Development of Intelligent Control and Testing of Particleboard Quality
-
摘要: 在国家“十四五”战略和“双碳”目标的共同引领下,刨花板产业蓬勃发展。将智能技术融入刨花板产业装备,实现刨花板生产检测智能一体化,提升刨花板智能装备水平,是促进刨花板工业增产和提质的有效手段。文中分析刨花板的质量缺陷和成因以及对应的生产工段,综合阐述在生产上易影响产品质量的施胶工段和热压工段的智能控制方法以及对刨花板密度和外观的先进检测技术,总结现阶段存在的不足,并从刨花板生产控制、产品检测、设备在线监测及智能生产线等方面对刨花板工业未来发展进行展望,为刨花板产业的绿色化、智能化、高质量发展提供参考。Abstract: Under the guidance of both the national strategies for “Fourteenth Five-Year Plan” and “carbon peaking and carbon neutrality” goal, the particleboard industry has flourished. It is an efficient approach to increase production and quality particleboard industry in which intelligent technology has been integrated into the equipment with the aim at realizing the intelligent integration of particleboard production and testing and improve intelligent equipment for particleboard production. In this paper, the defects of particleboard as well as the reasons for the defects and the corresponding section of production are analyzed. The intelligent control methods used in the gluing section and the hot-pressing section of production, which can easily affect product quality, as well as the advanced technology of particleboard density and appearance, are comprehensively expounded. The shortcomings found on the present stage are deeply summarized. The future development trends of particleboard industry are described in terms of the production control, product testing, online monitoring of equipment and intelligent production lines, which would provide references for the green, intelligent and high-quality development of particleboard industry.
-
Key words:
- particleboard /
- defect /
- intelligent control /
- product detection
-
表 1 刨花板产品外观质量检验等级评定标准及缺陷产生的原因
缺陷名称 优等品 合格品 产生原因 工段 分层鼓包 不允许 不允许 胶黏剂质量不合格,热压的时间、压力、温度设置不合理都有可能导致板材鼓包 施胶和热压 边部松软、残损 宽度≤1 cm、
深度≤5 mm,允许宽度≤3 cm、
深度≤2 cm,允许铺装板坯过干,结构强度低,铺装质量不易控制,表面细料极易被压机闭合气流吹掉;胶黏剂活性期短,刨花板毛坯在进入热压机之前提前固化,热压后边部出现松软,残损 铺装热压 板面粗糙、压痕、
有金属不允许 不允许 热压时钢带下夹杂异物或钢带本身不平整 铺装热压 板面波纹 触摸无手感,允许 触摸轻微有手感,允许 铺装时刨花分布不均使刨花板表面产生波浪状或鱼鳞状图案 铺装热压 密度不均 密度偏差<3% 密度偏差<4% 垂直于铺装方向上刨花板各点密度差超过工艺要求 铺装热压 漏砂 不允许 轻微漏沙,允许 因砂光量太大而使刨花板芯层大刨花裸漏 砂光 单个面积大于
40 mm2大刨花、
胶斑、油污斑等不允许 不允许 表面细料量不足,铺装后漏出芯层大刨花;铺装机内飞花捕捉网掉落或局部损坏撕裂;漏胶,铺装板坯上下结构不对称,出现板面大刨花,并造成板子翘曲 施胶和热压等 -
[1] 缪东玲, 岳宇慧, 陆婉樱. 基于嵌套logit模型的中国出口人造板产品质量分析[J]. 世界林业研究,2020,33(1):87 − 92. doi: 10.13348/j.cnki.sjlyyj.2019.0122.y [2] 柯美元, 成伟华, 王镜. 我国木工机械的智能化应用案例与发展目标[J]. 林业机械与木工设备,2018,46(2):4 − 9. doi: 10.3969/j.issn.2095-2953.2018.02.001 [3] 刘永焕. 基于低碳经济视角的中国刨花板产业浅析[J]. 林产工业,2020,57(7):104 − 106. doi: 10.19531/j.issn1001-5299.202007028 [4] 李东虎, 李万兆, 梅长彤. 定向刨花板抗弯性能、形变及剖面密度梯度的相关性[J]. 林业工程学报,2023,8(3):52 − 57. [5] 齐英杰, 赵越, 曲文, 等. 用科学发展观回顾并展望中国人造板机械制造行业[J]. 林业机械与木工设备,2013,41(4):4 − 14. doi: 10.3969/j.issn.2095-2953.2013.04.003 [6] 朱良宽, 程赛葛, 王沛煜, 等模型降阶的刨花板施胶自抗扰控制[J]. 控制工程, 2022, 29(4): 707 − 716. [7] 左玉虎. 基于plc的pid控制器在刨花板调供胶系统中的应用[J]. 科技信息,2011(28):108 − 109. doi: 10.3969/j.issn.1001-9960.2011.28.092 [8] 王金祥, 孙丽萍, 王松寒. 模糊免疫2dof pid在刨花板流量控制系统中的研究与仿真[J]. 机电产品开发与创新,2010,23(1):138 − 140. doi: 10.3969/j.issn.1002-6673.2010.01.056 [9] ZHU L K, QI X, WANG P Y. Adaptive fuzzy fractional order global sliding mode tracking control algorithm for particleboard glue system[J]. Processes, 2022, 10(4). DOI: 10.3390/pr10040719. [10] WANG P Y, ZHU L K, ZHANG C R, et al. Prescribed performance control with sliding-mode dynamic surface for a glue pump motor based on extended state observers[J]. Actuators, 2021, 10(11). DOI: 10.3390/act10110282. [11] 郭继宁, 孙丽萍, 曹军, 等. 优化自抗扰控制在刨花板施胶流量跟踪中的应用[J]. 东北林业大学学报,2021,49(6):119 − 123. doi: 10.3969/j.issn.1000-5382.2021.06.023 [12] LI H P, WANG X J, ZHANG C R. Heat transfer hot-pressing model of medium density fiberboard[C]. International Conference on Advanced Material and Manufacturing Science, Beijing, China, 2012. [13] LIU Y Q, WEI Y Y, JING W P, et al. Modeling and simulation comparison of real-time monitoring of particleboard hot-pressing thermal conductivity[C]//Proceedings of 2010 3rd International Conference on Computer and Electrical Engineering (ICCEE). Singapore: IACSIT Press, 2012. [14] 韩宇光, 曹军, 朱良宽. 刨花板热压控制系统模糊自适应pid控制[J]. 森林工程,2011,27(4):30 − 33. doi: 10.3969/j.issn.1001-005X.2011.04.009 [15] ZHANG W, WANG X W. Research on hot-pressing machine control system based on plc and kingview[C]. 27th Chinese Control and Decision Conference (CCDC), Qingdao, China, 2015. [16] 黄晓舟, 朱良宽, 曹军. 基于自适应遗传算法整定的刨花板热压系统pid控制[J]. 森林工程,2013,29(2):54 − 57. doi: 10.3969/j.issn.1001-005X.2013.02.012 [17] 张星梅, 戚玉涵, 任丁, 等. 基于预测控制的连续平压机热压板升降系统同步控制[J]. 林业科学,2020,56(6):83 − 93. [18] HILBERS U, THOEMEN H, HASENER J, et al. Effects of panel density and particle type on the ultrasonic transmission through wood-based panels[J]. Wood Science and Technology, 2012, 46(4):685 − 698. doi: 10.1007/s00226-011-0436-9 [19] 吴晓新, 施世明. 纤维/刨花板板坯面密度的自动检测与控制[J]. 木材工业,2006(1):34 − 36. doi: 10.19455/j.mcgy.2006.01.011 [20] ZAMBELLI N, ZANETTINI S, BENASSI G, et al. High performance czt detectors for in-line non-destructive x-ray based density measurements[C]. IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) / 25th International Symposium on Room-Temperature Semiconductor X-Ray and Gamma-Ray Detectors, Sydney, Australia, 2018. [21] KORAI H. Effects of density profile on bending strength of commercial particleboard[J]. Forest Products Journal, 2022, 72(2):85 − 91. doi: 10.13073/FPJ-D-21-00070 [22] ISTANA B, BATANI M L, SUTIKNO S, et al. Influence of particle size and bulk density on sound absorption performance of oil palm frond-reinforced composites particleboard[J]. Polymers, 2023, 15(3). DOI: 10.3390/polym15030510. [23] RIEGLER M, GINDL-ALTMUTTER W, HAUPTMANN M, et al. Detection of uf resin on wood particles and in particleboards: potential of selected methods for practice-oriented offline detection[J]. European Journal of Wood and Wood Products, 2012, 70(6):829 − 837. doi: 10.1007/s00107-012-0628-5 [24] YU Q L, ZHU H W, DU G B, et al. Rapid determination of urea formaldehyde resin content in wood fiber mat using near-infrared spectroscopy[J]. Bioresources, 2022, 17(3):4043 − 4054. doi: 10.15376/biores.17.3.4043-4054 [25] KIBLEUR P, BLYKERS B, BOONEM N, et al. Detecting thin adhesive coatings in wood fiber materials with laboratory-based dual-energy computed tomography (dect)[J]. Scientific Reports, 2022, 12(1):15969 − 15969. doi: 10.1038/s41598-022-20422-1 [26] 郭慧, 王霄, 刘传泽, 等. 基于灰度共生矩阵和分层聚类的刨花板表面图像缺陷提取方法[J]. 林业科学,2018,54(11):111 − 120. doi: 10.11707/j.1001-7488.20181116 [27] 郭慧, 盛振湘, 王霄, 等. 基于机器视觉的刨花板表面缺陷检测系统[J]. 木材工业,2019,33(3):18 − 22. doi: 10.19455/j.mcgy.20190305 [28] GUZAITIS J, VERIKAS A. An efficient technique to detect visual defects in particleboards[J]. Informatica, 2008, 19(3):363 − 376. doi: 10.15388/Informatica.2008.218 [29] 彭煜, 肖书浩, 阮金华, 等. 基于faster r-cnn的刨花板表面缺陷检测研究[J]. 组合机床与自动化加工技术,2020(3):91 − 94. [30] ZHAO Z Y, YANG X X, ZHOU Y C, et al. Real-time detection of particleboard surface defects based on improved YOLOV5 target detection[J]. Scientific Reports, 2021, 11(1). DOI: 10.1038/s41598-021-01084-x. -

计量
- 文章访问数: 30
- 被引次数: 0