Article(id=1311999913165157084, tenantId=1146029695717560320, journalId=1311385739772133495, issueId=1311999647825101743, articleNumber=null, orderNo=null, doi=10.6041/j.issn.1000-1298.2025.12.034, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1727539200000, receivedDateStr=2024-09-29, revisedDate=1730044800000, revisedDateStr=2024-10-28, acceptedDate=null, acceptedDateStr=null, onlineDate=1790734755077, onlineDateStr=2026-09-30, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790734755077, onlineIssueDateStr=2026-09-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790734755077, creator=13701087609, updateTime=1790734755077, updator=13701087609, issue=Issue{id=1311999647825101743, tenantId=1146029695717560320, journalId=1311385739772133495, year='2025', volume='56', issue='12', pageStart='1', pageEnd='818', issueExtLink='null', onlineDate='null', pubDate='1766592000000', pubDateStr='2025-12-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790734691815, creator='13701087609', updateTime=1790738411040, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1312015247465083866, tenantId=1146029695717560320, journalId=1311385739772133495, issueId=1311999647825101743, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1312015247465083867, tenantId=1146029695717560320, journalId=1311385739772133495, issueId=1311999647825101743, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=376, endPage=385, ext={EN=ArticleExt(id=1311999913387455197, articleId=1311999913165157084, tenantId=1146029695717560320, journalId=1311385739772133495, language=EN, title=Design and Experiment of Banana De-handing End Effector Based on Opening-closing Cutter, columnId=1311999707161919908, journalTitle=Transactions of the Chinese Society for Agricultural Machinery, columnName=Agricultural Equipment and Mechanization Engineering, runingTitle=null, highlight=null, articleAbstract=

In order to solve the problems of low adaptability of the tool to the banana crown and the low success rate of the banana in the process of intelligent de-handing, a type of end effector was designed according to the morphological parameters of the banana bunch and the crown and the production requirements of the de-handing. The cutting arc of the adjustable opening-closing de-handing tool was used to adapt to different sizes of the banana crown to achieve continuous banana de-handing. The key parameters and main structure of the de-handing end effector were designed. The mechanical analysis model of the process of cutting banana crown by the de-handing tool was established, and the strength simulation was carried out. The results showed that the maximum stress of the de-handing tool during the de-handing process was 58.147 MPa, which was less than the yield strength of the tool material 205 MPa. The test platform of robot de-handing was built, and the significant factors affecting the de-handing effect were sorted as the cutting angle of de-handing, the blade angle and the de-handing speed. In order to obtain the optimal parameter combination, taking the peak cutting force and incision quality as the evaluation indices, the combination test of three-factors and three-levels were carried out by using Design-Expert software, and the mathematical regression model between the experimental factors and the evaluation indexes was obtained. The multi-objective optimization of the regression model was carried out, and the optimal parameter combination was obtained as follows: the de-handing speed was 2 m/s, the cutting angle of de-handing was 5.77°, and the blade angle was 5°. The results of the optimal parameter combination verification test showed that the peak cutting force was 31.49 N, the incision quality was 84 points, the relative error with the prediction results of the regression model was less than 5%, and the success rate of the de-handing was 92%, indicating that the opening-closing end effector of banana de-handing can effectively adapt to the banana crown's morphology and obtain better incision quality.

, authors=Jieli DUAN1, Xingkang MO1, Chaowei HUANG1, Bocheng LIU1, Zhou YANG1, 2, Xiangjun ZOU1, 3, authorsList=Jieli DUAN, Xingkang MO, Chaowei HUANG, Bocheng LIU, Zhou YANG, Xiangjun ZOU, authorCompany=null, correspAuthors=Zhou YANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311999921025282836, articleId=1311999913165157084, tenantId=1146029695717560320, journalId=1311385739772133495, language=CN, title=基于张合式刀具的香蕉落梳末端执行器设计与试验, columnId=1311999707321303462, journalTitle=农业机械学报, columnName=农业装备与机械化工程, runingTitle=null, highlight=null, articleAbstract=

针对在智能化落梳过程中,刀具对香蕉果柄自适应性差且落梳成功率低等问题,本文根据香蕉果穗及果柄形态参数并结合落梳生产要求设计了一种新型末端执行器,利用可变落梳张合式刀具切割弧适应不同大小的香蕉果柄,从而实现香蕉连续落梳。设计了落梳末端执行器关键参数与主要结构;建立了落梳刀具插切香蕉果柄过程力学分析模型,并开展了强度仿真,结果表明在落梳过程中落梳刀具最大应力为58.147 MPa,小于刀具材料屈服强度205 MPa。搭建了落梳机器人试验平台,并得到影响落梳效果的显著性因素排序为落梳入切角、刀刃角、落梳速度。为获得最佳参数组合,以峰值切割力和切口质量作为评价指标,利用Design-Expert软件进行了三因素三水平组合试验,得到试验因素与评价指标间的数学回归模型。对回归模型进行多目标优化,得到最佳参数组合为:落梳速度2 m/s、落梳入切角5.77°、刀刃角5°。最佳参数组合验证试验结果表明,峰值切割力为31.49 N,切口质量为84分,与回归模型预测结果相对误差均小于5%,落梳成功率为92%,表明张合式香蕉落梳末端执行器能有效适应香蕉果柄形态且获得较好的切口质量。

, authors=段洁利1, 莫杏康1, 黄朝炜1, 刘博成1, 杨洲1, 2, 邹湘军1, 3, authorsList=段洁利, 莫杏康, 黄朝炜, 刘博成, 杨洲, 邹湘军, authorCompany=null, correspAuthors=杨洲, authorNote=

段洁利(1973—),女,教授,博士生导师,主要从事智能农业装备研究,E-mail:

, correspAuthorsNote=
杨洲(1972—),男,教授,博士生导师,主要从事水果生产机械化与信息化研究,E-mail:
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caption=落梳末端执行器整体结构和张合式刀具结构

1. 刀具固定板 2. 加强筋板 3. 凸起补偿块 4. 中间主刀 5. 1号副刀 6. 弧形刀位补偿 7. 2号副刀 8. 连杆 9. 连杆驱动板 10. 电机固定板 11. 丝杠电机

, figureFileSmall=RRa8xRhAXlJiOR7maf8RSQ==, figureFileBig=YDgrAU6SgAZuJAhHGkRcPw==, tableContent=null), ArticleFig(id=1311999925626434380, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1311999913165157084, language=EN, label=Fig. 4, caption=Tool cutting force analysis diagram, figureFileSmall=RPOEHLO3N/qUn7eKUKp27g==, figureFileBig=TCXblgYPplASG4ZEK5u5Lg==, tableContent=null), ArticleFig(id=1311999925693543245, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1311999913165157084, language=CN, label=图4, caption=刀具插切果柄受力分析

1. 果轴 2. 果指 3. 果柄 4. 落梳刀

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1. 6自由度机械臂 2. 深度相机 3. 蕉穗旋转夹持装置 4. 落梳末端执行器 5. 便携式计算机 6. 控制箱

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Basic parameters of banana bunch

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参数数值
蕉穗质量/kg30~50
果柄内弧长/mm84.81±21.54
果柄外弧长/mm113.35±31.98
果柄轴向间距/mm106.21±34.91
果柄轴向高度差/mm35.64±7.73
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蕉穗基本参数

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参数数值
蕉穗质量/kg30~50
果柄内弧长/mm84.81±21.54
果柄外弧长/mm113.35±31.98
果柄轴向间距/mm106.21±34.91
果柄轴向高度差/mm35.64±7.73
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Main structural parameters of end-effector

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参数数值
外形尺寸(长×宽×高)/(mm×mm×mm)161×93×142
质量/kg0.76
主刀数1
副刀数2
两侧副刀最大开口长度/mm83
两侧副刀最大张合角/(°)107
副刀长度/mm105
主刀长度/mm100
刀尖角/(°)120
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末端执行器主要结构参数

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参数数值
外形尺寸(长×宽×高)/(mm×mm×mm)161×93×142
质量/kg0.76
主刀数1
副刀数2
两侧副刀最大开口长度/mm83
两侧副刀最大张合角/(°)107
副刀长度/mm105
主刀长度/mm100
刀尖角/(°)120
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Related parameters of 316L stainless steel

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参数数值
密度/(kg·m-3)7 980
弹性模量/MPa1.93×105
剪切模量/MPa7.42×104
泊松比0.3
抗拉强度/MPa515
屈服强度/MPa205
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316L不锈钢相关参数

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参数数值
密度/(kg·m-3)7 980
弹性模量/MPa1.93×105
剪切模量/MPa7.42×104
泊松比0.3
抗拉强度/MPa515
屈服强度/MPa205
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Coding of test factors

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编码因素
落梳速度x1/(m·s-1)落梳入切角x2/(°)刀刃角x3/(°)
-11.235
01.6610
12.0915
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试验因素编码

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编码因素
落梳速度x1/(m·s-1)落梳入切角x2/(°)刀刃角x3/(°)
-11.235
01.6610
12.0915
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Test scheme and results

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序号因素峰值切割力/N切口质量/分
X1X2X3
100052.4782
201145.8779
300051.0981
40-1161.7086
500057.6979
601-127.6476
7-11044.5774
811042.3074
900056.1580
100-1-148.7080
11-10142.4588
1210-135.9682
13-10-157.8086
14-1-1068.5682
151-1057.0682
1600055.3977
1710152.3392
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试验方案与结果

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序号因素峰值切割力/N切口质量/分
X1X2X3
100052.4782
201145.8779
300051.0981
40-1161.7086
500057.6979
601-127.6476
7-11044.5774
811042.3074
900056.1580
100-1-148.7080
11-10142.4588
1210-135.9682
13-10-157.8086
14-1-1068.5682
151-1057.0682
1600055.3977
1710152.3392
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Analysis of variance of regression equation

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方差来源峰值切割力Y1切口质量Y2
平方和自由度均方值FP平方和自由度均方值FP
模型1 444.539160.507.780.006 5**353.42939.2714.430.001**
X182.75182.754.010.085 25.68×10-1415.68×10-142.09×10-141.000
X2715.181715.1834.680.000 6**91.12191.1233.480.000 7**
X3130.011130.016.300.040 3*55.13155.1320.260.002 8**
X1X221.30121.301.030.343 35.68×10-1415.68×10-142.09×10-141.000
X1X3251.541251.5412.200.010 1*16.00116.005.880.045 8*
X2X36.8416.840.331 60.582 72.2512.250.826 80.393 4
0.081 410.081 40.003 90.951 725.79125.799.480.017 9*
7.0817.080.343 20.576 476.95176.9528.280.001 1**
223.401223.4010.830.013 3*94.00194.0034.540.000 6**
残差144.35720.6219.0572.72
失拟项114.92338.315.210.072 44.2531.420.382 90.771 8
纯误差29.4247.3614.8043.70
综合1 588.8816372.4716
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回归方程方差分析

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方差来源峰值切割力Y1切口质量Y2
平方和自由度均方值FP平方和自由度均方值FP
模型1 444.539160.507.780.006 5**353.42939.2714.430.001**
X182.75182.754.010.085 25.68×10-1415.68×10-142.09×10-141.000
X2715.181715.1834.680.000 6**91.12191.1233.480.000 7**
X3130.011130.016.300.040 3*55.13155.1320.260.002 8**
X1X221.30121.301.030.343 35.68×10-1415.68×10-142.09×10-141.000
X1X3251.541251.5412.200.010 1*16.00116.005.880.045 8*
X2X36.8416.840.331 60.582 72.2512.250.826 80.393 4
0.081 410.081 40.003 90.951 725.79125.799.480.017 9*
7.0817.080.343 20.576 476.95176.9528.280.001 1**
223.401223.4010.830.013 3*94.00194.0034.540.000 6**
残差144.35720.6219.0572.72
失拟项114.92338.315.210.072 44.2531.420.382 90.771 8
纯误差29.4247.3614.8043.70
综合1 588.8816372.4716
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基于张合式刀具的香蕉落梳末端执行器设计与试验
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段洁利 1 , 莫杏康 1 , 黄朝炜 1 , 刘博成 1 , 杨洲 1, 2 , 邹湘军 1, 3
农业机械学报 | 农业装备与机械化工程 2025,56(12): 376-385
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农业机械学报 |农业装备与机械化工程 2025 , 56 (12) : 376 -385
基于张合式刀具的香蕉落梳末端执行器设计与试验
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段洁利1 , 莫杏康1, 黄朝炜1, 刘博成1, 杨洲1, 2 , 邹湘军1, 3
作者信息
  • 1.华南农业大学工程学院,广州 510640
  • 2.广东海洋大学机械工程学院,湛江 524088
  • 3.佛山市中科农业机器人与智慧农业创新研究院,佛山 528200
通讯作者:
杨洲(1972—),男,教授,博士生导师,主要从事水果生产机械化与信息化研究,E-mail:
作者简介:

段洁利(1973—),女,教授,博士生导师,主要从事智能农业装备研究,E-mail:

Design and Experiment of Banana De-handing End Effector Based on Opening-closing Cutter
Jieli DUAN1 , Xingkang MO1, Chaowei HUANG1, Bocheng LIU1, Zhou YANG1, 2 , Xiangjun ZOU1, 3
Affiliations
  • 1.College of Engineering, South China Agricultural University, Guangzhou 510640, China
  • 2.College of Mechanical Engineering, Guangdong Ocean University, Zhanjiang 524088, China
  • 3.Foshan-Zhongke Innovation Research Institute of Intelligent Agriculture, Foshan 528200, China
出版时间: 2025-12-25 doi: 10.6041/j.issn.1000-1298.2025.12.034
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针对在智能化落梳过程中,刀具对香蕉果柄自适应性差且落梳成功率低等问题,本文根据香蕉果穗及果柄形态参数并结合落梳生产要求设计了一种新型末端执行器,利用可变落梳张合式刀具切割弧适应不同大小的香蕉果柄,从而实现香蕉连续落梳。设计了落梳末端执行器关键参数与主要结构;建立了落梳刀具插切香蕉果柄过程力学分析模型,并开展了强度仿真,结果表明在落梳过程中落梳刀具最大应力为58.147 MPa,小于刀具材料屈服强度205 MPa。搭建了落梳机器人试验平台,并得到影响落梳效果的显著性因素排序为落梳入切角、刀刃角、落梳速度。为获得最佳参数组合,以峰值切割力和切口质量作为评价指标,利用Design-Expert软件进行了三因素三水平组合试验,得到试验因素与评价指标间的数学回归模型。对回归模型进行多目标优化,得到最佳参数组合为:落梳速度2 m/s、落梳入切角5.77°、刀刃角5°。最佳参数组合验证试验结果表明,峰值切割力为31.49 N,切口质量为84分,与回归模型预测结果相对误差均小于5%,落梳成功率为92%,表明张合式香蕉落梳末端执行器能有效适应香蕉果柄形态且获得较好的切口质量。

香蕉  /  落梳机器人  /  末端执行器  /  张合式刀具

In order to solve the problems of low adaptability of the tool to the banana crown and the low success rate of the banana in the process of intelligent de-handing, a type of end effector was designed according to the morphological parameters of the banana bunch and the crown and the production requirements of the de-handing. The cutting arc of the adjustable opening-closing de-handing tool was used to adapt to different sizes of the banana crown to achieve continuous banana de-handing. The key parameters and main structure of the de-handing end effector were designed. The mechanical analysis model of the process of cutting banana crown by the de-handing tool was established, and the strength simulation was carried out. The results showed that the maximum stress of the de-handing tool during the de-handing process was 58.147 MPa, which was less than the yield strength of the tool material 205 MPa. The test platform of robot de-handing was built, and the significant factors affecting the de-handing effect were sorted as the cutting angle of de-handing, the blade angle and the de-handing speed. In order to obtain the optimal parameter combination, taking the peak cutting force and incision quality as the evaluation indices, the combination test of three-factors and three-levels were carried out by using Design-Expert software, and the mathematical regression model between the experimental factors and the evaluation indexes was obtained. The multi-objective optimization of the regression model was carried out, and the optimal parameter combination was obtained as follows: the de-handing speed was 2 m/s, the cutting angle of de-handing was 5.77°, and the blade angle was 5°. The results of the optimal parameter combination verification test showed that the peak cutting force was 31.49 N, the incision quality was 84 points, the relative error with the prediction results of the regression model was less than 5%, and the success rate of the de-handing was 92%, indicating that the opening-closing end effector of banana de-handing can effectively adapt to the banana crown's morphology and obtain better incision quality.

banana  /  de-handing robot  /  end effector  /  opening-closing cutter
段洁利, 莫杏康, 黄朝炜, 刘博成, 杨洲, 邹湘军. 基于张合式刀具的香蕉落梳末端执行器设计与试验. 农业机械学报, 2025 , 56 (12) : 376 -385 . DOI: 10.6041/j.issn.1000-1298.2025.12.034
Jieli DUAN, Xingkang MO, Chaowei HUANG, Bocheng LIU, Zhou YANG, Xiangjun ZOU. Design and Experiment of Banana De-handing End Effector Based on Opening-closing Cutter[J]. Transactions of the Chinese Society for Agricultural Machinery, 2025 , 56 (12) : 376 -385 . DOI: 10.6041/j.issn.1000-1298.2025.12.034
我国是香蕉生产和消费大国,香蕉营养价值丰富、品类繁多,强大的消费市场需求刺激着香蕉产业的可持续发展[1-3]。香蕉产后处理主要包括采摘、运输、落梳、清洗、消毒、分级和包装运输等环节[4]。目前,香蕉落梳环节主要依靠人工落梳方式完成,且在落梳时往往面临用工荒、效率低、强度高等问题。
国内外学者对香蕉机械化落梳进行了相关研究。陈兆春[5]利用单把弧形落梳刀对香蕉果柄落梳过程进行了分析,但单把弧形落梳刀难以适应不同大小的果柄弧长。杨洲等[6]设计了一种可变径自适应旋转切割式香蕉落梳刀具,通过由内外刀刃形成环形包络结构,用于连续落梳时包络香蕉果轴,但该结构刀具忽略了香蕉果轴弯曲度及圆度的影响,在落梳过程中刀具对香蕉果轴适应性差,容易切入果轴。金莫辉等[7]针对香蕉落梳刀具对果柄适应性差的问题,设计了一种可与蕉园中香蕉运送导轨相配合的香蕉落梳末端执行器,针对不同大小果柄,该末端执行器变径落梳刀具可进行有效仿形变径,但该末端执行器对于较大的果柄适应性差且所采用的落梳刀具为薄钢片,用于落梳作业时容易折弯变形,刀具寿命短。
虽然,香蕉机械化落梳已展开深入研究,但受蕉穗不规则生长形态的影响,仍难以使用。为了解决传统人工落梳和机械化落梳对香蕉落梳环节的限制,开展智能化落梳研究非常有必要[8]。在香蕉智能化落梳领域,ZHAO等[9]通过采用多种成像方法,从微观角度分析香蕉果柄管束的形态特征,得到了可减少能量消耗和提高切割效率的最佳落梳区域,应在中央茎冠过渡区和冠状扩张区之间,为智能化落梳提供了更科学的落梳切割点。段洁利等[10]提出的一种基于机械手的可变径式落梳末端执行器,以气缸驱动升降平台作为末端执行器搭载平台,并以插切方式切割落梳,其刀具结构复杂,制造成本较高。国外ARM Hub公司在智能化落梳可行性研究中[11],阐述了一种浸没式智能落梳装置工作原理,但该方案仅提出利用机械臂作为智能化落梳平台并没有提及可适用于智能化落梳末端执行器,可行性有待进一步研究。香蕉智能化落梳是利用计算机视觉技术、机器人技术和自动化执行设备,对香蕉果柄进行自动识别、定位和落梳,以提高落梳效率和质量。在实际落梳环节中,存在梳把之间生长间距小、香蕉果指弯曲且过于贴合果轴、果轴弯曲等问题[12]。为了实现香蕉智能化连续落梳,除研究智能识别非线性果柄弧长以及定位等技术外,落梳末端执行器是智能化落梳机器人关键执行部件,负责切割果柄将蕉梳从果轴上分离出来,其刀具结构设计直接影响落梳作业效果,因此需进一步对落梳末端执行器进行研究。
针对香蕉果柄及果轴个体差异性较大的生长特征,本文基于张合式刀具设计一种新型香蕉落梳末端执行器,通过调整张合角度适应不同品种、不同弧长的香蕉果柄,以实现自上而下的连续落梳。以落梳速度、落梳入切角及刀刃角为试验因素,以峰值切割力和切口质量为试验评价指标,采用响应面分析法对末端执行器落梳性能进行优化设计。
以种植面积最多、处于收获期的巴西蕉(Musa Acuminate,AAA group,cv. Brazil)为研究对象,蕉穗生长过程中香蕉梳把呈簇状分布在香蕉果轴上,每把香蕉分别由两排香蕉果指上下堆叠而成,相邻的蕉梳之间存在一定的高度差和角度差[13],如图1所示。对香蕉园种植管理农艺要求的调查研究表明,香蕉断蕾时,蕉农们为确保断蕾后的香蕉梳把能够长成大而饱满的香蕉,一般保留7~8梳香蕉。根据农艺调查,选择处于收获期、新鲜收获的蕉穗进行了相关参数测量,包括蕉穗质量、果柄内弧长、果柄外弧长、果柄轴向间距、果柄轴向高度差,各参数示意图如图1所示。测量统计结果如表1所示。
落梳刀具结构是香蕉落梳末端执行器核心部件,合理的刀具结构可降低落梳切割阻力和功耗,同时提高落梳效率和改善香蕉果柄切口质量。由表1可知,蕉穗不同位置果柄之间内外弧长标准差较大,为实现连续落梳需落梳刀具具备一定的仿形能力以满足不同大小果柄自适应。因此,刀具设计应考虑香蕉果柄弧长及果柄轴向高度差等物理特性参数,避免在落梳过程中造成切散完整果柄或切到下一梳果柄而导致落梳失败。
为适应不同香蕉品种果柄生长差异性较大的特点,落梳末端执行器主刀刃口设计成弧形,前期落梳装置研究结果表明[14],单把弧形落梳刀难以完成整条蕉连续落梳,因此设计成基于张合式变化的主副刀刃以满足不同果柄弧长的落梳刀具。
对于不同香蕉品种的果柄能通过调节张合式刀具角度变化适应其弧长。当果柄内外弧长关系满足
式中
      Li——果柄内弧长,mm
      Lo——果柄外弧长,mm
      Lm——中间主刀有效刀刃弧长,mm
仅需用中间主刀进行香蕉果柄的切割落梳,两副刀在落梳过程中保持张开最大角度。
当果柄内外弧长关系满足
式中
      Lb——副刀刀刃有效长度,mm
主刀中心位置对准果柄的切割点,副刀夹持果柄位置上方的果轴以保证落梳末端执行器能稳定可靠地进行落梳动作。
由表1可知,香蕉果柄内弧长和外弧长平均值为84.81、113.35 mm,标准差为21.54、31.98 mm,因此落梳刀刀刃有效弧长不宜过大或过小,此时取主刀刀刃有效弧长Lm为65 mm,副刀刀刃有效长度Lb为39 mm,可在张合式刀具有效切割刃弧长范围内满足不同品种香蕉落梳工作要求。
落梳末端执行器张合角对不同品种、不同果柄位置的香蕉果柄切割力和切口质量具有较大的影响。如表1所示,巴西蕉果穗果柄外弧长最大约为146 mm,果柄内弧长最大约为106 mm。
为了更好地实现多品种香蕉果柄落梳,设计落梳末端执行器张合角范围如图2所示,取落梳末端执行器张合角为71°~107°。刀具张合角变化是通过丝杠电机驱动丝杠螺母,由丝杠旋转运动转换为直线运动后推动连杆,从而驱动两侧副刀实现张合角度变化。刀具张合角变化量与丝杠螺母直线运动位移变化量之间的函数关系式为
其中
式中
      Δθ——刀具张合角变化量,(°)
      ΔS——丝杠螺母直线运动位移变化量,mm
      n——丝杠电机转速,r/min
      L——丝杠螺纹导程,mm
      ΔT——运动时间变化量,s
由于香蕉果轴及果柄个体差异较大,且蕉穗质量和体积都较大,香蕉果轴弯曲度限制着机械化落梳刀具实现连续落梳,在落梳过程中落梳刀具容易插入果轴而导致香蕉落梳失败。由图1可知,蕉穗梳把间呈堆叠的形态,且沿着果轴不规则螺旋分布,果柄弧长长短不一[15],要求所设计的落梳末端执行器需要具备较好的自适应性能,通过调节张合角从而改变刀具切割刃覆盖范围以适应不同弧长果柄。
基于蕉穗生长特性,为了避免果指干扰,落梳时采用图1方式悬挂,末端执行器自上而下运动,从而实现连续落梳任务。在落梳过程中,峰值切割力主要出现在张合式刀具切入果柄过程,参照文献[5]及现有农用人工落梳刀刀尖角设计,设置张合式刀具刀尖角为120°。由于中间主刀与两侧副刀之间为铰链连接,连接处下方存在较大空隙,为保证结构完整性及能够将果柄完整地切割下来且获得较好的切口质量,两侧副刀分别在铰链连接处下方位置设置弧形刀位补偿。
综合考虑落梳末端执行器与机械臂末端处连接结构轻量化,以及保证末端执行器刚度能满足落梳要求,落梳末端执行器如图3所示。
由图3可知,末端执行器主要包括丝杠电机、连杆机构、中间主刀及两侧副刀。电机通过丝杠螺母将旋转运动转换成直线运动,再通过连接在副刀上的连杆调节张合角,从而改变刀具切割刃覆盖范围。主刀和两侧副刀之间通过上下两处光杆螺栓铰链连接。主刀为三边开刃,副刀为底边及外侧开刃,以降低落梳阻力和峰值切割力。为避免刀具在落梳过程中的弯曲变形,在中间主刀折弯处设置加强筋板。采用厚3 mm的铝方管连接整个落梳末端执行器与机械臂。
为保证落梳末端执行器在落梳过程中刀具不发生弯曲变形或断裂失效,主刀和副刀用于切割部分刀具最大厚度为2 mm。同时,对整个末端执行器进行了轻量化设计,末端执行器所用的连杆及连接板采用铝合金材料加工;而末端执行器上张合式刀具在结合刀具耐磨性及刚度需要满足落梳作业条件,并在保证较低的加工成本前提下,选择采用316L不锈钢材料,通过3D金属打印的方式加工制成。其结构参数如表2所示。
当张合式刀具插切果柄时,由于香蕉果柄维管组织系统包括木质部、韧皮部和维管束鞘等,若刀具贴合香蕉果轴往下插切落梳,刀具可能会插入果柄下方果轴或无法切断果柄下方连接的果轴表皮,导致落梳失败。为减少该情况发生,在中间主刀上方位置增加凸起补偿块,同时张合式刀具采用铰链连接,铰链安装在靠近果轴一侧,铰链凸起也可避免刀具过度贴合香蕉果轴。
为保证刀具刚度和可靠性,对落梳刀插切果柄进行受力分析,如图4所示。刀具在插切果柄过程中主要受到刀刃阻力Ff,正刀面受到的刀面摩擦力F1和法向载荷N1、后刀面受到的刀面摩擦力F2和法向载荷N2。刀具落梳过程的切割力受刀面摩擦力、刀面载荷和刀刃阻力影响,通过受力分析可得
其中
式中
      α——落梳入切角,(°)
      γ——刀刃角,(°)
      μ——刀具与果柄之间的摩擦因数
选择张合式刀具张合角为90°时,在Solidworks中建立落梳末端执行器三维模型,针对张合式刀具模型导入ANSYS/Workbench中进行静力学分析,材料为316L不锈钢,参数如表3所示。由文献[16]可知,落梳刀具切割果柄最大切割力约为300 N,因此,在落梳刀具刀刃上施加与刀面平行的切割力300 N,在中间主刀刀座上添加固定约束,对落梳刀具进行网格划分,求解得落梳刀具应力云图和总变形量云图,如图5所示。
由表3可知,落梳刀具屈服强度为205 MPa,而张合式刀具所受最大应力约为58.147 MPa,最大变形量约为0.236 8 mm,能够满足落梳性能要求。由图5a可看出,落梳刀具最大应力位置处于中间主刀上方加强筋板处,主刀和副刀铰链连接处并未产生应力集中的情况,两侧副刀通过铰链螺栓与主刀连接,主刀加强筋板的设计在一定程度上抑制了主刀折弯变形,同时平衡了大部分切割载荷。由图5b可知,张合式刀具在载荷作用下最大变形量主要发生在两侧副刀刀尖部分,该变形量小且不足以引发刀具断裂失效,表明所设计的末端执行器具有足够的强度和刚度进行落梳作业。
机器人智能化落梳试验平台主要由6自由度机械臂、深度相机、落梳末端执行器、蕉穗旋转夹持装置、便捷式计算机、控制箱和机架组成。6自由度机械臂型号为BRTIRUS-1510A(伯朗特机器人股份有限公司,东莞),额定电压220 V、最大运行半径1.5 m、重复定位精度±5 mm;落梳末端执行器主要由主刀、两侧副刀、丝杠电机和连接部件组成,可对香蕉果柄进行落梳作业,丝杠电机作为末端执行器张合动作驱动件,其重复定位精度为±0.03 mm,保持扭矩为0.17 N·m,水平空载最大速度30 mm/s;蕉穗旋转夹持装置主要由铝合金转盘和香蕉果轴夹钳组成,其中铝合金转盘固定在机架上,用于带动蕉穗旋转至果柄位置正对机械臂落梳末端执行器一侧,以确保落梳末端执行器在切完一梳后,蕉穗旋转一定角度(不同蕉穗形态参数不同)后进行下一梳香蕉落梳准备工作。香蕉果轴夹钳固定在铝合金转盘上,用于夹持果轴上端从而减缓落梳时整串蕉穗摇摆,同时起到夹持支撑整串蕉穗质量的作用,避免在落梳过程中整串蕉穗掉落。控制箱主要集成了6自由度机械臂控制以及张合式落梳刀具张合角控制,整机结构如图6所示。
机器人智能化落梳过程如图7所示。落梳机器人处于初始位姿时,为了便于立体视觉深度相机采集当前果柄图像信息,控制落梳末端执行器底部中间位置与首梳果柄距离约0.3 m。通过深度相机采集当前果柄图像并传输至便携式计算机,使用团队前期研究的改进DeepLabv3+网络模型识别检测出最近的果柄区域[17],计算出香蕉果柄切割点三维坐标,再通过已标定的坐标转换关系,将切割点三维坐标转换至机械臂坐标系下相对于落梳末端执行器的位置坐标,然后控制箱驱动机械臂使末端执行器运动至果柄切割点上方;末端执行器上丝杠电机驱动两侧副刀调整张合角以适应不同弧长果柄,最后控制箱驱动末端执行器向下运动实现最近果柄的落梳。深度相机识别并检测下一梳果柄与末端执行器的旋转角度,通过控制旋转夹持装置将悬挂的蕉穗旋转相应角度后,重复上述步骤进行下一梳落梳,直至完成蕉穗连续落梳。
为了进一步提高末端执行器工作性能,同时为后续响应面优化提供可靠的数据依据[18],进行单因素试验。
对于香蕉智能化落梳,张合式刀具是直接与香蕉果柄接触及切割果柄的关键机构,对香蕉落梳成功率和落梳切口质量具有重要影响[19]。主要影响因素有:落梳速度v、落梳入切角α、刀刃角γ、刀刃周长l、刀具厚度b等。其中,刀刃周长l由表1中果柄内弧长和外弧长平均值确定,可覆盖大部分香蕉果柄弧长,能满足落梳刀具设计要求;而刀具厚度b为刀具抗弯截面系数的重要影响参数,实际使用过程中能够保持切割过程平稳、不发生大变形或失效即可。因此刀刃周长l和刀具厚度b不再作为重点考虑因素,本文以落梳速度、落梳入切角、刀刃角为试验因素,分析其对落梳末端执行器落梳性能的影响。
试验对象为产自广州番禺蕉园的巴西蕉。随机选取15串处于成熟期的蕉穗,保证每组试验所切蕉穗果柄在果轴上分布的位置一致。
将落梳末端执行器张合式刀具与香蕉果柄接触过程的相互作用力定义为落梳刀具对香蕉果柄的切割力。将落梳速度、落梳入切角、刀刃角作为试验影响因素,分别以峰值切割力和切口质量作为试验评价指标,评估落梳末端执行器工作性能。
其中,果柄切口质量评判按农艺经验进行分级评分:等级评分为90~100分、80~90分、70~80分、60~70分4个等级[16]。当梳把被切散时,果柄切口质量为60~70分;当梳把未被切散且果轴表皮被部分撕扯下来,落梳切口非常不平整或特别靠近果指时,果柄切口质量为70~80分;当梳把未被切散且果轴表皮未被切割,切口比较平整且与果指分叉口之间距离较合适时,果柄切口质量为80~90分;当梳把未被切散且果轴表皮未被切割,切口平整且与果指分叉口之间距离合适时,果柄切口质量为90~100分。
落梳速度选取主要依据机械臂在落梳工作情况以及机械臂末端最大运动速度限制选定,速度太小落梳效率太低,因此落梳速度取机械臂末端最大运动速度的20%~100%,即0.4~2.0 m/s。在落梳试验过程中,蕉穗被夹持旋转装置反向夹持吊挂着,在实际落梳生产过程中,落梳刀具向下切割果柄时在竖直方向存在一定倾角,即落梳入切角,选用不同落梳入切角所获得的果柄切割峰值力不同,落梳入切角过大也会影响落梳成功率及切口质量,可能会导致落梳刀具切入果轴而落梳失败,文献[20]研究表明较优的切割倾角为0°~15°,因此结合前期落梳预试验确定落梳入切角为0°~12°。而刀刃角是体现落梳刀具锋利程度,刀刃角越大,则刀具切割果柄所受的阻力越大,刀刃越小则刀具刚度和强度较小,切割果柄过程中容易磨损或崩刃,文献[21]研究表明,在一定的落梳速度和入切角时,刀刃角为5°~30°之间切割效果较好,故落梳刀具刀刃角取5°~25°。为减小试验误差,每组试验重复3次,结果取平均值。
落梳末端执行器对香蕉果柄落梳试验过程分为4个阶段,分别为挤压阶段、切割阶段、切断阶段、落梳完成,如图8所示。
对果柄的切口质量和峰值切割力进行单因素试验,试验结果如图9所示。
由图9a可知,当刀刃角和落梳入切角分别为15°和6°时,峰值切割力随落梳速度增大而减小,果柄切口质量随落梳速度呈先降低后升高再降低的趋势;由图9b可知,当刀刃角和落梳速度分别为15°和1.2 m/s时,峰值切割力随着落梳入切角的增大,呈先减小后增大的变化趋势,而切口质量总体呈先升高最后降低趋势;由图9c可知,当落梳入切角和落梳速度分别为6°和1.2 m/s时,峰值切割力随着刀刃角增大而增大,果柄逐渐难以被切断,切口质量总体呈逐渐下降趋势。综合考虑峰值切割力较小,切口质量较优时,各试验因素最佳参数范围为:落梳速度为1.2~2.0 m/s、落梳入切角为3°~9°、刀刃角为5°~15°。
为研究落梳过程中多因子交互作用机制并获取最优参数组合,以落梳速度、落梳入切角及刀刃角为试验因素,选择峰值切割力、切口质量为试验评价指标开展响应面优化试验。
试验对象仍为产自广州番禺蕉园的巴西蕉,随机选取17串处于成熟期的蕉穗作为样本。基于单因素试验结果,实施三因素三水平的Box-Behnken响应面优化试验。选取落梳速度(1.2~2.0 m/s)、落梳入切角(3°~9°)、刀刃角(5°~15°)3个关键参数作为试验因素。试验因素编码如表4所示。
通过Design-Expert 13软件对试验数据进行回归性分析和因素方差检验,确定各因素对响应指标影响的显著性[22-25],并建立峰值切割力Y1和切口质量Y2回归模型。
响应面优化试验结果如表5所示,表中X1、X2、X3为因素编码值。对结果进行二次多项式回归模型拟合,得到了峰值切割力与切口质量回归模型为
对峰值切割力与切口质量的预测模型进行方差分析,结果如表6所示。由表6可知,峰值切割力和切口质量预测模型P均小于0.01,且失拟项P均大于0.05,表明峰值切割力和切口质量的回归模型极显著,具有较好拟合度,可用于落梳末端执行器落梳参数优化。
对于Y1,X2的P小于0.01,对峰值切割力影响极显著,X3、X1X3和的P小于0.05,对峰值切割力影响显著,而其余项对峰值切割力影响不显著。对于Y2,X2、X3、和的P小于0.01,对切口质量影响极显著,X1X3和的P小于0.05,对切口质量影响显著,其余项对切口质量影响不显著。由表6可知,各因素对落梳性能2个评价指标影响由大到小为落梳入切角、刀刃角、落梳速度。落梳速度、落梳入切角和刀刃角之间的交互作用对评价指标的影响如图10所示。
将落梳性能评价指标峰值切割力最小值和切口质量最大值作为优化目标,运用Design-Expert软件中的Optimization功能对落梳末端执行器的3个因素进行优化,目标函数和约束条件为
优化求解得到落梳末端执行器工作性能最佳参数为:落梳速度为2 m/s、落梳入切角为5.77°、刀刃角为5°,此时峰值切割力为32.60 N,切口质量为82.55分。
为了验证二次多项式回归模型获得最优落梳参数的准确性,试验材料随机选取5串处于成熟期、新鲜采摘的巴西蕉。以落梳速度2 m/s、落梳入切角5.77°、刀刃角5°进行试验,试验重复25次,以香蕉落梳试验峰值切割力和切口质量作为试验结果。试验结果为:成功落梳23梳,峰值切割力平均值为31.49 N,与预测值相对误差为3.4%;切口质量平均值为84分,与预测值相对误差为1.8%,落梳成功率为92%。结果表明评价指标预测值与实际测量值相近,相对误差均小于5%,验证了峰值切割力和切口质量回归拟合模型的准确性,所优化的香蕉落梳末端执行器最优工作参数组合可满足实际香蕉落梳环节应用要求。
(1)基于张合式刀具结构,设计了香蕉落梳末端执行器,通过调整刀具张合角可适应切割不同弧长的香蕉果柄。
(2)搭建了基于6自由度机械臂机器人智能化落梳试验平台,通过单因素试验与响应面优化试验,建立的峰值切割力与切口质量回归模型整体极显著(P<0.01)且无显著失拟(失拟项P>0.05),表明模型拟合度优异。影响落梳效果显著性由大到小为:落梳入切角、刀刃角、落梳速度。
(3)获得最优参数组合为:落梳速度2 m/s、落梳入切角5.77°、刀刃角5°。在最优参数组合下进行验证试验,得到峰值切割力平均值为31.49 N,切口质量平均值为84分,切口质量较好,与预测值相对误差均小于5%。验证试验中落梳成功率为92%,证明模型预测准确且参数可有效应用于实际香蕉落梳作业。
  • 国家自然科学基金项目(32271996)
  • “十四五”广东省农业科技创新十大主攻方向“揭榜挂帅”项目(2023SDZG03)
  • 国家现代农业产业技术体系项目(CARS-31-11)
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2025年第56卷第12期
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doi: 10.6041/j.issn.1000-1298.2025.12.034
  • 接收时间:2024-09-29
  • 首发时间:2026-09-30
  • 出版时间:2025-12-25
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  • 收稿日期:2024-09-29
  • 修回日期:2024-10-28
基金
国家自然科学基金项目(32271996)
“十四五”广东省农业科技创新十大主攻方向“揭榜挂帅”项目(2023SDZG03)
国家现代农业产业技术体系项目(CARS-31-11)
作者信息
    1.华南农业大学工程学院,广州 510640
    2.广东海洋大学机械工程学院,湛江 524088
    3.佛山市中科农业机器人与智慧农业创新研究院,佛山 528200

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杨洲(1972—),男,教授,博士生导师,主要从事水果生产机械化与信息化研究,E-mail:
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https://castjournals.cast.org.cn/joweb/nyjxxb/CN/10.6041/j.issn.1000-1298.2025.12.034
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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