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DOI: 10.15507/0236-2910.028.201802.148-163

 

Dielectric Permeability of Forestry Depending on Environmental Parameters in Radio Frequency Monitoring

  

Vladimir V. Pobedinsky
Professor, Chair of Service and Technical Operation, Ural State Forestry University (37 Sibirskiy Trakt St., 620100 Ekaterinburg, Russia), D.Sc. (Engineering), ResearcherID: G-3245-2018, ORCID: https://orcid.org/0000-0001-6318-3447, This email address is being protected from spambots. You need JavaScript enabled to view it.

Asgat M. Gazizov
Professor, Chair of Fire Protection and Industrial Safety, Ufa State Oil Technical University (5/14 Kosmonavtov St., Ufa 500064, Russia), D.Sc. (Engineering), ResearcherID: G-4307-2018, ORCID: https://orcid.org/0000-0001-7940-8444, This email address is being protected from spambots. You need JavaScript enabled to view it.

Sergey P. Sannikov
Associate Professor, Chair of Automation of Production Process, Ural State Forestry University (37 Sibirskiy Trakt St., 620100 Ekaterinburg, Russia), ResearcherID: G-4047-2018, ORCID: https://orcid.org/0000-0002-6135-6954, This email address is being protected from spambots. You need JavaScript enabled to view it.

Andrey A. Pobedinskiy
Senior Lecturer, Chair of Forestry and Applied Mechanics, State Agrarian University of the Northern Trans-Urals (18, Roshinskoye Shosse, Tyumen 625621, Russia), ResearcherID: G-3777-2018, ORCID: https://orcid.org/0000-0001-7548-3076, This email address is being protected from spambots. You need JavaScript enabled to view it.

Introduction. New approach to forestry monitoring is presented. The relevance of the study is caused by the need to improve the forest management system based of modern information technologies. The paper demonstrates radio frequency monitoring as a most effective solution using a network of radio-frequency devices. This system quickly tracks the movement of forest resources, detect forest fires at the beginning of smoke and perform other functions. Complex dielectric permittivity is one of the main parameters for the design and operation of the system. The usual statistical methods do not allow obtaining such permeability. Thus, the aim of the study is to find a functional dependence of the permittivity on the parameters of the forest environment based on fuzzy inference.
Materials and Methods. Mathematical and fuzzy modeling are methods of theoretical research in this paper. In addition, methods of forest inventory and logging processes, information theory and signaling, mathematical statistics, and experimental theory were used to perform experimental studies on approbation of a radio frequency monitoring system and to verify the adequacy of the proposed fuzzy model. We used Fuzzy Logic Toolbox software with MatLab technical computing software as a tool for synthesis.
Results.The dependence of the permittivity on the parameters of the forest environment based on fuzzy inference was obtained. Formally, the total complex dielectric constant εк of the forest area (canopy) and the values of the input quantities are determined as follows: εк = f (Vi , α), where Vi – volume fraction of i component of the forest environment (in real conditions, according to experimental data, is from 0 to 0,5); α – constant, taking into account the type of forest (from 0 to 0,5 – open area; from 0,5 to 1,5 – pine forest of standard height 25 m; from 1,5 to 2,5 – mixed forest; from 3,5 to 4,5 – birch grove; from 4,5 to 5,0 – spruce forest). A feature of the proposed approach is a discrete representation of the forest environment as a sum of forest elements. This approach provides an accurate measure of the permittivity of the forest environment.
Conclusions. The practical significance of the results lies in the possibility of creating an information support structure for an automated forest management system based on forestry monitoring. The proposed function of the permittivity of the forest area takes into account the main parameters of the forest environment, so it is sufficiently correct. This function is necessary for the design of radio frequency monitoring systems of forestry and allows us to implement a fundamentally new approach to solving the tasks of forest fund monitoring.

Keywords: radio frequency monitoring, forestry, forest, permittivity, complex dielectric permittivity, fuzzy modeling, fuzzy output

For citation: Pobedinsky V. V., Gazizov A. M., Sannikov S. P., Pobedinskiy A. A. Dielectric Permeability of Forestry Depending on Environmental Parameters in Radio Frequency Monitoring. Vestnik Mordovskogo universiteta = Mordovia University Bulletin. 2018; 28(2):148–163. DOI: https://doi.org/10.15507/0236-2910.028.201802.148-163

Authors’ contribution: V. V. Pobedinsky ‒ scientific management, mathematical formulation of the problem and development of a fuzzy model; A. M. Gazizov ‒ writing the draft; S. P. Sannikov ‒ development of experimental studies, testing of the model; A. A. Pobedinskiy ‒ software development for implementing the model, data processing and interpretation.

All authors have read and approved the final version of the paper.

 

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