• MACHINES

    METHODS AND RESULTS OF EXPERIMENTAL RESEARCHES MACHINES FOR AUTOMATIC SORTING EGGS ON THE BASIS OF THE TECHNICAL VISION SYSTEM

    Machines. Technologies. Materials., Vol. 11 (2017), Issue 8, pg(s) 380-383

    This article shows the method and results of experimental RESEARCHES of machines for egg sorting into categories based on size and form using a vision system. The principal difference of the considered machine for automatic sorting of eggs into categories from existing sorting machines is the division of eggs into categories by size and the separation of substandard eggs in the flow. Experimental verification showed that the machine provides the division of eggs in size into four categories and the separation of eggs of irregular shapes and sizes in the flow. The accuracy of separation of eggs into categories depending on the performance. With a productivity of up to two eggs per second, the accuracy of egg separation averages 94.8%., With a productivity of three eggs per second was 87.4%.

  • METHOD AND RESULTS OF EXPERIMENTAL RESEARCHES OF AUTOMATED INSTALLATION FOR DEFINITION OF EGG GEOMETRICAL PARAMETERS BASED ON VISION SYSTEM

    Machines. Technologies. Materials., Vol. 9 (2015), Issue 9, pg(s) 60-63

    A methodology and results of experimental researches of the automated installation for determination of geometric parameters of eggs, based on vision systems, using software LabVIEW and Vision Assistant, is considered in the paper. The installation provides improved performance and accuracy of the measurement of geometrical dimensions and determination of the form coefficients of the eggs.

    The principle of operation of the automated installation is based on non-contact method of measuring large and small diameter, area and perimeter of the eggs, as well as calculation of the values of form coefficients and comparing them with the fluctuation limits of the measured parameters. The basic technical parameters of the automated installation are accuracy of geometric parameters determination, image processing time and performance. Experimental researches were carried out by three stages: an estimation of geometrical parameters measurement accuracy; determination of measurement productivity of eggs geometrical parameters; determination of productivity of eggs division into two categories (relevant and irrelevant to the form requirements of the standard). The obtained experimental results give reason to consider that the measurement accuracy of the linear dimensions of eggs, using the automated installation, meets the technological requirements. Automated installation enhances 4.5 times the labour productivity, spent on measurement of parameters of eggs. The accuracy of separation of eggs into categories, based on the their form using the automated installation, depends on the time, which operator needs for the correct reaction on the signal of the virtual instrument indicator and is equal to 15% at productivity 1,800 eggs per hour and 5.0% at productivity 1200 eggs per hour.

  • EXPERIMENTAL INSTALLATION FOR INVESTIGATION OF THE EGGS AUTOMATIC SORTING INTO CATEGORIES IN STREAM

    Mechanization in agriculture & Conserving of the resources, Vol. 62 (2016), Issue 3, pg(s) 22-24

    A modified flow line for eggs sorting by geometric parameters and forms is discussed in the paper. A method for eggs sorting by shape factor allowing to remove sub-standard eggs is proposed. Also the algorithm for determining the geometric parameters of the eggs using a vision system is considered. The fundamental difference of experimental installation for automatic eggs sorting on the category from existing sorting machines, that share eggs on a category by weight, is separation of eggs on a categories by size and separation substandard eggs in the stream. In the experimental installation mechanism for moving the eggs dismantled and replaced to an endless rope transporter with independent frequency-controlled electric drive. As a result of the experimental verification of system parameters of technical vision on the experimental installation showed that the time required for classification of the eggs is not more than 340 ms.