During the experiment, non‐uniform data with nocertain trends was obtained by using CMOS camera inthree values of DBCL to extract entropy.Results of using CCD camera were also not reliable forDCBL 30cm and 50cm, but data for DCBL 40cm had anacceptable trend for extracting entropy feature.Figure 4 and Figure 5 illustrate the timeline of theextracted homogeneity at 12:00 am as averagedvalues obtained from the cucumber crops.Figure 5. Timeline of the extracted homogeneity at 12:00 amas averaged values obtained from cucumber crops by CCDcamera when DBCL is: (a) 30cm, (b) 40cm, and (c) 50cmAs older plants’ leaves are more colourful withdifferent shades of green, the related gray‐level pixeldistribution (homogeneity) decreases over time.Conversely, the younger plants, being more unified incolour, have higher homogeneity values [3]. Duringthe experiment, non‐uniform data with no certaintrends was obtained by using CMOS camera in threevalues of DBCL to extract homogeneity. Results ofusing CCD camera were also not reliable for DCBL 30cmand 50cm, but data for DCBL 40cm had an acceptabletrend for extracting homogeneity feature.CONCLUSIONSIn this study, a machine vision system was developedto evaluate the performance of CCD and CMOScameras for real‐time monitoring of plant growth in agreenhouse. Entropy and homogeneity weremeasured as textural features for greenhouse plantleaves’ image in an experiment for cucumber crops.The leaf samples were brought to the laboratory fromthe greenhouses to measure the textural features. The64ACTA TECHNICA CORVINIENSIS – Bulletin of Engineeringeffect of Distance between Camera and Leaves (DBCL)for three values (30, 40 and 50cm) and the type ofcamera (CMOS and CCD) on the uniformity of resulteddata were considered in this article.Results showed that non‐uniform data with no certaintrends was obtained by using CMOS and CCD camera intwo values of DBCL (30cm and 50cm) to extractentropy. Data for DCBL 40cm with a CCD camera hadan acceptable trend for extracting both of entropyand homogeneity features.ACKNOWLEDGEMENTThe authors would like to thank the University of Tehran forsupport of this research project.REFERENCES[1.] Asefpour Vakilian, A. and Asefpour Vakilian, K., A NewSatellite Image Segmentation Enhancement TechniqueFor Weak Image Boundaries, Annals of FacultyEngineering Hunedoara ‐ International Journal ofEngineering, X(2), 2012.[2.] Asefpour Vakilian, K. and Massah, J., Design,Development and Performance Evaluation of a Robotto Early Detection of Nitrogen Deficiency inGreenhouse Cucumber (Cucumis sativus) with MachineVision, International Journal of Agriculture: Research &Review, 2(4), 2012.[3.] Asefpour Vakilian, K. and Massah, J., Non‐linear GrowthModeling of Greenhouse Crops with Image TexturalFeatures Analysis, International Research Journal ofApplied and Basic Science, 3(1), 2012.[4.] Boyle, W.S. and Smith, G.E., Charge CoupledSemiconductor Devices. Bell System and TechnologyJournal, 49(4), 1970.[5.] Gonzalez, R. and Woods, R, Digital image processing.Addison‐Wesley, New Jersey, 2002.[6.] Haralick, R.M., Shanmugam, K., Dinstein, I., Texturalfeatures for Image Classification, IEEE Transactions onSystems, Man, and Cyberentics, 3(6), 1973.[7.] Jain, R., Kasturi, R. and Schunck, B.G., Machine Vision.McGraw‐Hill, 1995.[8.] Ling, P.P, Giacomelli, G.A. and Russell, T.P., Monitoringof plant development in controlled environment withmachine vision, Adv. in Space Research, 18(4‐5), 1996.[9.] Meyer, G.E., Troyer, W.W., Fitzgerald, J.B. andPaparozzi, E.T., Leaf nitrogen analysis of poinsettia(Euphorbia Pulcherrima Will D.) using spectralproperties in natural and controlled lighting. AppliedEngineering in Agriculture, 8(5), 1992.[10.] Penuelas, J. and Filella, I., Visible and near‐infraredreflectance techniques for diagnosing plantphysiological status, Trends in Plant Science, 3, 1998.[11.] Shearer, S.A. and Holmes, R.G., Plant identificationusing colour co‐occurrence matrices, Transactions onASAE, 33(6), 1990.[12.] Story, D., Kacira, M., Kubota, C., Akoglu, A., An, L.,Lettuce calcium deficiency detection with machinevision computed plant features in controlledenvironments, Computers and Electronics inAgriculture, 74, 2010.[13.] Tompsett, M.F., Amelio, G.F., Bertram, W.J., Buckley,R.R., McNamara, W.J., Mikkelsen, J.C. and Sealer, D.A.,Charge‐coupled imaging devices: Experimental results,IEEE Transactions on Electronic Devices. 18(11) 1971.[14.] Ushada, D., Murase, H. and Fukuda, H., Non‐destructivesensing and its inverse model for canopy parametersusing texture analysis and artificial neural network,Computers and Electronics in Agriculture, 57, 2007.[15.] Zheng, C., Sun, D.W. and Zheng, L., Recent applicationsof image texture for evaluation of food qualities‐areview Trends in Food Science and Technology, 17,2006.2012. Fascicule 3 [July–September]
1.Imre Zsolt MIKLOS, 2. Cristina Carmen MIKLOS, 3. Carmen Inge ALICCAM PROFILE COMPUTER AIDED DESIGN PLOTTING1.UNIVERSITY „POLITEHNICA” TIMIŞOARA, FACULTY OF ENGINEERING HUNEDOARA, ROMANIAABSTRACT: This paper shows how to plotting the profile of a plane rotating cam and a follower in the translational move,using Matlab program. Are shown how input the variables, kinematic analysis, speeds hodograph in graphical form,respectively plane cam profile designed, with a choice of several options for the best solutions.KEYWORDS: Cam, follower, cam profileINTRODUCTIONThe transformation of one of the simple motions, suchas rotation, into any other motions is oftenconveniently accomplished by means of a cammechanism A cam mechanism usually consists of twomoving elements, the cam and the follower, mountedon a fixed frame. Cam devices are versatile, andalmost any arbitrarily‐specified motion can beobtained. In some instances, they offer the simplestand most compact way to transform motions.A cam may be defined as a machine element having acurved outline or a curved groove, which, by itsoscillation or rotation motion, gives a predeterminedspecified motion to another element calledthe follower. The cam has a very important function inthe operation of many classes of machines, especiallythose of the automatic type, such as printing presses,shoe machinery, textile machinery, gear‐cuttingmachines, and screw machines. In any class ofmachinery in which automatic control and accuratetiming are paramount, the cam is an indispensablepart of mechanism.Cam mechanisms design, respectively profileobtaining, may be realize by many methods. The firstdesign methods for cam mechanisms war graphical.These methods require many graphical constructionswith low precision. With the new entry calculationsystems, have develop analytical methods to obtaincam profile by software writing (Basic, C++, Matlab,MathCAD, etc). These methods are faster, giving tothe plant designer varieties data results and charts.Plotting a plane cam profile requires knowledge ofsome initial elements of calculation. These are: The motion phases based on the technologicalprocess data, defined by the anglesof lifting, high stationary, going down and downstationary, respectively follower race (lineardisplacement respectively oscillating) Law of motion, which is chosed by thedesigner according to the angles values thatdefine motion phases and by the value of theangular velocity of the cam. In most cases law ofmotion is chosen depending on the maximumacceleration of the follower (for the reasons ofinertia forces equilibration), respectivelyon the acceleration jump from one phase toanother. Maximum pressure angle (between the followerand cam) Motion (linear or oscillating) and follower form Follower roller radius (if necessary), according tothe minimum radius of basic circle Expansion joints (if necessary)Plotting a plane cam profile can be made by graphicalmethods and analytical method. In both cases thedesign involves the following steps: Kinematic analysis of a cam mechanism,respectively the graphical representation ofdisplacement variation and follower low speeddepending on the cam rotational angle Velocities hodograph building Determination of minimum radius of curvature ofthe cam Checking the contact pressure Entering in calculations the expansion joints (ifnecessary) Establishing minimum radius of the cam basecircle, respectively the radius of the roller follower(if necessary) Cam profile constructionPROGRAM AND RESULTS PRESENTATIONPlane rotating cam plotting profile, with follower intranslation moving, was made with mathematicalformulas provided by analytical methods [2], using acomputer program designed and written in Matlabprogramming environment.For the case study was considered a cam mechanismhaving the follower parabolic law ofmotion, respectively the following input data definedby the technological process requirements: Follower lift: h = 50 mm Uplift angle: ϕ 1 = 150 grade Upper stationary angle: ϕ 2 = 30 grade Down angle: ϕ 3 = 150 grade Pressure angle allowed: δ = 30 grade Eccentricity: e = 10 mmWhen the computer program is launching appear adialog box with the user, from which will beintroduced the input data (dialog box defined withthe input procedure). This is shown in Figure 1.Based on input data (defined by the technologicalprocess) computer program make graphicrepresentation of displacement and follower lowspeed depending on cam rotation angle (Fig. 2),© copyright FACULTY of ENGINEERING ‐ HUNEDOARA, ROMANIA 65
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Ioan MILOŞANTransilvania Universit
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