基于神经网络的木材光谱分类方法研究  

Research on the Spectral Classification Method of Wood Based on Neural Network

作　　者：黄永华[1] 宋骆林[1] 陈福 HUANG Yonghua;SONG Luolin;CHEN Fu(School of Mechanical,Electrical and information Engineering,Putian University,Putian Fujian 351100,China;New Engineering Industry College,Putian University,Putian Fujian 351100,China)

机构地区：[1]莆田学院机电与信息工程学院,福建莆田351100 [2]莆田学院新工科产业学院,福建莆田351100

出　　处：《信息与电脑》2024年第17期77-79,共3页Information & Computer

基　　金：福建省中青年教师教育科研项目,“基于太赫兹时域光谱技术的木材识别研究”(项目编号:JAT200511);“基于太赫兹时域光谱技术的食品和药品无损检测研究”(项目编号:JAT210389);“单极式光伏并网逆变器的改进无差拍电流控制”(项目编号:JAT200499)。

摘　　要：在木材的生产、流通、利用及加工过程中,需对木材进行分类识别。本次实验选取了绿檀、黑胡桃、非洲檀香木三种木材作为实验对象,获取了太赫兹时域光谱信号并提取其吸收系数谱,构建了三层反向传播(Back Propagation,BP)神经网络分类模型,并进行了模型训练和测试。实验结果表明,借助BP神经网络,三种木材的分类准确率、精确率、召回率、F1得分等性能指标均取得了较好值。In the production,distribution,utilization and processing of wood,wood needs to be classified and identified.In this experiment,three kinds of wood,namely green sandalwood,black walnut and African sandalwood,were selected as experimental objects,and the terahertz time-domain spectral signals were obtained and their absorption coefficient spectra were extracted.A three-layer BP neural network classification model was built,and model training and testing were carried out.The experiments show that with the help of back propagation(BP)neural network,the performance indicators such as classification accuracy,precision,recall,F1 score,etc.of the three kinds of wood have achieved good values.

关 键 词：木材光谱 分类识别 神经网络 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]