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Cracking the code: real-time monitoring of wood drying and the occurrence of cracks
Wood Science and Technology ( IF 3.1 ) Pub Date : 2020-07-01 , DOI: 10.1007/s00226-020-01200-6
H. P. Botter-Kuisch , J. Van den Bulcke , J. M. Baetens , J. Van Acker

Predicting kiln-drying schedules for a given wood species is not yet possible, despite many research efforts. This is mainly due to insufficiently considering important spatio-temporal variables such as moisture and temperature gradients, and wood anatomical features during drying in the predictive modelling framework. To understand the influence of aforementioned variables, an experimental measurement set-up was developed consisting of heat-resistant load cells mounted in an oven to record the weight of the wood specimens dried at 100 °C. A camera was mounted outside the oven to acquire images of the end grain through the transparent door of the oven, as such enabling to monitor the occurrence of cracks. Furthermore, custom-made electrodes were inserted as well at different depths in the specimen to measure the electrical resistance, which relates to the moisture content. Specimens were also equipped with thermistors to record the temperature in the specimens at different depths from the surface. Heat-resistant wires from load cells, electrodes and thermistors were connected with data loggers outside the oven. Three specimens of basralocus ( Dicorynia guianensis ) were selected, measuring 50 mm wide, 50 mm thick and 120 mm long. The results show that it is possible to real-time monitor average moisture loss, local moisture content gradient represented by the electrical resistance gradient and wood temperature gradient as a function of time. These temporally resolved gradients can be related to the occurrence of cracks. This methodology enables to unveil interrelationships between the measured variables and changes of the wood anatomical structure, of utmost importance for the fine-tuning of kiln-drying schedules.

中文翻译:

破解代码:实时监控木材干燥和裂纹的发生

尽管进行了许多研究,但仍无法预测给定木材种类的窑干时间表。这主要是由于在预测建模框架中没有充分考虑重要的时空变量,例如水分和温度梯度,以及干燥过程中木材的解剖特征。为了了解上述变量的影响,开发了一种实验测量装置,该装置由安装在烤箱中的耐热称重传感器组成,用于记录在 100 °C 下干燥的木材样品的重量。一个摄像头安装在烤箱外面,通过烤箱的透明门获取最终谷物的图像,这样就可以监控裂纹的发生。此外,还将定制的电极插入样品的不同深度以测量电阻,这与水分含量有关。样品还配备了热敏电阻,以记录距表面不同深度的样品中的温度。来自称重传感器、电极和热敏电阻的耐热电线与烤箱外的数据记录器相连。选择了3个basralocus(Dicorynia guianensis)标本,宽50毫米,厚50毫米,长120毫米。结果表明,可以实时监测平均水分损失、由电阻梯度表示的局部水分含量梯度和作为时间函数的木材温度梯度。这些时间分辨的梯度可能与裂纹的出现有关。这种方法能够揭示测量变量与木材解剖结构变化之间的相互关系,
更新日期:2020-07-01
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