Please wait a minute...
J4  2010, Vol. 44 Issue (9): 1629-1636    DOI: 10.3785/j.issn.1008-973X.2010.09.001
    
Gene model based conceptual design of mechanism variation
MAI Ze-yu, FENG Yi-xiong, TAN Jian-rong, WEI Zhe
State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, China
Download:   PDF(0KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

Traditional mechanism variation is complex. The genetic expressions of component and kinematic pair composed of inheritance characteristic, variation characteristic and the set of link characteristics, and the genetic expressions of mechanism composed of components characteristic matrix, kinematic pair characteristic matrix and link relation matrix, were summarized by analyzing the comparability between the principle of biologic genetic inheritance and variation and that of  mechanism variation. And a mechanism gene model was created according to the genetic expressions of mechanism. Three rules of mechanism gene variation, according to which six variation operations on the mechanism gene model including voluntary variation, extreme variation, interchanged variation, reversed variation, recombinant variation and hybrid variation were proposed by simulating biological gene mutation, were concluded in order to reserve the inheritance characteristics of the mechanism. The steps of gene model based conceptual design of mechanism variation were explained and the design feasibility was proved by having obtained two variation mechanisms using the method proposed to take variation operations on the original mechanism composed of planar sixbar mechanism, planar fourbar mechanism and ratchet mechanism etc.



Published: 01 September 2010
CLC:  TP 391  
Cite this article:

MAI Ze-Yu, FENG Yi-Xiong, TAN Jian-Rong, WEI Zhe. Gene model based conceptual design of mechanism variation. J4, 2010, 44(9): 1629-1636.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2010.09.001     OR     http://www.zjujournals.com/eng/Y2010/V44/I9/1629


基于基因模型的机构变异方案设计

针对传统机构变异的复杂性,分析了生物基因遗传和变异的机理与机构变异的相似性,总结出由遗传特征、变异特征和联结特征集等特征组成的构件、运动副基因表达式和由构件特征矩阵、运动副特征矩阵和联结关系矩阵等3个矩阵组成的机构基因表达式,并根据机构基因表达式建立了机构的基因模型.为保留机构遗传特征归纳出机构基因变异的3条变异法则,模仿生物的基因突变根据变异法则规定了6种对机构基因模型的变异运算,即自发变异、极端变异、互换变异、反向变异、重组变异和杂交变异等.利用机构的基因模型对由平面六杆机构、平面四杆机构和棘轮机构等组成的原机构进行基因变异运算获得2种变异机构,对基于基因模型的机构变异方案设计的步骤进行了说明,证明了该设计的可行性.

[1] 张向军,桂长林.智能设计中的基因模型[J]. 机械工程学报, 2002, 38(10): 16.
ZHANG Xiangjun, GUI Changlin. Gene models in intelligent computeraided design[J]. Chinese Journal of Mechanical Engineering, 2002, 38(10): 16.
[2] 魏东,翁海珊,陈立周.基于遗传机理的机构构型设计系统的研究:机构创新设计系统研究之四[J]. 机械设计, 2003, 20(6): 911.
WEI Dong, WENG Haishan, CHEN Lizhou. Part Ⅳ of a research on innovatory design system of mechanism:a research on type design system of mechanism based on genetic theory [J]. Journal of Machine Design, 2003, 20(6): 911.
[3] 刘淑珍,何勇,张玉宝,等.连栋玻璃温室轨道式气动天窗机构设计与运动分析[J]. 浙江大学学报:工学版,2006, 40(5): 883887.
LIU Shuzhen, HE Yong, ZHANG Yuba, et al. Design and kinematic analysis for tracktype pneumatic roofvent opener of multispan glass greenhous [J]. Journal of Zhejiang University:Engineering Science, 2006, 40(5): 883887.
[4] LIU Hong, TANG Mingxi, JOHN H F. Supporting creative design in a visual evolutionary computing environment[J]. Advances in Engineering Software, 2004, 35(5): 261271.
[5] CHUNG W Y, CHIANG C H. Fourthorder synthesis of WattⅡsixbar function generators[J]. Mechanism and  Machine Theory, 1990, 25(4): 417426.
[6] 贺淹才.简明基因工程原理[M]. 北京:科学出版社, 1999.
[7] DRLICA K. Understanding DNA and gene clonig:a guide for the CURIOUS[M]. New York: Wiley,1992.
[8] WALKER M R, RAPLEY R. Route Maps in Gene Technology[M]. Oxford: Blackwell Science, 1997.

[1] ZHAO Jian-jun, WANG Yi, YANG Li-bin. Threat assessment method based on time series forecast[J]. J4, 2014, 48(3): 398-403.
[2] ZHANG Tian-yu, FENG Hua-jun, XU Zhi-hai, LI Qi, CHEN Yue-ting. Sharpness metric based on histogram of strong edge width[J]. J4, 2014, 48(2): 312-320.
[3] LIU Zhong, CHEN Wei-hai, WU Xing-ming, ZOU Yu-hua, WANG Jian-hua. Salient region detection based on stereo vision[J]. J4, 2014, 48(2): 354-359.
[4] CUI Guang-mang, ZHAO Ju-feng,FENG Hua-jun, XU Zhi-hai,LI Qi, CHEN Yue-ting. Construction of fast simulation model for degraded image by inhomogeneous medium[J]. J4, 2014, 48(2): 303-311.
[5] WANG Xiang-bing,TONG Shui-guang,ZHONG Wei,ZHANG Jian. Study on  scheme design technique for hydraulic excavator's structure performance based on extension reuse[J]. J4, 2013, 47(11): 1992-2002.
[6] WANG Jin, LU Guo-dong, ZHANG Yun-long. Quantification-I theory based IGA and its application[J]. J4, 2013, 47(10): 1697-1704.
[7] LIU Yu, WANG Guo-jin. Designing  developable surface pencil through  given curve as its common asymptotic curve[J]. J4, 2013, 47(7): 1246-1252.
[8] HU Gen-sheng, BAO Wen-xia, LIANG Dong, ZHANG Wei. Fusion of panchromatic image and multi-spectral image based on
SVR and Bayesian method 
[J]. J4, 2013, 47(7): 1258-1266.
[9] WU Jin-liang, HUANG Hai-bin, LIU Li-gang. Texture details preserving seamless image composition[J]. J4, 2013, 47(6): 951-956.
[10] CHEN Xiao-hong,WANG Wei-dong. A HDTV video de-noising algorithm based on spatial-temporal filtering[J]. J4, 2013, 47(5): 853-859.
[11] ZHU Fan , LI Yue, JIANG Kai, YE Shu-ming, ZHENG Xiao-xiang. Decoding of rat’s primary motor cortex by partial least square[J]. J4, 2013, 47(5): 901-905.
[12] WU Ning, CHEN Qiu-xiao, ZHOU Ling, WAN Li. Multi-level method of optimizing vector graphs converted from remote sensing images[J]. J4, 2013, 47(4): 581-587.
[13] JI Yu, SHEN Ji-zhong, SHI Jin-he. Automatic ocular artifact removal based on blind source separation[J]. J4, 2013, 47(3): 415-421.
[14] WANG Xiang, DING Yong. Full reference image quality assessment based on Gabor filter[J]. J4, 2013, 47(3): 422-430.
[15] TONG Shui-guang, WANG Xiang-bing, ZHONG Wei, ZHANG Jian. Dynamic optimization design for rigid landing leg of crane
based on BP-HGA
[J]. J4, 2013, 47(1): 122-130.