1 INTRODUCTIONWood chip refining is the most critical step in mechanical pulping.Commercical experi-ences have been gained for years.Modelling and control of chip refiners,however,pose a challenge mainly because of th...1 INTRODUCTIONWood chip refining is the most critical step in mechanical pulping.Commercical experi-ences have been gained for years.Modelling and control of chip refiners,however,pose a challenge mainly because of the stochastic nature of the process.Some attemptshave been made to employ factor analysis technique[1]in the modelling andsimulating of refiner operation[2,3].Strand[2]used common factors as links betweenintrinsic fibre properties and pulp quality.He believed that a qualitative concept onthe physical nature of these common factors could be arrived at,and thus would helpto understand what refining variables need to be controlled or adjusted in order to im-prove pulp quality.However,the linear model used in factor analysis is based on theassumption that the interactions among the system variables are linear,which,ofcourse,is not true in practice.展开更多
To investigate the effects of temperature and moisture content(MC) on acoustic wave velocity(AWV)in wood,the relationships between wood temperature,MC,and AWV were theoretically analyzed.According to the theoretical p...To investigate the effects of temperature and moisture content(MC) on acoustic wave velocity(AWV)in wood,the relationships between wood temperature,MC,and AWV were theoretically analyzed.According to the theoretical propagation characteristics of the acoustic waves in the wood mixture and the differences in velocity among various media(including ice,water,pure wood or oven-dried wood),theoretical relationships of temperature,MC,and AWV were established,assuming that the samples in question were composed of a simple mixture of wood and water or of wood and ice.Using the theoretical model,the phase transition of AWV in green wood near the freezing point(as derived from previous experimental results) was plausibly described.By comparative analysis between theoretical and experimental models for American red pine(Pinus resinosa) samples,it was established that the theoretically predicted AWV values matched the experiment results when the temperature of the wood was below the freezing point of water,with an averageprediction error of 1.66%.The theoretically predicted AWV increased quickly in green wood as temperature decreased and changed suddenly near 0 °C,consistent with the experimental observations.The prediction error of the model was relatively large when the temperature of the wood was above the freezing point,probably due to an overestimation of the effect of the liquid water content on the acoustic velocity and the limited variables of the model.The high correlation between the predicted and measured acoustic velocity values in frozen wood samples revealed the mechanisms of temperature,MC,and water status and how these affected the wood(particularly its acoustic velocity below freezing point of water).This result also verified the reliability of a previous experimental model used to adjust for the effect of temperature during field testing of trees.展开更多
Because growth ring data have temporal features, time series analysis can be used to simulate and reveal changes in the life of a tree and contribute to plantation management. In this study, the autoregressive(AR) and...Because growth ring data have temporal features, time series analysis can be used to simulate and reveal changes in the life of a tree and contribute to plantation management. In this study, the autoregressive(AR) and moving average modeling method was used to simulate the time series for growth ring density in a larch plantation with different initial planting densities. We adopted the Box–Jenkins method for the modeling, which was initially based on an intuitive analysis of sequence graphs followed by the augmented Dickey–Fuller stationarity test. The order p and q of the ARMA(p, q) model was determined based on the autocorrelation and partial correlation coefficient figure truncated on the respective order.Through the residual judgment, the model AR(2) was only fitted to the larch growth ring density series for the plantation with the 1.5 9 2.0 m^2 initial planting density.Because the residuals series for the other three series was not shown as a white noise sequence, the modeling was rerun. Larch wood from the initial planting density of2.0 9 2.0 m^2 was modeled by ARMA(2, 1), and ARMA((1, 5), 3) fitted to the 2.5 9 2.5 m^2 initial planting density,and the 3.0 9 3.0 m^2 was modeled by AR(1, 2, 5).Although the ARMA modeling can simulate the change in growth ring density, data for the different growth ring time series were described by different models. Thus, time series modeling can be suitable for growth ring data analysis, revealing the time domain and frequency domain of growth ring data.展开更多
In this paper, according to the theory and method of time-series analysis, the grow ing rings ARIMA model of wood properties variation pattern for Larix olgensis plantation was studied. The model recognition and param...In this paper, according to the theory and method of time-series analysis, the grow ing rings ARIMA model of wood properties variation pattern for Larix olgensis plantation was studied. The model recognition and parameter estimation were discused. The ARIMA model of wood growth ring density, growth ring widith and late wood percentage was obtained. Appling the ARIMA model which obtained from actual test fitted the variation pattem of wood growth ring for Larix olgensis. The result indicated it was an effective method that applied the ARIMA model to study wood growth ring properties variation pattem. By comparing with the actual variation pattem from test data the goodness of fit was good.展开更多
木材密度包括基本密度、气干密度等,在12%含水率条件下的气干密度(D12)较常用,因此有必要将木材气干密度换算为基本密度(Db)。目前利用木材气干密度计算基本密度的模型有Reyes、Chave、Simpson和Vieilledent模型等,然而这些模型预测结...木材密度包括基本密度、气干密度等,在12%含水率条件下的气干密度(D12)较常用,因此有必要将木材气干密度换算为基本密度(Db)。目前利用木材气干密度计算基本密度的模型有Reyes、Chave、Simpson和Vieilledent模型等,然而这些模型预测结果不完全一致。利用中国林业科学研究院木材工业研究所(Research Institute of Wood Industry,Chinese Academy of Forestry,CRIWI)和法国农业国际合作研究发展中心(French Agricultural Research Centre for International Development,CIRAD)的木材D12和Db数据,首先基于CRIWI的木材密度数据建立D12与Db的关系模型,然后将CRIWI和CIRAD的D12数据分别代入Reyes模型、Chave模型、Simpson模型、Vieilledent模型和新建模型,获得每个树种木材Db的预测值,并根据Db预测值和实测值计算残差绝对值均值。不同模型残差绝对值均值比较结果表明:Reyes模型在利用CRIWI和CIRAD的木材密度数据时预测Db的准确性都比较高,适用性最广;Simpson模型、新建模型在D12高于1.0 g/cm3时预测Db的准确性降低。展开更多
文摘1 INTRODUCTIONWood chip refining is the most critical step in mechanical pulping.Commercical experi-ences have been gained for years.Modelling and control of chip refiners,however,pose a challenge mainly because of the stochastic nature of the process.Some attemptshave been made to employ factor analysis technique[1]in the modelling andsimulating of refiner operation[2,3].Strand[2]used common factors as links betweenintrinsic fibre properties and pulp quality.He believed that a qualitative concept onthe physical nature of these common factors could be arrived at,and thus would helpto understand what refining variables need to be controlled or adjusted in order to im-prove pulp quality.However,the linear model used in factor analysis is based on theassumption that the interactions among the system variables are linear,which,ofcourse,is not true in practice.
基金funded by the National Natural Science Foundation of China(Grant Nos.31600453 and 31570547)Fundamental Research Funds for the Central Universities(Grant No.2572017EB02)Natural Science Foundation of Heilongjiang Province,China(Grant No.C201403)
文摘To investigate the effects of temperature and moisture content(MC) on acoustic wave velocity(AWV)in wood,the relationships between wood temperature,MC,and AWV were theoretically analyzed.According to the theoretical propagation characteristics of the acoustic waves in the wood mixture and the differences in velocity among various media(including ice,water,pure wood or oven-dried wood),theoretical relationships of temperature,MC,and AWV were established,assuming that the samples in question were composed of a simple mixture of wood and water or of wood and ice.Using the theoretical model,the phase transition of AWV in green wood near the freezing point(as derived from previous experimental results) was plausibly described.By comparative analysis between theoretical and experimental models for American red pine(Pinus resinosa) samples,it was established that the theoretically predicted AWV values matched the experiment results when the temperature of the wood was below the freezing point of water,with an averageprediction error of 1.66%.The theoretically predicted AWV increased quickly in green wood as temperature decreased and changed suddenly near 0 °C,consistent with the experimental observations.The prediction error of the model was relatively large when the temperature of the wood was above the freezing point,probably due to an overestimation of the effect of the liquid water content on the acoustic velocity and the limited variables of the model.The high correlation between the predicted and measured acoustic velocity values in frozen wood samples revealed the mechanisms of temperature,MC,and water status and how these affected the wood(particularly its acoustic velocity below freezing point of water).This result also verified the reliability of a previous experimental model used to adjust for the effect of temperature during field testing of trees.
基金financially supported by the National Sci-Tech Support Plan of China(Grant No.2015BAD14B05)
文摘Because growth ring data have temporal features, time series analysis can be used to simulate and reveal changes in the life of a tree and contribute to plantation management. In this study, the autoregressive(AR) and moving average modeling method was used to simulate the time series for growth ring density in a larch plantation with different initial planting densities. We adopted the Box–Jenkins method for the modeling, which was initially based on an intuitive analysis of sequence graphs followed by the augmented Dickey–Fuller stationarity test. The order p and q of the ARMA(p, q) model was determined based on the autocorrelation and partial correlation coefficient figure truncated on the respective order.Through the residual judgment, the model AR(2) was only fitted to the larch growth ring density series for the plantation with the 1.5 9 2.0 m^2 initial planting density.Because the residuals series for the other three series was not shown as a white noise sequence, the modeling was rerun. Larch wood from the initial planting density of2.0 9 2.0 m^2 was modeled by ARMA(2, 1), and ARMA((1, 5), 3) fitted to the 2.5 9 2.5 m^2 initial planting density,and the 3.0 9 3.0 m^2 was modeled by AR(1, 2, 5).Although the ARMA modeling can simulate the change in growth ring density, data for the different growth ring time series were described by different models. Thus, time series modeling can be suitable for growth ring data analysis, revealing the time domain and frequency domain of growth ring data.
文摘In this paper, according to the theory and method of time-series analysis, the grow ing rings ARIMA model of wood properties variation pattern for Larix olgensis plantation was studied. The model recognition and parameter estimation were discused. The ARIMA model of wood growth ring density, growth ring widith and late wood percentage was obtained. Appling the ARIMA model which obtained from actual test fitted the variation pattem of wood growth ring for Larix olgensis. The result indicated it was an effective method that applied the ARIMA model to study wood growth ring properties variation pattem. By comparing with the actual variation pattem from test data the goodness of fit was good.
文摘木材密度包括基本密度、气干密度等,在12%含水率条件下的气干密度(D12)较常用,因此有必要将木材气干密度换算为基本密度(Db)。目前利用木材气干密度计算基本密度的模型有Reyes、Chave、Simpson和Vieilledent模型等,然而这些模型预测结果不完全一致。利用中国林业科学研究院木材工业研究所(Research Institute of Wood Industry,Chinese Academy of Forestry,CRIWI)和法国农业国际合作研究发展中心(French Agricultural Research Centre for International Development,CIRAD)的木材D12和Db数据,首先基于CRIWI的木材密度数据建立D12与Db的关系模型,然后将CRIWI和CIRAD的D12数据分别代入Reyes模型、Chave模型、Simpson模型、Vieilledent模型和新建模型,获得每个树种木材Db的预测值,并根据Db预测值和实测值计算残差绝对值均值。不同模型残差绝对值均值比较结果表明:Reyes模型在利用CRIWI和CIRAD的木材密度数据时预测Db的准确性都比较高,适用性最广;Simpson模型、新建模型在D12高于1.0 g/cm3时预测Db的准确性降低。
