Експериментально-статистичне дослідження теплиці як об’єкта керування з метою підвищення ресурсоефективності виробництва

Н. А. Заєць, А. О. Дудник, І. Ю. Якименко


УДК 631.2 : 658.2


N. Zaets, A. Dudnyk, I. Yakymenko

Actuality. Competitive struggle between producers of greenhouse products requires the use of advanced technologies, reducing the cost of production, saving energy resources. To do this, the creation of control systems should move from the automation of individual processes to the automation and robotic production in general. In addition, the agro-industrial sector is characterized by the presence of a biological component, the state of which is determined by natural disturbances that are accidental in nature. High energy prices (natural gas, electricity) create conditions for the development of special systems that are able to reduce, but better to minimize energy costs. However, the solution to the problem of increasing resource efficiency of production is impossible without a detailed analytical and experimental study of the links between the productivity of vegetables and energy costs to maintain the necessary technological parameters. Therefore, experimental-static research is a necessary component in the development of resource-efficient growing regimes in greenhouses.

Analysis of recent research and publications. The equipment of greenhouses consists of the following systems: heating of soil and air; irrigation; the introduction of liquid mineral fertilizers and extra-root feeding, the supply of carbon dioxide, ventilation, stinging, systems for the functioning of domestic premises. The system of heating the greenhouses - one of the most important, which provides conditions for growing plants, consists of 132 registers, each of which is made of tubes with a diameter of 50 mm, a length of 150 m, and when its operation consumes the largest amount of energy. Thus, according to the results of the measurements, it was established that for the spring period, the daily consumption of gas for the greenhouse № 9 of PJSC "Kombinat" Teplichny "is 6000 m3. In addition, the electrical complex of such a greenhouse during the day consumes about 6000 kWh of electricity. This is a huge amount of energy, which largely determines the cost of production (the share of energy in the cost of tomatoes in greenhouses is up to 60%).

Data on temperature, humidity and other growth factors of plants in greenhouses are transmitted by sensors to the control panel, where the control equipment automation and its control are concentrated.

The purpose of the research is to increase the resource efficiency of the work of the electrotechnological equipment in greenhouses through the preliminary experimental and statistical study of the control object.

Materials and methods of research. A description of technological objects, processes or technological systems can be presented in the form of mathematical equations, tables and graphs, which represent the connection between the input, output parameters and parameters of the control object model.

The temperature of the light in the greenhouse is adjusted on the account of changes in the hot water temperature in the heating system of the greenhouse. In this case, the greenhouse as an object of temperature control in the capacity of the regulating body will have a crane in the mainstream of the hot water supply from the refrigerant to the heater. At a constant temperature of hot water, provided by the CAC of the heating system, the opening of the crane leads to an increase in the movement of hot water through the heating system and an increase in the amount of heat that goes up to the greenhouse and vice versa. The control action is governed by the temperature regulator in the form of an overhead faucet of the crane at an angle α.

Research results. The method of experimental research to obtain model characteristics of an object involves the presence of probable dependencies between the input and output parameters of the object. Investigation of the energy intensity of the automation facility, namely, the consumption of electricity and natural gas, depending on the environment, was carried out on the example of the workshop No. 9 for 2016.

Using tabular data implies the need to study some of the statistics. The method of experimental and analytical studies of obtaining statistical models is based on the use of the structure of analytical models and the determination of the coefficients of such models experimentally. In carrying out an experiment, the relationship between input and output parameters is obtained in the form of tabular data and to determine the values that do not belong to the nodes of the table, it is necessary to use the methods of probability theory and mathematical statistics.

The use of the StatSoft Statistica software program allows you to analyze the resulting tabular data, determine their distribution frequencies, correlate, obtain the experimental data distribution histogram, and so on.

To determine the nature of the distribution of input variables determine the frequency of fluctuations in their values. The frequency of oscillations is absolute numbers, which show as many times in the aggregate there is a given input value of the parameter, where Valid - the number of tests; Mean - mean values of the sample; St. Dev - standard deviation, which is defined as the root square of the dispersion, and shows how much the individual values of the investigated value are deviating on average from their mean value.

There is a negative correlation, the values are average correlated, that is, there is a dependence of energy costs on the temperature of the environment, but there are a number of exceptions, according to technological requirements.

For a visual assessment of the central trend, we use a scale diagram. In the center of the rectangle there is a median, the upper line corresponds to the maximum value, and the lower one to the minimum. The upper and lower sides of the rectangle correspond to the quartiles.


Consequently, all input parameters describing the microclimate parameters in the greenhouse and external perturbations are distributed according to the normal law. The normal distribution in our case is important in that instead of selecting a large volume of the data set for the input of the neural network for prediction of perturbations and product quality, we can provide some statistical characteristics of the received additive model, which fully describe the nature of the image being analyzed.


Повний текст:



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