LIN Yixin, CHEN Dandan, LIU Hongbo, et al. Identification of key amino acid residues controlling the activities of glycerol-3-phosphate acyltransferases in Arabidopsis thaliana and Brassica napus[J]. Journal of Zhejiang A&F University, 2023, 40(4): 695-706. DOI: 10.11833/j.issn.2095-0756.20220764
Citation: HU Xiaojun, TIAN Ze, XU Yunjie, et al. Effect of milling parameters on cutting force and quality of vascular bundle fiber extraction in bamboo[J]. Journal of Zhejiang A&F University, 2025, 42(X): 1−9 doi:  10.11833/j.issn.2095-0756.20240536

OnlineFirst articles are published online before they appear in a regular issue of the journal. Please find and download the full texts via CNKI.

Effect of milling parameters on cutting force and quality of vascular bundle fiber extraction in bamboo

DOI: 10.11833/j.issn.2095-0756.20240536
  • Received Date: 2024-09-11
  • Accepted Date: 2024-12-20
  • Rev Recd Date: 2024-12-13
  •   Objective  This study aims to explore the optimal cutting parameters for cutting force and extraction quality when extracting bamboo (Phyllostachys edulis) vascular bundle fibers by milling, and provide theoretical reference for efficient acquisition of high-quality natural vascular bundle fibers with uniform thickness and good consistency in length and size.   Method  Cutting speed (Vc), feed per tooth (fz), and cutting depth (Ap) were taken as variables, unidirectional milling and orthogonal cutting experiments were conducted on bamboo boards using a double-edged straight groove hard alloy woodworking carving knife. The influence of cutting parameters on cutting force was verified by range analysis and variance analysis. The experimental data were analyzed by multivariate nonlinear regression method to establish an empirical formula for cutting force. Based on transient cutting geometric model and single-factor experiments, the effects of cutting speed, cutting depth, and feed per tooth on the quality of vascular bundle fiber extraction were investigated.   Result  During the cutting process, only X-Y-directional cutting forces were generated on the workpiece, while the Z-directional cutting force continuously fluctuated near zero value. Cutting depth had an extremely significant impact on cutting force. Within the X-Y plane, cutting force mainly acted along parallel the feed direction of the tool, and feed per tooth had a more significant influence on cutting force than cutting speed. The vertical tool feed direction was mainly affected by extrusion force, and cutting speed had a more significant effect on cutting force than feed per tooth. The coefficient of determination (R2) of nonlinear regression equation for cutting force along the tool feed direction was 0.956, which could accurately predict the magnitude of cutting force. The determination coefficient of the nonlinear regression equation for cutting force in the vertical tool feed direction was 0.697, but the error between its predicted and theoretical value was within ±5 N, reflecting the overall trend of cutting force in this direction. The error between the average fiber length obtained by milling and the target length was within ±0.1 mm. Within the range of cutting parameters, when cutting parameters were Vc=188.5 m·min−1, Ap=12 mm, and fz=0.2 mm, vascular bundle fibers with larger diameters and higher aspect ratio were obtained.   Conclusion  Cutting depth is the most important factor affecting the magnitude of cutting force. In the parallel tool feed direction, feed per tooth has a greater impact on cutting force than cutting speed. In the vertical tool feed direction, cutting speed has a greater impact on cutting force than feed per tooth. The nonlinear regression model of cutting force can accurately calculate cutting force in various directions and the overall trend of change. The milling method can accurately control the target length of vascular bundle fibers. Higher cutting speed, greater cutting depth, and smaller feed per tooth can help obtain vascular bundle fibers with larger aspect ratio and diameters. [Ch, 9 fig. 5 tab. 26 ref.]
  • [1] NIU Sijie, WANG Na, CUI Baixiang, WANG Chuangui, WU Heng, ZHANG Shuangyan.  Effects of different ages and positions on fiber morphology and crystallinity of Phyllostachys edulis . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.20220749
    [2] LI Rongrong, HE Chujun, PENG Bo, WANG Chuangui.  Differences in fiber morphology and partial physical properties in different parts of Phyllostachys edulis . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.20200649
    [3] LI Congcong, PAN Biao, WANG Hui, HUANG Libin.  Fiber morphology, microfibril angle and crystallinity of American red oak introduced . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2020.01.021
    [4] YIN Huanhuan, LIU Qinghua, ZHOU Zhichun, WAN Xueqin, YU Qixin, FENG Zhongping.  Genetic variation of wood basic density and fiber morphology and selection of Pinus massoniana . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.20190720
    [5] LI Yuanyuan, ZHANG Shuangyan, WANG Chuangui, FANG Xuqin.  Chemical composition, fiber morphology, and pulping properties of logging residues in Phyllostachys edulis . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2019.02.002
    [6] CAO Tingting, HOU Shoupeng, YUAN Xiaodong, HE Ying.  Trapping termites with cellulose bait . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2018.01.024
    [7] LI Weiguang, ZHANG Zhankuan.  Modeling the cutting force in wood sawing with different radial clearance angles based on a response surface methodology . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2018.03.018
    [8] FENG Chen, TONG Hongtuo, WANG Haoqing, LIU Changjie, QIAN Jun.  Surface coating technology for medium density fiberboard . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2017.05.019
    [9] PHAM Tuong Lam, WANG Xinzhou, DENG Yuhe, DONG Geping, TRAN Minh Toi, CAO Quoc An.  Characteristics of recycled poplar cement formwork fiber and its fiberboard manufacturing . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2014.06.017
    [10] XU Xiuyu, WANG Minghuai, ZHONG Chonglu, ZHANG Huaxin.  Wood properties and anti-typhoon performance in selected trees . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2014.05.014
    [11] LIU Xiaoling, FU Yunlin.  Anatomy and basic density of Tsoongiodendron odorum . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2013.05.021
    [12] LI Xiaoping, WU Zhangkang, ZHANG Congjie.  Physical properties of tobacco stalk fibers along the stem . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2013.04.014
    [13] YANG Xiao-jun, SUN You-fu.  Shear creep properties for the bond layer at the wood-CFRP interface . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2012.02.007
    [14] SU Wen-hui, FAN Shao-hui, PENG Ying, YU You-ming, ZHANG Da-peng.  Fiber forms and tissue measurements of Bambusa sinospinosaBambusablumeana and Dendrocalamus yunnanicus stem . Journal of Zhejiang A&F University, doi: 10.11833/j.issn.2095-0756.2011.03.007
    [15] LI Xiao-ping, ZHOU Ding-guo, ZHOU Xu-bin, WANG Wei, SHAO Yi.  Microstructure and fiber size of the castor-oil plant . Journal of Zhejiang A&F University,
    [16] WANG Shu-guang, PU Xiao-lan, DING Yu-long, WAN Xian-chong, LIN Shu-yan.  Morphological differences of Fargesia yunnanensis fibers . Journal of Zhejiang A&F University,
    [17] Yu Xuejun, Han Hong, Tian Jingxiang, Wang Rendong, Zhou Yingchun..  FiberMorphology and Basic Density of Fast-growing Chinese Fir From Zhejiang. . Journal of Zhejiang A&F University,
    [18] Lou Luhuan, Li Genyou, Lü Zhengshui, XuYaoling, Zhang Daogou..  Characteristics of Vascular Plant Flora of Taishun County . Journal of Zhejiang A&F University,
    [19] Lü Zhengshui, Dong Zhixiao, Xu Liuyang, Lou Luhuan, Li Genyou, Yang Caijin, Zhou Hongqing.  A List of Vascular Plants in Taishun County . Journal of Zhejiang A&F University,
    [20] Ma Lingfei, Han Hong, Ma Naixun, .  . Journal of Zhejiang A&F University,
  • [1]
    YAN Shi, YANG Zhengyong, ZHOU Xiaojian, et al. Effects of bamboo age and longitudinal position on wood and fiber properties of Bambusa blumeana[J]. Journal of Zhejiang A&F University, 2024, 41(4): 861−869.
    [2]
    LI Wenting, LI Mingpeng, CHENG Haitao, et al. Development of environmentally friendly and efficient bamboo fiber processing[J]. Scientia Silvae Sinicae, 2022, 58(11): 160−173.
    [3]
    NIU Sijie, WANG Na, CUI Baixiang, et al. Effects of different ages and positions on fiber morphology and crystallinity of Phyllostachys edulis[J]. Journal of Zhejiang A&F University, 2023, 40(2): 446−452.
    [4]
    LI Weilin, LIN Weisheng, YANG Wen, et al. Preparation and structure characterization of bamboo fiber by alkali-boiling and NaCIO oxidation[J]. China Forest Products Industry, 2021, 58(1): 6−10.
    [5]
    WANG Chunhong, CHEN Zhen, LI Yuanping, et al. Classified extraction and properties of bamboo fiber[J]. Journal of Textile Research, 2017, 38(11): 9−15.
    [6]
    HUANG Hui, WANG Yu, SUN Fengwen, et al. Effect of splitting method on bamboo fiber extraction and its mechanical properties[J]. Journal of Forestry Engineering, 2016, 1(6): 23−28.
    [7]
    SHU Biqing, REN Qin, HE Qian, et al. Study on the formation cause of binderless hybrid fiberboard based on steam explosion method[J]. Journal of Yangzhou University (Natural Science Edition), 2020, 23(1): 54−58, 67.
    [8]
    LUO Hai, YUE Lei, WANG Naiwen, et al. Manufacture of binderless fiberboard made from bamboo processing residues by steam explosion pretreatment[J]. Wood Research, 2014, 59(5): 861−870.
    [9]
    YANG Yongfu, XI Baotian, LI Li. Study on the effects of cutting parameters for bamboo on cutting forces[J]. Wood Processing Machinery, 2005(3): 13−15.
    [10]
    GUO Yingjie, YANG Yongfu. Study on the effects of milling parameters for moso bamboo on its surface roughness[J]. China Forest Products Industry, 2009, 36(4): 21−23.
    [11]
    GUO Yingjie, YANG Yongfu, BAI Xue. Effects of milling parameters for moso bamboo on its advance splitting[J]. Journal of Beijing Forestry University, 2009, 31 (suppl 1): 193−196.
    [12]
    OGAWA K, HIROGAKI T, AOYAMA E, et al. Fabrication of binder-free green composite using bamboo fibers extracted with a machining center[J]. Key Engineering Materials, 2010, 447−448: 760−764.
    [13]
    OGAWA K, HIROGAKI T, AOYAMA E, et al. Bamboo fiber extraction method using a machining center[J]. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2008, 2(4): 550−559.
    [14]
    XUE Hao, XU Can, BAI Tian, et al. Preparation and interfacial modification of bamboo fiber/epoxy resin composites via RTM process[J]. Journal of Northeast Forestry University, 2020, 48(12): 106−111, 123.
    [15]
    ZHAO He, MIAO Qingxian, HUANG Liulian, et al. Preparation of long bamboo fiber and its reinforced polypropylene membrane composites[J]. Journal of Forestry Engineering, 2021, 6(5): 96−103.
    [16]
    HAN Yutong, WANG Kuang, BU Xiangting, et al. Long bamboo fiber bundle directional reinforced polypropylene composite[J]. Packaging Engineering, 2022, 43(13): 17−23.
    [17]
    ZHAN Shaobin, MAO Qianxin, TONG Wenxuan, et al. Effect of length-diameter ratios and contents of bamboo riber on properties of epoxy resin based composites[J]. China Plastics Industry, 2019, 51 (12): 82−87.
    [18]
    CHEN Hainiao, TIAN Wei, JIN Xiaoke, et al. Analysis on cross-sectional structure of moso bamboo using three-dimensional microscope imaging[J]. Journal of Textiles Research, 2021, 42(12): 49−54.
    [19]
    YUAN Jing, ZHANG Xuexia, YU Yan, et al. Effects of the distribution and structure of vascular bundles on the compressive properties of bamboo[J]. Journal of Central South University of Forestry & Technology, 2019, 39(6): 121−127.
    [20]
    SHANG Lili, SUN Zhengjun, JIANG Zehui, et al. Variation and morphology of vascular bundle in moso bamboo[J]. Scientia Silvae Sinicae, 2012, 48(12): 16−21.
    [21]
    GUO Xiaolei, ZHU Nanfeng, WANG Jie, et al. Effect of cutting speed and chip thickness on cutting forces and surface roughness of fiberboard[J]. Journal of Forestry Engineering, 2016, 1(4): 114−117.
    [22]
    JIANG Rongsheng, GUO Xiaolei, CAO Pingxiang. Effect of spindle speed and milling tool rake angle on cutting forces and surface roughness of wood plastic composites[J]. Journal of Forestry Engineering, 2022, 7(3): 144−149.
    [23]
    SUN Chenggang, ZHU Mengnan, GUO Xiaolei. Effect of cutting tool angle on surface quality of wood-plastic composite[J]. Forestry Science and Technology, 2023, 48(5): 51−55.
    [24]
    LI Li. Principles of Wood Cutting and Cutter Tools[M]. Beijing: China Forestry Publishing House, 2024.
    [25]
    WANG Li, JIANG Zenghui, WANG Shuli, et al. Simulation study of influence of cutting parameters on cutting force of 316H stainless steel[J]. Manufacturing Technology & Machine Tool, 2022(6): 80−83.
    [26]
    ZHAO Xiaojin, LIANG Zhidong, SHAO Lijie, et al. Analysis and evaluation on nonlinear regression function of SPSS software[J]. Statistics & Decision, 2021, 37(23): 20−22.
  • Created with Highcharts 5.0.7Amount of accessChart context menuAbstract Views, HTML Views, PDF Downloads StatisticsAbstract ViewsHTML ViewsPDF Downloads2024-052024-062024-072024-082024-092024-102024-112024-122025-012025-022025-032025-040Highcharts.com
    Created with Highcharts 5.0.7Chart context menuAccess Class DistributionFULLTEXT: 21.3 %FULLTEXT: 21.3 %META: 76.2 %META: 76.2 %PDF: 2.5 %PDF: 2.5 %FULLTEXTMETAPDFHighcharts.com
    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 9.7 %其他: 9.7 %其他: 1.1 %其他: 1.1 %Baden: 0.3 %Baden: 0.3 %Brazil: 0.3 %Brazil: 0.3 %Canada: 0.3 %Canada: 0.3 %China: 1.8 %China: 1.8 %Edinburg: 0.2 %Edinburg: 0.2 %Egypt: 0.2 %Egypt: 0.2 %Elizabeth City: 0.1 %Elizabeth City: 0.1 %Italy: 0.1 %Italy: 0.1 %Philippines: 0.5 %Philippines: 0.5 %Russian Federation: 0.1 %Russian Federation: 0.1 %Seattle: 0.1 %Seattle: 0.1 %United States: 0.2 %United States: 0.2 %Wixom: 0.2 %Wixom: 0.2 %[]: 3.1 %[]: 3.1 %上海: 0.7 %上海: 0.7 %东莞: 0.1 %东莞: 0.1 %临汾: 0.1 %临汾: 0.1 %丹佛: 0.3 %丹佛: 0.3 %休斯敦: 0.5 %休斯敦: 0.5 %保定: 0.1 %保定: 0.1 %北京: 9.7 %北京: 9.7 %北伯根: 0.1 %北伯根: 0.1 %匹兹堡: 0.2 %匹兹堡: 0.2 %南京: 0.2 %南京: 0.2 %南昌: 0.1 %南昌: 0.1 %博阿努瓦: 0.1 %博阿努瓦: 0.1 %卢瓦尔: 0.2 %卢瓦尔: 0.2 %厦门: 0.1 %厦门: 0.1 %台州: 0.1 %台州: 0.1 %合肥: 0.1 %合肥: 0.1 %哥伦布: 0.1 %哥伦布: 0.1 %嘉兴: 0.6 %嘉兴: 0.6 %坦佩: 0.2 %坦佩: 0.2 %士嘉堡: 0.2 %士嘉堡: 0.2 %天津: 0.1 %天津: 0.1 %娄底: 0.1 %娄底: 0.1 %密蘇里城: 0.6 %密蘇里城: 0.6 %广州: 0.5 %广州: 0.5 %张家口: 1.7 %张家口: 1.7 %徐州: 0.1 %徐州: 0.1 %德国: 0.1 %德国: 0.1 %成都: 0.4 %成都: 0.4 %扬州: 0.1 %扬州: 0.1 %拉雷多: 0.1 %拉雷多: 0.1 %昆明: 0.2 %昆明: 0.2 %晋城: 0.1 %晋城: 0.1 %杭州: 3.7 %杭州: 3.7 %杭州市拱墅区: 0.1 %杭州市拱墅区: 0.1 %森尼韦尔: 0.2 %森尼韦尔: 0.2 %武汉: 0.3 %武汉: 0.3 %洛杉矶: 0.4 %洛杉矶: 0.4 %洛阳: 0.1 %洛阳: 0.1 %济南: 0.1 %济南: 0.1 %深圳: 0.3 %深圳: 0.3 %温州: 0.2 %温州: 0.2 %漯河: 0.6 %漯河: 0.6 %潍坊: 0.1 %潍坊: 0.1 %百色: 0.1 %百色: 0.1 %石家庄: 0.5 %石家庄: 0.5 %福州: 0.1 %福州: 0.1 %纽瓦克: 0.3 %纽瓦克: 0.3 %绍兴: 0.3 %绍兴: 0.3 %美国密歇根大急流城: 0.2 %美国密歇根大急流城: 0.2 %芒廷维尤: 8.0 %芒廷维尤: 8.0 %芜湖: 0.1 %芜湖: 0.1 %芝加哥: 0.3 %芝加哥: 0.3 %苏州: 0.3 %苏州: 0.3 %西宁: 41.7 %西宁: 41.7 %西安: 0.1 %西安: 0.1 %贵阳: 0.1 %贵阳: 0.1 %贺州: 0.1 %贺州: 0.1 %运城: 2.3 %运城: 2.3 %邯郸: 0.1 %邯郸: 0.1 %邵阳: 0.1 %邵阳: 0.1 %郑州: 0.9 %郑州: 0.9 %重庆: 0.2 %重庆: 0.2 %金华: 0.6 %金华: 0.6 %长沙: 0.7 %长沙: 0.7 %长治: 0.1 %长治: 0.1 %阳泉: 0.5 %阳泉: 0.5 %阿布奎基: 0.2 %阿布奎基: 0.2 %青岛: 0.2 %青岛: 0.2 %马鞍山: 0.1 %马鞍山: 0.1 %黔西南: 0.1 %黔西南: 0.1 %其他其他BadenBrazilCanadaChinaEdinburgEgyptElizabeth CityItalyPhilippinesRussian FederationSeattleUnited StatesWixom[]上海东莞临汾丹佛休斯敦保定北京北伯根匹兹堡南京南昌博阿努瓦卢瓦尔厦门台州合肥哥伦布嘉兴坦佩士嘉堡天津娄底密蘇里城广州张家口徐州德国成都扬州拉雷多昆明晋城杭州杭州市拱墅区森尼韦尔武汉洛杉矶洛阳济南深圳温州漯河潍坊百色石家庄福州纽瓦克绍兴美国密歇根大急流城芒廷维尤芜湖芝加哥苏州西宁西安贵阳贺州运城邯郸邵阳郑州重庆金华长沙长治阳泉阿布奎基青岛马鞍山黔西南Highcharts.com
  • Cited by

    Periodical cited type(12)

    1. 陈昱舟. 浙江省未来乡村建设典型案例分析——基于桐乡市荣星村的调查. 现代农机. 2024(04): 36-38 .
    2. 孔祥文,商楠,于墨涵,申超,刘一鸣. 生态产业引领发展的植物园景观规划探析——以岳阳植物园为例. 城市建筑. 2024(20): 214-220 .
    3. 隋洁. 乡村振兴背景下乡村景观环境中的艺术介入研究. 绿色科技. 2023(09): 51-56+70 .
    4. 何思笑,张建国. 浙江省森林康养品牌资源空间分布特征及其影响因素. 浙江农林大学学报. 2022(01): 180-189 . 本站查看
    5. 何圣博,丁昶. 人居环境科学视角下乡村景观营造研究——以徐州市三座楼村为例. 城市建筑. 2022(05): 16-20 .
    6. 邹初红. 基于特征约束的乡村景观植物布局规划模型. 河北北方学院学报(自然科学版). 2022(05): 55-60 .
    7. 赵丹萍,聂文彬,黄若之. 认知发展理论下的乡村公共空间景观营建策略. 山西建筑. 2022(13): 40-44 .
    8. 王能洲,周昭英. 基于产业导向的城市建设策略——以南京江北新区为例. 城市. 2022(09): 3-13 .
    9. 刘世芳. 新型城镇化背景下乡村产业与景观环境生态分析. 美与时代(城市版). 2022(10): 126-128 .
    10. 霍晓姝,熊艳,王艳辉. 林业科技推广在林业产业发展中的应用探讨. 林产工业. 2021(04): 84-86 .
    11. 杨炎坤,朱箫笛. 家具企业盈利模式问题及对策分析. 林产工业. 2021(05): 83-85 .
    12. 赵勇强,马明,赵莉莉,雷占礼. 国土空间规划背景下田园综合体创新模式与发展路径探究——以内蒙古土默特右旗大雁滩田园综合体为例. 西北师范大学学报(自然科学版). 2021(04): 93-100+127 .

    Other cited types(10)

通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(9)  / Tables(5)

Article views(32) PDF downloads(0) Cited by(22)

Related
Proportional views

Effect of milling parameters on cutting force and quality of vascular bundle fiber extraction in bamboo

doi: 10.11833/j.issn.2095-0756.20240536

Abstract:   Objective  This study aims to explore the optimal cutting parameters for cutting force and extraction quality when extracting bamboo (Phyllostachys edulis) vascular bundle fibers by milling, and provide theoretical reference for efficient acquisition of high-quality natural vascular bundle fibers with uniform thickness and good consistency in length and size.   Method  Cutting speed (Vc), feed per tooth (fz), and cutting depth (Ap) were taken as variables, unidirectional milling and orthogonal cutting experiments were conducted on bamboo boards using a double-edged straight groove hard alloy woodworking carving knife. The influence of cutting parameters on cutting force was verified by range analysis and variance analysis. The experimental data were analyzed by multivariate nonlinear regression method to establish an empirical formula for cutting force. Based on transient cutting geometric model and single-factor experiments, the effects of cutting speed, cutting depth, and feed per tooth on the quality of vascular bundle fiber extraction were investigated.   Result  During the cutting process, only X-Y-directional cutting forces were generated on the workpiece, while the Z-directional cutting force continuously fluctuated near zero value. Cutting depth had an extremely significant impact on cutting force. Within the X-Y plane, cutting force mainly acted along parallel the feed direction of the tool, and feed per tooth had a more significant influence on cutting force than cutting speed. The vertical tool feed direction was mainly affected by extrusion force, and cutting speed had a more significant effect on cutting force than feed per tooth. The coefficient of determination (R2) of nonlinear regression equation for cutting force along the tool feed direction was 0.956, which could accurately predict the magnitude of cutting force. The determination coefficient of the nonlinear regression equation for cutting force in the vertical tool feed direction was 0.697, but the error between its predicted and theoretical value was within ±5 N, reflecting the overall trend of cutting force in this direction. The error between the average fiber length obtained by milling and the target length was within ±0.1 mm. Within the range of cutting parameters, when cutting parameters were Vc=188.5 m·min−1, Ap=12 mm, and fz=0.2 mm, vascular bundle fibers with larger diameters and higher aspect ratio were obtained.   Conclusion  Cutting depth is the most important factor affecting the magnitude of cutting force. In the parallel tool feed direction, feed per tooth has a greater impact on cutting force than cutting speed. In the vertical tool feed direction, cutting speed has a greater impact on cutting force than feed per tooth. The nonlinear regression model of cutting force can accurately calculate cutting force in various directions and the overall trend of change. The milling method can accurately control the target length of vascular bundle fibers. Higher cutting speed, greater cutting depth, and smaller feed per tooth can help obtain vascular bundle fibers with larger aspect ratio and diameters. [Ch, 9 fig. 5 tab. 26 ref.]

LIN Yixin, CHEN Dandan, LIU Hongbo, et al. Identification of key amino acid residues controlling the activities of glycerol-3-phosphate acyltransferases in Arabidopsis thaliana and Brassica napus[J]. Journal of Zhejiang A&F University, 2023, 40(4): 695-706. DOI: 10.11833/j.issn.2095-0756.20220764
Citation: HU Xiaojun, TIAN Ze, XU Yunjie, et al. Effect of milling parameters on cutting force and quality of vascular bundle fiber extraction in bamboo[J]. Journal of Zhejiang A&F University, 2025, 42(X): 1−9 doi:  10.11833/j.issn.2095-0756.20240536
  • 竹材和竹制品的环保特性已成为竹产业的标志属性。毛竹Phyllostachys edulis的微观结构是由维管束纤维与基体组成的两相复合材料,维管束纤维是影响毛竹宏观力学性能的关键。现有竹纤维分离方法可分为高温蒸煮和机械冲击摩擦2类,如蒸汽爆破、碾压捶打、机械梳解、化学分离等[18]。以上分离方法关注的焦点均在于所得纤维产品的性能优劣,而忽视了维管束与薄壁组织的分离效果评价。在分离过程中,常存在纤维热损伤、比强度降低、生产效率低、纤维尺寸一致性差等问题。

    数控加工中心可通过数控程序精确控制刀具路径和切削方向,并通过合理设置刀具路径和铣削条件精确控制纤维形状。杨永福等[9]分析了不同刀具前角、切削速度以及进给量等切削参数对竹片平面直角自由切削过程中切削力的影响;郭莹洁等[1011]研究了铣削加工参数的改变对竹片表面质量及超前劈裂的影响。OGAWA等[1213]通过设定合适的加工中心切削参数,切削提取得到了长度均匀、无热损伤的竹纤维。上述研究主要围绕竹制品的切削特性和切削提取原竹纤维的加工条件展开,并未深入探讨天然竹维管束纤维制取过程中切削力及切削特性等变化。

    为揭示天然毛竹维管束纤维提取过程中铣削参数对切削力及维管束纤维形态的影响,本研究以切削加工三要素为变量,使用双刃直槽硬质合金木工雕刻刀对竹板开展单向顺铣正交切削试验,运用极差、方差分析方法,验证分析铣削参数对切削力的影响,并建立切削力经验公式;基于瞬态切削几何模型和单因素试验,探究切削速度(Vc)、切削深度(Ap)和每齿进给量(fz)对维管束纤维提取质量的影响,以期为合理选取切削参数,高效获取优质竹纤维提供理论以及技术指导。

    • 选取浙江湖州5年生毛竹,并截取直径约110 mm,竹壁厚度约10 mm的竹段作为试材。去除竹节后放入烘箱中,在70~80 ℃下烘烤8 h。然后,用破竹器将每段试材分成8根竹条,并去除0.8 mm厚度的竹青表皮,最后对竹条进行切割,得到高度分别为36、40和44 mm的竹板毛坯。加工机床采用宁波其锐达机械有限公司生产的KMD-80120型三轴高速雕铣机,主轴最高转速达到12 000 r·min−1;试验刀具为直径10 mm的双刃直槽硬质合金木工雕刻刀。在试验过程中,刀刃径向跳动调整在6 μm以下。切削力测量系统为宁波灵元测控工程有限公司生产的压电晶体测力仪。

    • 对于纤维增强复合材料,具有大长径比的纤维是理想的[1417],因此本研究以纤维长度、纤维直径和纵横比评判维管束纤维质量。设计正交切削试验并获取各参数下的切削力数据,再基于切削力数据分析切削参数对切削力及维管束纤维质量的影响规律。

      参考以往研究[1820],本研究将竹壁沿径向划分为图1所示的内、中、外3层,其中外部维管束纤维呈半开放型,纤维长轴平均长度为0.39 mm,短轴平均长度为0.23 mm。经测量,竹壁外部维管束纤维在水平方向的平均间隙为0.2~0.4 mm。切削过程中,为得到尽可能完整的维管束纤维,切削步进距(Ae)设置为0.4 mm。在以上加工参数的基础上,将切削速度、每齿进给量及切削深度分别定义为因素ABC,制定正交试验方案(表1)。试验采用刀刃平行于维管束纤维,沿X轴单向顺铣,干式切削方式进行,对每个试件连续切削3个步距,每组参数重复切削5个试件。通过以上正交试验,可得到135组切削力数据。

      Figure 1.  Schematic diagram of bamboo wall layering

      序号 切削速度(A)/
      (m·min−1)
      每齿进给量(B)/
      mm
      切削深度(C)/
      mm
      切削力/N 序号 切削速度(A)/
      (m·min−1)
      每齿进给量(B)/
      mm
      切削深度(C)/
      mm
      切削力/N
      Fx Fy Fx Fy
      1 62.8 0.2 4 23.70 −8.89 6 125.7 0.4 4 34.78 −10.86
      2 62.8 0.3 12 81.04 −25.87 7 188.5 0.2 8 37.22 −24.62
      3 62.8 0.4 8 69.56 −23.88 8 188.5 0.3 4 27.01 −15.82
      4 125.7 0.2 12 55.84 −19.59 9 188.5 0.4 12 85.16 −42.63
      5 125.7 0.3 8 51.97 −16.12

      Table 1.  Forces of orthogonal experimental cutting

      在切削速度为62.8 m·min−1,每齿进给量为0.2 mm,切削深度为4 mm,切削步进距为0.4 mm条件下,对高度为36 mm的竹块毛坯进行切削试验,每个切削刃的部分切削分力(FxFyFz)的动态分布曲线如图2所示。切削力呈周期性变化。由于竹壁维管束纤维呈错列排布,铣削过程中维管束纤维的切削厚度不尽相同,因此加工过程中切削力的最大值变化显著。1个切削周期内,Fx先增后减,且为正值,表明在切削过程中,切削刃始终沿进给方向对竹板产生拉力,且随着切削厚度增至最大,切削力也增至最大;Fy向切削刃始终对竹板产生挤压作用,且顺铣时切削刃切出工件侧面过程中,切削厚度逐渐减小为0,故Fy始终为负值。此外,不同于螺旋铣刀,双刃直槽硬质合金木工雕刻刀在切削过程中对材板无Z轴方向作用力,但机床系统振动会导致Z轴方向作用力产生如图2C所示的微小波动[21],因此本研究忽略Z轴方向作用力的影响[2223]。为保证试验数据的一致性,均在切削力曲线中选取重复频率较高、数值较大的切削力数值进行记录。每组试验参数记录15组切削力数据,并计算其平均值作为该组正交试验参数的切削力,正交试验方案及切削力如表1所示。

      Figure 2.  Dynamic distribution of cutting force

      图3为维管束纤维切削瞬态几何模型[24]。定义纤维纵横比为α=L/amax,用以标定维管束纤维的长度和窄度,其中L为切割弧长,amax为最大纤维切削厚度。amaxL可根据下式得到:

      Figure 3.  Transient geometry of vascular bundle fiber cutting

      式(1)~(2)中:fz为每齿进给量,φ0为最大接触角,R为刀具半径。定义维管束纤维理论直径为De=(L+amax)/2。从每组试验中随机选取的100根维管束纤维,使用游标卡尺分别测量纤维厚度、切割弧长和纤维长度(L0),并分别以各自平均值作为对应参数的最终数据。

    • 在每齿进给量为0.4 mm,切削深度为12 mm,切削步进距为0.4 mm条件下,切削速度与切削力平均值的关系如图4所示。切削过程中,Fx为正值,为主要切削力。Fy为负值,切削刃对工件产生挤压作用。随着切削速度的增加,刀具单次切削竹维管束的体积减小,单次切削功率也随之减小,因此Fx随切削速度的增加而减小;Fy在−40 N附近轻微波动。由此可见:切削速度的变化对Fy方向的切削力影响不大,其轻微波动主要由切削系统共振造成。

      Figure 4.  Influence of cutting speed on cutting force

      在每齿进给量为0.4 mm,切削深度为12 mm, 切削步进距为0.4 mm条件下,切削速度对维管束纤维形态的影响如图5所示。随着切削速度的增加,维管束纤维直径(D0)先减小后增大,且数值只有维管束纤维理论直径的0.5~0.7倍(图5A)。这是因为理论切割弧长大于维管束纤维直径,即使维管束纤维被完整切割也无法达到理论值。各参数铣削获得的维管束纤维长度比较稳定,且与理论值的误差极小(图5B)。维管束纤维纵横比随着切削速度的增大而增大,且当切削速度大于125.7 m·min−1时,纤维纵横比有较明显的提高(图5C)。由纤维直径、纤维长度及纤维纵横比的变异系数(CV)可知(图5D):随着切削速度的变化,纤维长度并未产生明显的变化,纤维直径和纤维纵横比均在切削速度为160.0~188.5 m·min−1时出现最小值且变化幅度较小。综上,提高切削速度有助于获得尺寸稳定且有较大纵横比和直径的维管束纤维。

      Figure 5.  Effect of cutting speed on the shape of bamboo fiber

    • 在切削速度为125.7 m·min−1,切削深度为12 mm,切削步进距为0.4 mm条件下,每齿进给量与切削力平均值的关系如图6所示。随着每齿进给量增加,单位时间内切下切屑的体积增大,切削功率也随之增大,因此随着每齿进给量的增加,Fx呈近似线性增大,Fy呈近似线性减小。

      Figure 6.  Influence of feed rate per tooth on cutting force

      在切削速度为125.7 m·min−1,切削深度为12 mm, 切削步进距为0.4 mm条件下,每齿进给量对维管束纤维形态的影响如图7所示。不同每齿进给量下获得维管束纤维直径先减小后增大,且当每齿进给量为0.2 mm时出现最大值(图7A);各参数铣削获得的维管束纤维长度比较稳定,且与理论值接近(图7B);纤维纵横比随着每齿进给量增加,呈先下降后上升再下降的趋势,且当每齿进给量为0.2 mm时出现最大值(图7C);纤维长度、纤维直径和纤维纵横比随每齿进给量变化而产生明显的变化,但均在每齿进给量为0.2 mm时获得最优维管束纤维(图7D)。综上,减小每齿进给量有利于获得较高质量的维管束纤维。

      Figure 7.  Effect of feed rate per tooth on bamboo fiber morphology

    • 在切削速度为188.5 m·min−1,每齿进给量为0.3 mm,切削步进距为0.4 mm条件下,切削深度与切削力平均值的关系如图8所示。随着切削深度增加,单位时间内切下切屑的体积增大,切削功率也随之增大,因此Fx随切削深度的增加而增大,而Fy随切削深度的增加而减小。

      Figure 8.  Influence of cutting depth on cutting force

      在切削速度为188.5 m·min−1,每齿进给量为0.3 mm, 切削步进距为0.4 mm条件下,切削深度对维管束纤维形态的影响如图9所示。不同切削深度下获得维管束纤维直径变化不大,且为理论值的一半左右(图9A);维管束纤维长度随切削深度增加而增加,且曲线斜率为1,表明纤维长度与理论值保持一致(图9B);纤维纵横比随着切削深度增加,呈先下降后上升的趋势(图9C);图9D为切削深度对纤维形态变异系数的影响,其中纤维长度和纤维直径的变异系数基本保持恒定,纤维纵横比的变异系数先降低后升高且在切削深度大于10 mm后基本保持恒定。综上,增加切削深度有利于获得较高质量的维管束纤维。

      Figure 9.  Effect of cutting depth on the shape of bamboo fiber

    • 对切削力正交试验结果进行极差分析,结果如表2所示。由表2可知:切削深度(C)对FxFy的影响最大,切削速度(A)和每齿进给量(B)分别对FxFy的影响最小。因此,可以得到对FxFy影响最小的最优加工参数方案为A2B1C1

      切削力 参数 切削参数 切削力 参数 切削参数
      切削速度(A)/
      (m·min−1)
      每齿进给量(B)/
      mm
      切削深度(C)/
      mm
      切削速度(A)/
      (m·min−1)
      每齿进给量(B)/
      mm
      切削深度(C)/
      mm
      Fx K1 174.301 116.764 85.497 Fy K1 −58.638 −53.102 −35.573
      K2 142.582 160.022 158.749 K2 −46.577 −57.819 −64.624
      K3 149.399 189.497 222.037 K3 −83.078 −77.373 −88.096
      k1 58.100 38.921 28.499 k1 −19.546 −17.701 −11.858
      k2 47.527 53.341 52.916 k2 −15.526 −19.273 −21.541
      k3 49.800 63.166 74.012 k3 −27.693 −25.791 −29.365
      R 10.573 24.244 45.514 R 12.167 8.090 17.507
      主次因素 ApfzVc 主次因素 ApVcfz
      最优方案 A2B1C1 最优方案 A2B1C1
        说明:Ki. 满足要求的单元格求和;ki. Ki的算术平均值;R. 极差。

      Table 2.  Range of cutting force orthogonal experiment

      对切削力数据进行方差分析,结果如表3所示。在单向顺铣过程中,切削深度对Fx影响极显著(P<0.01),对Fy影响显著(P<0.05)。每齿进给量对Fx影响显著(P<0.05),对Fy影响不显著。切削速度对FxFy切削力影响均不显著。因此,单向顺铣过程中,切削深度是影响切削力的最主要因素,每齿进给量对切削力的影响大于切削速度。方差分析结果与极差分析结果一致,表明正交试验设计的有效性。

      方差来源离差平方和均方F显著性方差来源离差平方和均方F显著性
      FxVc245.647122.82314.0320.067FyVc230.558115.27918.2910.052
      fz860.307430.15349.1440.020*fz110.41255.2068.7600.102
      Ap3 125.7551 562.877178.5560.006**Ap461.497230.74836.6130.027*
      误差17.5068.753误差12.6056.302
        说明:*. 差异显著(P<0.05),**. 差异极显著(P<0.01)。

      Table 3.  Variance analysis of cutting force

      对不同切削状态下的切削数据进行多元非线性回归分析[2526]Fx非线性回归方程决定系数(R2)为0.956,说明对应模型能解释95.6%的变异,模型拟合效果很好。Fy非线性回归方程R2为0.697,说明对应模型仅能解释69.7%的变异。

      式(3)~(4)中:FxFy为切削分力;Ap为切削深度度;fz为每齿进给量;Vc为切削速度;R2为决定系数。正交试验与回归方程预测的对比结果如表4所示。Fx的预测值与试验值的误差为±6%左右,说明回归方程具有较高的可靠性。Fy的预测值与试验值的偏差较大,是因为切削刃对竹板反复产生挤压作用,导致切削系统振动。但对比Fy的试验值与预测值可知,预测值与理论值之间的差值在±5 N以内,且Fy的切削力数值相对较小,因此Fy的回归模型能够一定程度上反映其实际切削状态。

      序号Fx/NFy/N序号Fx/NFy/N
      试验值预测值误差/%试验值预测值误差/%试验值预测值误差/%试验值预测值误差/%
      124.3123.70−2.57−8.89−7.53−18.06633.1634.784.66−10.86−14.6625.92
      277.8181.043.99−25.87−24.71−4.69737.2537.22−0.08−24.62−19.01−29.51
      373.8169.56−6.11−23.88−21.17−12.80825.4127.015.92−15.82−13.80−14.64
      457.6355.84−3.21−19.59−23.5716.89984.0085.161.36−42.63−41.97−1.57
      549.0051.975.71−16.12−21.8026.06

      Table 4.  Test of predicted value of regression equation of orthogonal experimental parameters

      为进一步验证回归模型的可靠性,设计各切削要素条件下的非正交试验,试验结果如表5所示。回归方程对各参数的切削力预测与上述非正交试验结果基本一致,说明回归方程具有较高的可靠性。

      序号切削速度/(m·min−1)每齿进给量/mm切削深度/mmFx/NFy/N
      试验值预测值误差/%试验值预测值误差/%
      162.80.3431.3332.724.25−9.80−13.7328.62
      262.80.41298.78104.345.33−29.79−35.1315.20
      3125.70.2421.5922.242.92−9.35−8.35−11.98
      4125.70.2839.3239.29−0.08−16.75−14.65−14.33
      5125.70.31273.8073.09−0.97−30.67−29.17−5.14
      6125.70.4863.3462.86−0.76−26.29−20.00−31.45
      7125.70.41289.9590.530.64−36.98−37.371.04
      8188.50.21252.8656.426.31−26.75−37.7829.20
      9188.50.3849.2046.38−6.08−24.74−22.04−12.25

      Table 5.  Test of predicted values of regression equations of non-orthogonal experimental parameters

    • 切削深度对维管束纤维切削力的影响最大,平行于刀具进给方向受力主要为切削力,每齿进给量相对于切削速度对切削力的影响更明显,垂直于刀具进给方向主要受挤压力作用,切削速度比每齿进给量对切削力的影响大。对不同切削状态下的切削数据进行多元非线性回归分析,得到切削力非线性回归模型。试验值与模型预测值的对比结果显示:该模型可以较为准确地计算各方向的切削力。

      采用铣削方法可提取长度一致性好的维管束纤维,且可通过控制铣刀的切削深度,得到不同长度的维管束纤维。采用较高切削速度、较大切削深度和较小每齿进给量有助于获得较大长径比和直径的维管束纤维。

Reference (26)

Catalog

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return