Design and experimental study of the self-adaptive splitting technology of lotus seeds

被引:1
|
作者
Lu, Ange [1 ]
Ma, Qiucheng [1 ]
Ma, Jie [2 ]
机构
[1] Xiangtan Univ, Sch Mech Engn, Xiangtan 411105, Hunan, Peoples R China
[2] Univ Lancaster, Fac Sci & Technol, Lancaster LA1 4YW, Bailrigg, England
基金
中国国家自然科学基金;
关键词
lotus seed; lotus plumule; splitting process; mechanical design; optimization; NELUMBO-NUCIFERA; OPTIMIZATION; QUALITY;
D O I
10.1139/tcsme-2019-0297
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The lotus plumule has high medicinal value and is an important part of the lotus seed. Usually, the lotus seed must be split symmetrically into two halves through a splitting process to obtain an intact lotus plumule. However, this process is difficult to mechanize and automate, as different lotus seeds are of different sizes. In this study, a novel automatic self-adaptive splitting technology (SAST) is proposed for lotus seeds, based on a specially designed combined linkage mechanism and a roller pair centering mechanism. The technology can automatically adjust the position of the splitting point taper punch according to the size of the lotus seed and ensure that the tip of the punch is on the axis of the lotus seed. First, the centering deviation of the centering mechanism was analyzed. A mathematical model for the SAST was developed, and the key parameters were optimized using the firefly algorithm. An automatic splitting machine and a test bench were designed for centering deviation measurements, and both centering and splitting experiments were conducted. The generated maximum centering deviation of the SAST was <0.176 mm; the highest accurate splitting rates of 95% and 93.05% were achieved for unclassified and graded lotus seeds, respectively.
引用
收藏
页码:92 / 102
页数:11
相关论文
共 50 条
  • [31] Applying Digital Evolution to the Design of Self-Adaptive Software
    Beckmann, Benjamin E.
    Grabowski, Laura M.
    McKinley, Philip K.
    Ofria, Charles
    2009 IEEE SYMPOSIUM ON ARTIFICIAL LIFE, 2009, : 100 - 107
  • [32] Design Patterns for Self-Adaptive RTE Systems Specification
    Ben Said, Mouna
    Kacem, Yessine Hadj
    Kerboeuf, Mickael
    Ben Amor, Nader
    Abid, Mohamed
    INTERNATIONAL JOURNAL OF RECONFIGURABLE COMPUTING, 2014, 2014
  • [33] Self-adaptive stepsize search for automatic optimal design
    Nolle, L.
    Bland, J. A.
    KNOWLEDGE-BASED SYSTEMS, 2012, 29 : 75 - 82
  • [34] Design of self-adaptive fuze system based on MEMS
    School of Mechatronics Engineering, Univ. of Electron. Sci. and Technol. of China, Chengdu 610054, China
    Dianzi Keji Diaxue Xuebao, 2006, 6 (932-935):
  • [35] Tutorial: A Design for Adaptation Framework for Self-Adaptive Systems
    De Sanctis, Martina
    Marconi, Annapaola
    2018 IEEE 3RD INTERNATIONAL WORKSHOPS ON FOUNDATIONS AND APPLICATIONS OF SELF* SYSTEMS (FAS*W), 2018, : 3 - 4
  • [36] Design and research of self-adaptive learning diagnosis agent
    Tian L.
    Hong Z.
    Journal of Convergence Information Technology, 2010, 5 (01) : 54 - 59
  • [37] Design of a power efficient self-adaptive LVDS driver
    Xu, Hanyang
    Wang, Jian
    Lai, Jinmei
    IEICE ELECTRONICS EXPRESS, 2018, 15 (05):
  • [38] On the Mechanical Design and Control of a Self-Adaptive Exoskeleton Chair
    Liao, Yongqiang
    Wang, Can
    Wu, Xinyu
    Lu, Feng
    Wang, Pingan
    Cai, Shibo
    2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, 2015, : 937 - 942
  • [39] Study on self-adaptive fuzzy neural networks
    Liu, Fang
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES, 2007, 2 : 335 - +
  • [40] Decentralized Self-Adaptive System: A Mapping Study
    Quin, Federico
    Weyns, Danny
    Gheibi, Omid
    2021 INTERNATIONAL SYMPOSIUM ON SOFTWARE ENGINEERING FOR ADAPTIVE AND SELF-MANAGING SYSTEMS (SEAMS 2021), 2021, : 18 - 29