{"title":"基于电磁波传播时间的特定树种木材含水率预测模型","authors":"Peng Wang, Ruixia Qin, Jiaxing Guo, Jiedong Wei, Huadong Xu","doi":"10.15376/biores.19.2.3001-3009","DOIUrl":null,"url":null,"abstract":"Laboratory and field experiments were performed to examine the feasibility of using Time Domain Reflectometry (TDR) to monitor moisture content (MC) of wood and standing trees. The TDR was used to detect the electromagnetic wave propagation time of four tree species (Betula platyphylla, Tilia tuan, Picea asperata, and Fraxinus mandshurica) at different MCs. During the TDR test, effects of probe insertion depths on MC predictive accuracy were considered. The best results were obtained at an insertion depth of 8 cm. At the selective 8 cm insertion depth, a species-specific MC prediction model (0.94 ≤ R2 ≤ 0.98), a generalized model for the four species (R2 = 0.65), and a hybrid model for the species with similar densities (0.80 ≤ R2 ≤ 0.96) were constructed, respectively. Overall, the species-specific MC prediction model showed good predictive ability for both tree and wood disc samples, including that TDR can be used to detect wood and standing tree MC. If possible, the hybrid model can be used for species with similar density.","PeriodicalId":9172,"journal":{"name":"Bioresources","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Species-specific prediction model of wood moisture content based on electromagnetic wave propagation time\",\"authors\":\"Peng Wang, Ruixia Qin, Jiaxing Guo, Jiedong Wei, Huadong Xu\",\"doi\":\"10.15376/biores.19.2.3001-3009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Laboratory and field experiments were performed to examine the feasibility of using Time Domain Reflectometry (TDR) to monitor moisture content (MC) of wood and standing trees. The TDR was used to detect the electromagnetic wave propagation time of four tree species (Betula platyphylla, Tilia tuan, Picea asperata, and Fraxinus mandshurica) at different MCs. During the TDR test, effects of probe insertion depths on MC predictive accuracy were considered. The best results were obtained at an insertion depth of 8 cm. At the selective 8 cm insertion depth, a species-specific MC prediction model (0.94 ≤ R2 ≤ 0.98), a generalized model for the four species (R2 = 0.65), and a hybrid model for the species with similar densities (0.80 ≤ R2 ≤ 0.96) were constructed, respectively. Overall, the species-specific MC prediction model showed good predictive ability for both tree and wood disc samples, including that TDR can be used to detect wood and standing tree MC. If possible, the hybrid model can be used for species with similar density.\",\"PeriodicalId\":9172,\"journal\":{\"name\":\"Bioresources\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioresources\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.15376/biores.19.2.3001-3009\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, PAPER & WOOD\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioresources","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.15376/biores.19.2.3001-3009","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, PAPER & WOOD","Score":null,"Total":0}
引用次数: 0
摘要
为了研究使用时域反射仪(TDR)监测木材和立木含水率(MC)的可行性,我们进行了实验室和现场实验。TDR 用于探测四种树种(Betula platyphylla、Tilia tuan、Picea asperata 和 Fraxinus mandshurica)在不同 MC 下的电磁波传播时间。在 TDR 测试过程中,考虑了探针插入深度对 MC 预测精度的影响。插入深度为 8 厘米时结果最佳。在选择的 8 厘米插入深度下,分别构建了物种特异性 MC 预测模型(0.94 ≤ R2 ≤ 0.98)、适用于四个物种的广义模型(R2 = 0.65)和适用于密度相似物种的混合模型(0.80 ≤ R2 ≤ 0.96)。总体而言,树种特异性 MC 预测模型对树木和木盘样本都显示出良好的预测能力,包括 TDR 可用于检测木材和立木 MC。如果可能,混合模型可用于密度相似的树种。
Species-specific prediction model of wood moisture content based on electromagnetic wave propagation time
Laboratory and field experiments were performed to examine the feasibility of using Time Domain Reflectometry (TDR) to monitor moisture content (MC) of wood and standing trees. The TDR was used to detect the electromagnetic wave propagation time of four tree species (Betula platyphylla, Tilia tuan, Picea asperata, and Fraxinus mandshurica) at different MCs. During the TDR test, effects of probe insertion depths on MC predictive accuracy were considered. The best results were obtained at an insertion depth of 8 cm. At the selective 8 cm insertion depth, a species-specific MC prediction model (0.94 ≤ R2 ≤ 0.98), a generalized model for the four species (R2 = 0.65), and a hybrid model for the species with similar densities (0.80 ≤ R2 ≤ 0.96) were constructed, respectively. Overall, the species-specific MC prediction model showed good predictive ability for both tree and wood disc samples, including that TDR can be used to detect wood and standing tree MC. If possible, the hybrid model can be used for species with similar density.
期刊介绍:
The purpose of BioResources is to promote scientific discourse and to foster scientific developments related to sustainable manufacture involving lignocellulosic or woody biomass resources, including wood and agricultural residues. BioResources will focus on advances in science and technology. Emphasis will be placed on bioproducts, bioenergy, papermaking technology, wood products, new manufacturing materials, composite structures, and chemicals derived from lignocellulosic biomass.