Dimension and Quality Specifications of Round Logs Harvested with the Use of Multi-Operational Forest Machines. P.114-130

Complete text of the article:

Download article (pdf, 3.8MB )

UDС

630*811

DOI:

10.37482/0536-1036-2022-5-114-130

Abstract

It is necessary to carry out a statistical assessment of the harvested wood parameters in order to increase the yield of round timber and the overall productivity of logging operations while operating multi-operational forest machines. Modern forestry harvesters are equipped with a variety of CAN control sensors to monitor operation and have onboard software that can collect and store input data on various file types to ensure continuous correct operation. One of the main file types is STM (trunk files). These files are presented in two forms: some contain information for each individual tree trunk in different files, and others store all the data for all trunks in one. The second type of STM files is the most relevant when analyzing the operations carried out at the logging site. However, it is inconvenient to use STM files every time to get information, so there is a need to convert the initial data into a table for easy transfer and decision-making at risk and uncertainty. The article proposes a method for transferring such data to a CSV table using Python pandas, numpy, seaborn, matplotlib programming language libraries, which help to process large data arrays quickly and efficiently and display them graphically. The data obtained by two operators using a medium-class Ponsse Ergo 8W machine in the typical natural and production conditions of the Mondi Syktyvkar JSC (Komi Republic, middle taiga zone) were used for the transfer. The efficiency of the operators’ work was assessed. We obtained functions for determining the volume of a tree trunk on the basis of the reported data from the forest machines. The analysis of structured data on the operation of multi-operational forest machines helps to improve decision-making during subsequent felling of trees with the selection of species, which provides the largest volume of round timber output. Moreover, it is possible to adjust assortment tables (APT-matrices) for shortand medium-term planning of assortment harvesting volumes.

Authors

Kirill D. Zhuk¹, Postgraduate Student, ReseacherID: T-6299-2017, ORCID: https://orcid.org/0000-0003-0619-1242
Sergey A. Ugryumov¹*, Doctor of Engineering, Prof.; ReseacherID: F-6510-2016,ORCID: https://orcid.org/0000-0002-8077-3542
Fedor V. Svoikin², Candidate of Engineering; ReseacherID: AAC-4074-2020, ORCID: https://orcid.org/0000-0002-8507-9584
Vladimir F. Svoikin², Candidate of Engineering, Assoc. Prof.;ReseacherID: AAQ-8212-2020, ORCID: https://orcid.org/0000-0001-8989-4626

Affiliation

¹Saint-Petersburg State Forest Technical University named after S.M. Kirov, Institutskiy per., 5, liter U, Saint Petersburg, 194021, Russian Federation; zhuk_kd@mail.ru,ugr-s@yandex.ru*
²Syktyvkar Forestry Institute (Branch) of Saint-Petersburg State Forest Technical University named after S.M. Kirov, ul. Lenina, 39, Syktyvkar, 167982, Russian Federation; svoykinvf@mail.ru, svoykin_fv@mail.ru

Keywords

multi-operational forest machine, STM file, trunk file, StanForD2010, harvester, multi-operational forest machine productivity, Python, pandas, csv, Scandinavian cut-tolength technology (CTL-technology)

For citation

Zhuk K.D., Ugryumov S.A., Svoikin F.V., Svoikin V.F. Dimension and Quality Specifications of Round Logs Harvested with the Use of Multi-Operational Forest Machines. Lesnoy Zhurnal = Russian Forestry Journal, 2022, no. 5, pp. 
 https://doi.org/10.37482/0536-1036-2022-5-114-130

References

1. Mehrencev A.V., Azarenok V.A., Gerc E.F., Zalesov S.V. Assorted Wood Harvesting.Moscow, INFRA-M Publ., 2021. 140 p. (In Russ.). https://doi.org/10.12737/1141213
2. Gerts E.F. Assessment of Forest Management Technology in Logging Operations: Monograph. Yekaterinburg, UGLTU Publ., 2003. 120 p. (In Russ.).
3. Derbin V.M., Derbin M.V. Improving Cut-to-Length of Timber. Forestry Engineering Journal, 2015, vol. 5, no. 1(17), pp. 128–135. https://doi.org/10.12737/11270
4. Evdokimov B.P., Kormshchikova Z.I. Foreign Forest Machines. Syktyvkar, SLI Publ., 2009. 161 p. (In Russ.).
5. Kapustina Yu.A., Mekhrentsev A.V., Rostovskaya Yu.N., Starikov E.N. Improving Information Support as a Factor in Sustainable Development of the Forest Sector. Forests of Russia: Politics, Industry, Science and Education. Proceedings of the 3rd International Scientific and Technical Conference. Vol. 2. Ed. by V.M. Ged’o. Saint Petersburg, SPbFTU Publ., 2018, pp. 281–284. (In Russ.).
6. Manukovskiy A.Yu., Zorin M.V., Rudov S.E., Kunitskaya O.A., Grigorev I.V. Software Complexes of Modern Forest Machines. Priority Areas of Innovation in Industry: Collection of Academic Papers. Kazan, Konvert Publ., 2020, pp. 57–59. 
7. Nikonorova L.I., Timofeev M.G., Kuznetsova A.P. Python as a Modern Programming Language. Nauka i Obrazovaniye, 2019, vol. 2, no. 2, art. 263. (In Russ.).
8. Samorodnitskiy A.A., Svoikin V.F. To the Issue of Processing Tree Trunks with a Harvester. February Readings: Proceedings of the Scientific and Practical Conference on the Results of Research Work of Lecturers of the Syktyvkar Forest Institute in 2017. Syktyvkar, SLI Publ., 2018, pp. 167–172. (In Russ.).
9. Zhuk K.D., Ugryumov S.A., Svoikin F.V. The Program for Dynamic Calculation and Graphical Representation of the Output of Finished Products from a Separate Part of the stmLogic Shaft. Certificate of Registration of the Computer Program 2020666691 RF, No. 2020665981. 2020.
10. Svoikin V.F., Molchanova A.A. The Research Output of Assortments on the Cutting Area in the Republic of Komi. Current Directions of Scientific Research of the XXI Century: Theory and Practice, 2015, vol. 3, no. 9-2(20-2), pp. 258–262. (In Russ.). https://doi.org/10.12737/16481
11. Svoikin V.F., Yakovlev N.G., Molchanova A.A. Methodology for Assessing the Yield of Assortments at the Logging Site. February Readings: Proceedings of the Scientific and Practical Conference on the Results of Research Work of Lecturers of the Syktyvkar Forest Institute in 2012. Syktyvkar, SLI Publ., 2013, pp. 258–265. (In Russ.).
12. Sinitsyna I.V. Exploring Engineering Trends and Technology with Python // Тр. Междунар. науч.-метод. конф. «Информатизация инженерного образования» — ИНФОРИНО-2014. М.: МЭИ, 2014. С. 11–12.Sinitsyna I.V. Exploring Engineering Trends and Technology with Python. Proceedings of the International Scientific and Methodological Conference “Informatization of Engineering Education” – INFORINO-2014. Moscow, MEI Publ., 2014. pp. 11–12.
13. Adebayo A.B., Han H.-S., Johnson L. Productivity and Cost of Cut-to-Length and Whole-Tree Harvesting in a Mixed-Conifer Stand. Forest Products Journal, 2007, no. 57, iss. 6, pp. 59–69.
14. Alstott J., Bullmore E., Plenz D. Powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions. PLoS ONE, 2014, vol. 9, iss. 1, art. e85777. https://doi.org/10.1371/journal.pone.0085777
15. Arlinger J., Möller J. Information Exchange with CTL Machines, Recent Development of StanForD – A Communication Standard. Proceedings of the 3rd Forest Engineering Conference. Mont-Tremblant, Canada, 2007.
16. Fleischer M. Geschichte der Holzernte in Handarbeit. Proekte Verlag Cornelius GmbH, Halle/S, 2009. 212 p. (In Ger.).
17. Heinimann H.R. Productivity of a Cut-to-Length Harvester Family – An Analysis Based on Operation Data. Council on Forest Engineering (COFE) Conference Proceedings: “Appalachian Hardwoods: Managing Change”. Snowshoe, WV, 2001. Available at: https:// cofe.org/pdfs/COFE_2001.pdf (accessed 18.07.21).
18. Hesse K. Components and Systems for Tractor, Stacker and Combine. Elchingen, Bosch Rexroth Mobile Training, 2003, pp. 18–20.
19. Kemmerer J., Labelle E.R. Using Harvester Data from On-Board Computers: A Review of Key Findings, Opportunities and Challenges. European Journal of Forest Research, 2021, vol. 140, pp. 1–17. https://doi.org/10.1007/s10342-020-01313-4
20. Linhares M., Sette Júnior C.R., Campos F., Yamaji F.M. Harvester and Forwarder Machines Efficiency and Operational Performance in Forest Harvesting. Pesquisa Agropecuária Tropical, 2012, vol. 42, no. 2, pp. 212–219. (In Portuguese). https://doi.org/10.1590/S1983-40632012000200007
21. Marchi E., Chung W., Visser R., Abbas D., Nordfjell T., Mederski P.S., McEwan A., Brink M., Laschi A. Sustainable Forest Operations (SFO): A New Paradigm in a Changing World and Climate. Science of the Total Environment, 2018, vol. 634, pp. 1385–1397. https:// doi.org/10.1016/j.scitotenv.2018.04.084
22. Marshall H. On-Board Machine Stability Information System. Harvesting Technical Notes. Report No. HTN05-01. Rotorua, NZ, 2013. 5 p.
23. Möller J., Arlinger J., Hannrup B., Larsson W., Barth A. Harvester Data as a Base for Management of Forest Operations and Feedback to Forest Owners. Proceedings of the 4th Forest Engineering Conference “Innovation in Forest Engineering: Adapting to Structural Change”. White River, South Africa, 2011.
24. Olivera A., Visser R. Development of Forest-Yield Maps Generated from Global Navigation Satellite System (GNSS)-Enabled Harvester StanForD Files: Preliminary Concepts. New Zealand Journal of Forestry, 2016, vol. 46, art. 3. https://doi.org/10.1186/s40490-016-0059-x
25. Operation Manual, Spare Parts Catalog Ponsse Ergo. Issue 0230197-0390001. Finland, 2012. 2541 p.
26. Standard for Forest Data and Communications. Skogforsk, 2007. 10 p. Available at: www.skogforsk.se/contentassets/b063db555a664ff8b515ce121f4a42d1/ stanford_maindoc_070327.pdf (accessed 18.07.21).
27. User Manual. Drive and Control Systems for Combine Harvesters and Forage Harvesters. RE 98071. Bosch Rexroth AG, 2001. 16 p.
28. User Manual. Ergo Operation and Maintenance Manual. Ponsse Oyj, Finland, 2006. 958 p.
29. User Manual. Operator Book Ponsse Opti 4G.4.705. Ponsse Oyj, Finland, 2009. 382 p.