木材机械加工表面粗糙度的激光在线检测系统

介绍了一种采用计算机控制激光位移传感器在线检测木材机械加工表面粗糙度的新方法。该系统由计算机、模数转换板(A/D板)、激光传感器测量系统(激光头及激光控制器)等组成,试验研究是在木材加工CNC(Computer Numerical Control)装置上进行的。文中给出了硬件结构、软件程序设计流程图及木材表面粗糙度在线检测的实验数据。     

NEM－2型电容数字式木材刨花含水率测定仪

ＮＥＭ－２型电容数字式木材刨花含水率测定仪是为木材刨花板生产线而设计的，采用ＭＣＳ－５１单片机应用系统，利用频率测量法测定木材刨花通过电容传感器时由于含水率不同引起的电容的变化，从而测定了木材刨花的含水率。     

NEM—2型电容数字式木材刨花含水率测定仪

ＮＥＭ－２型电容数字式木材刨花含水率测定仪是为木材刨花板生产线而设计，采用ＭＣＳ－５１单片机应用系统，利用频率测量法测定木材刨花通过电容传感器时由于含水率不同引起的电容的变化，从而测定了木材刨花的含水率。     

木材表面缺陷的激光在线检测技术

本文介绍了采用激光位移传感器对刨削加工后的木材表面的裂纹及节子缺陷进行在线检测的方法。测试原理是利用激光位移传感器扫描木材表面，提供特征信号，由傅里叶分析仪FFT记录时间信号的波形，计算机进行数据处理和分析判断，这不仅可以快速识别裂纹及节子等缺陷，并从记录波形上即可计算出裂纹的宽度和深度。     

单片机在木材干燥控制系统中的应用

1 前 言 传统的木材干燥工艺一般采用电测理论确定温湿度系数,以实现干燥控制,其虽然比较直观,但缺点较多.随着单片机技术的不断发展,在木材干燥行业中也可以用单片机作为系统的核心处理部件。采用时间干燥基准,不但可克服传统工艺的缺点,有效地协调监测和控制,而且控制简单、功能强大、成本低、小巧实用.用户还可根据自己的需求添加外围电路及设备,开发出适合自己的智能电子产品.因此,单片机技术在木材干燥业中有着十分广阔的应用前景.     

基于GPS技术的木材采运系统设计

设计了一种基于GPS技术的木材采运系统,并给出了系统总体设计框图.设计了用于木材采运系统的GPS定位接收机,通过AT89C51单片机的控制作用,将定位点的三维信息和测量数据通过液晶显示器显示出来.     

炉气间接加热木材干燥窑微机控制系统

介绍一种以8031单片机为核心的木材干燥控制系统的功能与工作原理,描述了该系统中以8031单片机为核心的硬件系统、软件结构以及采取的抗干扰措施。该系统实际应用效果表明：它能按程序设定的要求对木材干燥过程进行精确控制,使干燥质量明显提高,干燥时间缩短10％～30％。     

木材的激光去除成型技术方法研究

采用由计算机，模数转换板（A／D板），激光传感器等组成的木材表面粗糙度在线检测系统，在CNC数控加工中心上对铣削加工的针叶材花旗松和阔叶材山毛榉进行了表面粗糙度RZ的在线检测。实验结果表明，该系统的检测数据是准确的，并具有高速在线测量等特点。     

激光切削在木材加工中的应用

本文综述了激光切削木材及木质材料的设备、切削机理．激光加工木材的优点及存在的问题，论述了影响激光切削的非设备方面的因素，列举了激光切削木材和木质材料的部分实例，以期为激光在木材加工中的研究及应用提供参考。     

不同数量传感器下云杉模拟缺陷材应力波成像规律探讨

以云杉原木圆盘为对象,研究不同面积、不同轮廓形状的空洞缺陷及用不同数量传感器情况时应力波成像技术检测缺陷图像与实际缺陷的关系.结果表明:应力波成像系统可以直观显示木材内部缺陷,其检测精度与空洞等实际缺陷面积和被测木材的截面积比率、使用传感器数量及空洞等缺陷轮廓形状有关;当空洞实际面积与被测木材截而积比从1.6％上升到25.0％时,应力波成像系统显示缺陷图像面积与实际缺陷面积相对误差从22.6％下降到9.7％;成像用传感器数量在6～24个之间时,应力波成像系统均能显示空洞等缺陷的存在,但成像用传感器的数量会影响检测精度;缺陷轮廓形状对应力波成像有一定影响,缺陷面积一定时,狭长形缺陷容易被检出,近圆形缺陷检测相对误差小.     

激光传感器定量测量木材表面粗糙度的研究

1IntroductionThe surface roughness of wood is one of the important parameters that can be used to operate the automatic woodcutting machinery,and alsoto evaluatethe quality of products . Withthe development of computertechnology,automaticmeasurement methods of the machined surface roughness have been proposed.Inrecent years ,newnon_contact methodshave been studiedto measure the roughness of machined surfaces .For example ,ultrasonic sensor was usedto measuringsurface roughness(Blessinget al.,…     

STUDY ON MEASUREMENT OF WOOD SURFACEROUGHNESS BY COMPUTER VISION

The working processes,machining devices and tools,cutting amount,consumptionof materials,productivity and quality of products are directly affected wood surface roughness.This paper gives an extensive review of methods used previously to measure wood surfaceroughness,and concludes that computer vision is the most suitable.The preliminarystudy shows that computer vinon method has the advantages of a noncontact,three--dimensionalmeasurement,high speed and well correlates with stylus tracing method.The method can be usedin classification and in-time measurement of wood surface roughness after being improved.     

Evaluation of surface smoothness by laser displacement sensor 1: effect of wood species

The best methods for determining surface roughness in an industrial environment are of the noncontact variety, with reproduction of the profile. The objective of this work was to compare the roughness profile obtained by a contact stylus with a commercial laser displacement sensor (LDS). Measurements were done using 15 wood species with different densities and colors, based on which special triangle profiles were prepared. The accuracy of the laser sensor was examined by statistical analysis of roughness parameters measured from the profiles. Experimental results show that LDS profiles were imitated correctly. However, LDS accuracy depends on the scanned wood properties (density and color), installation position of the sensor, and profile shape. It was found that evaluation of dark and high-density wooden surfaces was imperfect.Part of this work was presented at the 50th Annual Meeting of the Japan Wood Research Society, Kyoto, April 2000; and at the 51st Annual Meeting of the Japan Wood Research Society, Tokyo, April 2001     

Toward a process monitoring of CNC wood router. Sensor selection and surface roughness prediction

The measurement of wood surface roughness is performed once the machining process is completed. It requires considerable time since the measurement is performed at slow speed. The objective of this study was to develop a method to evaluate the surface roughness of paper birch wood while routing. For this purpose, a number of transducers were mounted on the router spindle and also in the proximity of the workpiece and cutting zone. Signals were acquired during a wide range of cutting conditions and analyzed. Statistical regression and artificial neural networks were employed to establish relationships between the signals and the actual cutting depth and surface roughness. The sensor selection and the feasibility of the sensor placement were determined. The models were subjected to a validation procedure to confirm their performance. The placement of the microphone at constant distance from the cutting zone was determined to be the most useful one. A model able to predict the surface roughness of routed paper birch wood regardless of the depth of cut was produced. The performance of the model was valid independently of the length of the workpiece.     

THE EFFECT OF WOOD SURFACE ROUGHNESS OF DIFFERENT SPECIES OF TREES ON WOOD COLOR IN WORKING OPERATION

Woodsurfaceroughnessisthemicrogeometrypropertycomposedbyalittlespacingandpeak-tovalley.Generallythesurfaceroughnesswascomposedbytheworkingmethodandotherfactorst123.Woodsurfaceroughnesswasnotonlyanimportantindexwhichmeasuredthesur-facesmoothextentofwoodproductandtheworkingqualitybutalsothewoodsur-fitceroughnessaffectedwoodsurfacefeel--lngandpsychologicalfeeling[3'4,lo,ll:.Th,'quantitativesurftlceproPertyparametersweretheimportantpartwhichmarkedthewoodsurfacevisualpsycho1ogicalmagni-tude,whichha…     

计算机视觉技术在木材工业科研与生产中的应用

本文讨论了计算机视沉技术在木材工业中的应用，介绍了计算机视觉的研究内容及系统的组成，分析了计算机视觉在木材科学，表面粗糙度，制浆，造纸，人造板和制材等加工研究中的应用方法和研究成果，并预测了计算机视觉技术在木材工业科研与生产中应用的发展趋势。     

基于分形维木材表面粗糙度的研究

应用分形维对木材表面粗糙度特征进行研究。首先，对Sarkar和Chaudhuri提出的分形维计算方法做了改进：其次，以60个树种为研究对象，提取和分析木材表面的分形维数。得出结论：分形维数能够反映木材表面的粗糙程度，可作为木材表面粗糙度的一种度量？     

木质材料表面粗糙度光学付立叶测量方法的研究

阐述了木质材料表面粗糙度现有的测量技术与研究现状，研究了木质材料表面的统计模型和一维高斯型木质材料表面光学付立叶变换谱强度分布的模型，并得到了计算木质材料表面粗糙度均方根误差和自相关函数的数学公式。测量两个参数的实验系统，将具有非接触、高测量速度、测量不受被测材料影响和能得到比较多的轮廓信息等优点，进一步完善后，可用于木质材料表面粗糙度的分类检测及监控。