過程對樣品無損,不產生化學汙染物,適宜對各類織物成分的定性鑒彆,突破瞭現有檢測方法存在的跼限.
랍만광보작위쾌속、무손적검측기술수도월래월엄범적관주,이경성공적응용우과정감공、질량감측、고고감정등영역.침대방직섬유랍만광보적특성,제출료일충기우특정제취적랍만광보정성감별방법.해방법통과직접측취직물、섬유적격광랍만광보,병결합광보예처리기술여특정봉제취、필배식별방법,능구정성지감별직물、섬유적성분귀속,대방직품검험중적난점화학섬유성분적감별효과우기현저.이용94빈측시양품대직물성분중보편존재적4충섬유품충--조륜、정륜、금륜화점효진행료감별이험증산법적유효성.실험결과표명,해감별방법쾌속、유효,병구유흔호적확전성능,차해방법속순수적광학방법,수요양품량소、무수전처리,측시과정대양품무손,불산생화학오염물,괄의대각류직물성분적정성감별,돌파료현유검측방법존재적국한.
According to the characteristics o{ the textile fibers Raman spectra, a qualitative identification method based on Raman feature extraction is proposed. This fast method consists of spectrum measurement and spectral data processing algorithm, inclu-ding spectrum preprocessing, feature extraction and matching recognition. It can be used to identify the components of fibers or fabrics, especially chemical fibers, which is an inspective difficulty in daily analytic work for its remarkable Raman feature. The authors performed an experiment to analyze 4 typical and widely used kinds of fibers as algorithm verification. They are terylene fiber, acrylic fiber, nylon fiber and rayon fiber. To identify the components of one test sample, first the authors set up feature tables of these 4 standard samples, which describe the features of their preprocessed spectra containing both position information and intensity information, then extract features of the test sample. The authors match these features with the tables and calcu-late the matching confidence coefficients of the results, which can be used to filter the unexpected matching results caused by ac-cident and attain the final qualitative identification result. The experimental results confirm that this method is effective, efficient and expansible, which means it can be used to identify more actual fiber types by adding more standard spectra to the feature ta-ble database. In addition, it is a pure optical method, which needs only a small quantity of sample without any pretreatment.The whole identification process is damage-free, pollution-free and suitable for various kinds of fabrics. Compared to all existing methods, this Raman spectrum identification method can solve the limitation of efficiency, pollution, universality, and fill a gap in fabric inspection field.