首页 | 本学科首页   官方微博 | 高级检索  
     检索      

近红外光谱结合SIMCA模式识别法检测木材表面节子
引用本文:杨忠,陈玲,付跃进,吕斌.近红外光谱结合SIMCA模式识别法检测木材表面节子[J].东北林业大学学报,2012,40(8):70-72.
作者姓名:杨忠  陈玲  付跃进  吕斌
作者单位:中国林业科学研究院木材工业研究所,北京,100091
基金项目:国家自然科学基金(30800889)
摘    要:利用近红外光谱结合SIMCA模式识别法来检测马尾松木材单板节子.结果表明,通过培训集样本建立的基于主成分分析的SIMCA判别模型对有无节子两种类型样本进行回判和对未知节子类型的样本(包括无节子和有节子样本)的判别正确率均达到90%~100%,说明应用近红外光谱结合SIMCA模式识别法可以快速有效地检测木材表面的节子缺陷.

关 键 词:近红外光谱  SIMCA模式识别法  木材单板  节子缺陷  检测

Rapid Detection of Knot Defect in Wood Surface by Near Infrared Spectroscopy Coupled with SIMCA Pattern Recognition
Yang Zhong , Chen Ling , Fu Yuejin , Lü Bin.Rapid Detection of Knot Defect in Wood Surface by Near Infrared Spectroscopy Coupled with SIMCA Pattern Recognition[J].Journal of Northeast Forestry University,2012,40(8):70-72.
Authors:Yang Zhong  Chen Ling  Fu Yuejin  Lü Bin
Institution:Yang Zhong,Chen Ling,Fu Yuejin,Lü Bin(Research Institute of Wood Industry,Chinese Academy of Forestry,Beijing 100091,P.R.China)
Abstract:A study was performed to rapidly detect knots in Pinus massoniana veneer by near infrared(NIR) spectroscopy coupled with soft independent modeling of class analogy(SIMCA) pattern recognition as well as principal component analysis.The discriminant accuracy by the SIMCA model based on principal component analysis was between 90% and 100%.Results showed that NIR spectroscopy coupled with SIMCA pattern recognition could be used to rapidly detect knot defect in wood veneer.
Keywords:Near infrared spectroscopy  SIMCA pattern recognition  Wood veneer  Knot defects  Detection
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号