Magnesite-bonded wood wool panel (MWWP) is an inorganic-bonded panel product in which wood excelsior is bonded with magnesite. Lowering the hygroscopicity is one of the key measures to improve the quality of the panel. In this study, moisture absorption mechanism of MWWP and measures generally applied to lower its hygroscopicity were reviewed. Three methods were then experimented to improve the dimensional stability of the panel, including adjusting the molar ratio of raw materials, adding additives and optimizing the conditioning process. The results showed that satisfying dimensional stability could be achieved when the molar ratio of MgO to MgCl2 was 5:1, the No.2 composite additive (aluminum powder + NH4H2PO4 + ferric alum) was adopted and a constant temperature and humidity treatment was applied in the first stage of conditioning.

为提高粉尘火焰/火花检测的可靠性,基于钾元素发射光谱设计木粉尘火焰/火花检测装置.利用粉尘蕴含元素受热会激发光谱特征为理论依据,采用高精度光谱元件、高速数模转换和控制芯片搭建检测装置,通过网口协议稳定传输获取的实时光谱特征.结果表明:采用上述方法能够获得明显的钾元素光谱,具有显著的光谱特征,可作为检测装置的检测依据.所设计的装置能迅速准确获得实时粉尘光谱状态,且成本低、精度高、体积小,可为预防粉尘燃爆事故的发生提供技术支撑.

设计了一种智能地板系统,包括由地板组成的成员组件和负责主控的控制组件构成.将包含有NRF2401的ARM控制器嵌入地板中赋予地板近距离无线通信,配合贴合在地板表面的压力传感器感知地板表面物体的压力点并向控制组件发送相应位置信息实现室内近距离定位;将地板和其他智能传感器有机结合,以实现温度监控、环境光强检测等功能.实物研究结果表明:基于NRF2401的地板可用于地面局部领域的定位需要,可将室内地板有机串联成一个整体,为后续地板智能化发展提供先行经验.

为解决木材加工厂所面临的粉尘爆炸事故威胁,保护人民群众的生命财产安全,丰富国内燃爆检测设备的种类并提高检测设备的检测效率和精度,通过研究粉尘爆炸五要素中的点火源发现粉尘燃烧时具备若干特征.燃爆产生初期粉尘处于炽热或者着火状态,前期研究发现,粉尘着火时会在钠、钾元素对应的波长范围内产生2个特殊的光谱特征.围绕这2个光谱特征,采用dsPIC作为控制芯片制作检测电路板,搭载硅型PIN光电二极管、LT1793和LT1012型运算放大器作为信号采集单元,通过二级放大电路来放大所捕获的火花信号,再由上位机和dsPIC决策最终的有效信息.为验证本装置是否具备实用性,联合第三方权威认证机构,依照国际标准搭建验证平台并进行了有效性检测.结果表明,本装置能够较为灵敏地对火花进行探测.认证结果表明,本装置最远可探测到75 cm距离的火花信号,是国际标准(15 cm)的5倍,且装置的反应时间低于520μs,远超德国某品牌设备的响应时间,符合企业使用需求.

The yield of sawn lumber has been largely governed by the identification accuracy of the external face width. However, the traditional method cannot measure the external face width with high accuracy and low error. In view of this, an image-based laser-triangulation width measurement model was established to measure the width of sawn lumber's external face in an effort to overcome the deficiency of the traditional method. A hypothesis was established from the theoretical model, as follows: when the laser line is cast on the external face and the reflected light is captured by the camera with a certain angle, the width resolution will be the least affected and will even depend on the resolution of the camera under precise conditions. Data from contrasting experiments suggested that a particular angle has a width-detection error 0.15% and accuracy 0.177 mm, which absolutely satisfies the need of wood industry detection online. Furthermore, this paper gives a theoretical proof of conjecture from the perspective of optical principles and mathematical analysis.

在已有的激光三角测厚技术的基础上提出了激光三角宽度测量的数学模型.模型认为宽度测量分辨率与被测试件宽度无关,与被测试件厚度存在线性关系,当激光和相机光轴的夹角满足一定条件时,宽度分辨率是个常数,此时模型精度最高.利用这个模型结合数字图像处理技术对九种常见规格的锯材试件进行504个样本宽度检测,结果显示毛边锯材外材面宽度识别相对误差率不到0.12%,误差均值在0.13 m m以内,所提模型是一种高精度新型非接触性检测外材面宽度的方法.