Issue |
E3S Web Conf.
Volume 371, 2023
International Scientific Conference “Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East” (AFE-2022)
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Article Number | 03039 | |
Number of page(s) | 8 | |
Section | Innovations in Environmental Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202337103039 | |
Published online | 28 February 2023 |
Investigation of geometric characteristics of the micro landform of the cutting area as a source of perturbing oscillations of logging machines
Volga State University of Technology, 424000 Yoshkar-Ola, Russia
* Corresponding author: lastochkindm@volgatech.net
The article presents the results of experimental studies of the micro landform of the cutting area surface as a source of perturbing continuous oscillations of the sprung and unsprung masses of the logging machine. The substantiation of the expediency of studying the microprofile of forest support surfaces in the framework of this work is presented. The characteristic of the objects of the experimental study of the micro landform is given. A new measuring complex and the procedure for measuring geometric parameters of irregularities and slopes of the forest support surface of vehicles were proposed. The justification of the number of measurements in the planning of the experiment is given. As a result of data processing after approximation, normalized correlation functions and their approximation coefficients for the studied types of forest growing conditions were obtained. The obtained curves of normalized correlation functions have a decreasing character, which indicates the presence of a strong correlation on a small section of the length and differ in the steepness of the decline and the distance of the correlation, which varies from 1.8 to 11.6 m for different sections. The obtained approximation coefficients quantitatively characterize the perturbing effect of the irregularities of the natural surfaces of cutting areas of various types of forest growing conditions on the movement of logging machines.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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