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林业科学 ›› 2022, Vol. 58 ›› Issue (9): 138-147.doi: 10.11707/j.1001-7488.20220914

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微钻阻力法间接测量木材密度

姚建峰1,郭旭展1,2,符利勇2,3,王雪峰2,3,雷相东2,3,卢军2,3,郑一力4,宋新宇5   

  1. 1. 信阳师范学院计算机与信息技术学院 信阳 464000
    2. 国家林业和草原局森林经营与生长模拟重点实验室 北京 100091
    3. 中国林业科学研究院资源信息研究所 北京 100091
    4. 北京林业大学工学院 北京 100083
    5. 信阳师范学院数学与统计学院 信阳 464000
  • 收稿日期:2021-06-27 出版日期:2022-09-25 发布日期:2023-01-18
  • 基金资助:
    河南省科技发展计划项目(212102110209);河南省高等学校重点科研项目(22A220002);国家自然科学基金项目(32071761)

Indirect Measurement of Wood Density by Micro Drill Resistance Method

Jianfeng Yao1,Xuzhan Guo1,2,Liyong Fu2,3,Xuefeng Wang2,3,Xiangdong Lei2,3,Jun Lu2,3,Yili Zheng4,Xinyu Song5   

  1. 1. College of Computer and Information Technology, Xinyang Normal University Xinyang 464000
    2. Key Laboratory of Forest Management and Growth Modelling, National Forestry and Grassland Administration Beijing 100091
    3. Research Institute of Forest Resource Information Techniques, CAF Beijing 100091
    4. College of Technology, Beijing Forestry University Beijing 100083
    5. College of Mathematics and Statistics, Xinyang Normal University Xinyang 464000
  • Received:2021-06-27 Online:2022-09-25 Published:2023-01-18

摘要:

目的: 探究微钻阻力仪钻针阻力与木材密度之间合适的模型形式,以及不同树种之间和同类树种之间的数学模型适应性,为微钻阻力法间接测量木材密度提供依据。方法: 1) 使用Resistograph 650-S微钻阻力仪测量包含软木和硬木8个树种木材样品的钻针阻力和绝干密度,每个树种2/3的测量数据作为建模数据集,1/3的测量数据作为测试数据集;2) 基于总体建模数据集,建立所有树种钻针平均阻力与木材绝干密度之间的线性模型、对数模型以及线性模型与对数模型相结合的混合模型,选用决定系数最高的模型形式作为总模型反映钻针平均阻力与木材绝干密度之间的关系;3) 基于软木类和硬木类建模数据集,使用选定的模型形式分别建立软木类和硬木类木材钻针平均阻力与木材绝干密度之间的类模型;4) 基于每个树种建模数据集,使用选定的模型形式建立每个树种钻针平均阻力与木材绝干密度之间的分模型;5)基于测试数据集,计算总模型、类模型和分模型的估计标准误差和平均估计精度,分析各级别模型之间估计标准误差和平均估计精度是否存在显著性差异。结果: 1) 基于总体建模数据集建立的线性模型、对数模型以及线性模型与对数模型相结合的混合模型的决定系数分别为0.942、0.952和0.961;2) 软木和硬木类模型的决定系数分别为0.780和0.864,分模型的决定系数在0.397~0.943之间;3) 总模型、类模型和分模型估计标准误差分别为32.222、31.635和27.121 kg ·m-3,平均估计精度分别为95.554%、95.636%和96.292%;4) 各树种总模型、类模型和分模型相互之间的估计标准误差和平均估计精度在0.1水平上均不存在显著性差异。结论: 1) 线性模型与对数模型相结合的混合模型的决定系数最高,采用线性模型与对数模型相结合的混合模型形式研究钻针阻力与木材绝干密度之间的关系较为合适;2) 分模型的估计标准误差最小,平均估计精度最高,采用分模型预估木材绝干密度较为合适;3) 当测量精度要求不高时,为降低建模工作量,可采用总模型估计木材绝干密度。

关键词: 木材密度, 微钻阻力法, 微损测量, 线性模型, 对数模型

Abstract:

Objective: At present, scholars mainly use linear model to study the relationship between drill resistance and wood density. There are great differences among the models, and the generality of the models is poor. This paper discusses the model form between drill resistance and wood density, and whether different tree species or similar tree species can share a mathematical model, in order to provide a basis for indirect measurement of wood density by micro drill resistance method. Method: 1) The resistance of 8 tree species including softwood and hardwood was measured by Resistograph 650-S. Two thirds of the measured data of each tree species was used as the modeling data set, and the remaining one third of the measured data was used as the test data set. 2)Using the total modeling data set, the linear model, logarithmic model and the mixed model of linear model and logarithmic model between the average drill resistance and wood absolute dry density were established respectively. The model with the highest determination coefficient was selected as the total model between the average drill resistance and wood absolute dry density, and the model form was selected to represent the relationship between drill needle resistance and wood absolute dry density. 3)The 2 class models of softwood and hardwood between drill resistance and absolute dry density were established by using the selected model form. 4)The sub models of each tree species between the average resistance of drill needles and absolute dry density were established respectively using the selected model form. 5)The test data set was used to test the estimation standard error and average estimation accuracy of the total model, class model and sub model. Result: 1) The determination coefficients of linear model, logarithmic model and mixed model of linear model and logarithmic model established using the total modeling data set are 0.942, 0.952 and 0.961 respectively. 2)The determination coefficients of softwood class model and hardwood class model are 0.780 and 0.864 respectively, and the determination coefficients of the sub model of each tree species are 0.397-0.943. 3)The total estimation standard errors of total model, class model and sub model are 32.222, 31.635 and 27.121 kg ·m-3 respectively, and the average estimation accuracy is 95.554%, 95.636% and 96.292% respectively. 4)There was no significant difference in the estimation standard error and average estimation accuracy among the total model, the class models and the sub models at the significance level of 0.1. Conclusion: 1) The mixed model of linear model and logarithmic model has the highest determination coefficient. Therefore, it is more appropriate to use the mixed model of linear model and logarithmic model to study the relationship between drill resistance and wood absolute dry density. 2)The estimation standard error of sub model is the smallest and the average estimation accuracy is the highest. Therefore, it is appropriate to use the sub model to predict the absolute dry density of wood. 3)When the measurement accuracy is not high, the total model can be used to estimate the absolute dry density of wood to reduce the modeling workload.

Key words: wood density, micro drill resistance method, micro destructive measurement, linear model, logarithmic model

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