摘要
为了快速无损地检测评估木材的霉变及含水量,利用高光谱激光雷达系统主动获取木材的高光谱数据,设计了一种分析霉变特征并建立含水量预测模型的方法。首先选取白松为样本,进行时长为4个月的间隔性测量,分析其霉变发生发展过程(正常、潮湿和霉变状态)的光谱特征变化;然后在分析样本不同含水量光谱特性的基础上,采用竞争性自适应重加权采样算法、连续投影算法及竞争性自适应重加权采样-连续投影组合算法提取特征波长;最后分别建立偏最小二乘回归预测模型。结果表明,正常状态的光谱反射率最高而霉变状态最低;当霉变状态稳定时,光谱反射率随时间变化缓慢并趋于稳定;基于竞争性自适应重加权采样-连续投影组合算法建立的模型预测性能最佳,预测集的相关系数和均方根误差分别为0.9073和0.7564。利用高光谱激光雷达主动获取的高光谱信息可以评估木材的霉变并实现含水量预测,为木质建筑的快速无损检测提供了新思路。
In order to quickly and non-destructively detect and assess mildew and moisture content of timber,the hyperspectral data of timber was actively acquired by hyperspectral light detection and ranging(LiDAR),and a method was designed to analyze mildew characteristics and establish timber moisture content prediction model.Firstly,timber sample(white pine)hyperspectral data was measured at monthly intervals for four months,and the spectral characteristics of mildew occurrence and development(normal,wet and mildew state)were analyzed.Then based on analyzing the spectral characteristics of sample moisture content,competitive adaptive reweighted sampling,successive projections algorithm and competitive adaptive reweighted sampling-successive projections algorithm were employed to extract feature wavelength.Finally,prediction models were established with partial least squares regression respectively.The results show that,the spectral reflectance of normal state is highest and the mildew’s is lowest;when the mildew state is stable,the spectral reflectance changes slowly with time and tends to stabilize;and the model based on combined algorithm achieved the best predictive performance,the correlation coefficient and root mean square error of the prediction set are 0.9073 and 0.7564,respectively.The active acquisition of hyperspectral information by hyerspectral LiDAR can be used to assess mildew and predict timber moisture content,providing new ideas for rapid non-destructive detecting of wood buildings.
作者
刘璐
邵慧
孙龙
陈杰
徐恒
胡玉霞
肖晓
LIU Lu;SHAO Hui;SUN Long;CHEN Jie;XU Heng;HU Yuxia;XIAO Xiao(School of Electronic and Information Engineering,Anhui Jianzhu University,Hefei 230601,China;Anhui International Joint Research Center for Ancient Architecture Intellisencing and Multi-Dimensional Modeling,Anhui Jianzhu University,Hefei 230601,China)
出处
《激光技术》
CAS
CSCD
北大核心
2023年第5期620-626,共7页
Laser Technology
基金
安徽省科技厅面上项目(2008085MF182)
安徽省高校省级自然科学研究项目(KJ2021JD16,KJ2020A0471,KJ2021A0622)
安徽省高校协同创新项目(GXXT-2021-028)
安徽省古建筑智能感知与高维建模国际联合研究中心主任基金资助项目(GJZZX2021ZR02)。
关键词
遥感
高光谱激光雷达
偏最小二乘回归
木材
霉变
含水量
remote sensing
hyperspectral LiDAR
partial least squares regression
timber
mildew
moisture content
