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Probability Analysis of Relations between Operation Mode Parameters of Saw Frames

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S.P. Ageev, A.N. Minaev, S.I. Roshchina

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UDС

621.311

DOI:

10.17238/issn0536-1036.2019.3.121

Abstract

Nature of woodworking processes is dramatically influenced by various random factors. Mathematically, these processes should be considered as one of accidental types. The most energy-intensive process is sawmilling. Here, saw frame and frame equipment comprise a separate section, which largely forms the electricity consumption nature of product line and the whole plant. Therefore, the issues of improving the energy efficiency of woodworking industry can be solved only by joint consideration of the technological and energy parameters of wood sawing. The research purpose is a probability-theoretical analysis of relationship between the saw frames operating parameters, as well as finding the distribution laws and numerical ratings of these parameters as random variables when sawing the sort log load. The queuing system is used as a mathematical model of the saw frame cutting mechanism. The application of the probability theory has allowed us to find the distribution density and numerical characteristics of the effective time; hourly average sawing raw material output; hourly average power consumption, energy losses in the network; absolute and specific power consumption in conjunction with the geometric parameters of raw materials and operation parameters of saw frame mode. Electricity consumption parameters have probabilistic nature and are distributed by law, different from normal. The density of parameters distribution was approximated by the density of the Gauss’ law in order to simplify the analysis procedure. Herewith, the error of approximation was not more than 1.71 %. Formulas for calculating the values of technological and energy parameters of saw frames opera-tion are proposed.

Authors

S.P. Ageev1, Doctor of Engineering, Assoc. Prof.; Publons: 1758124/sergey-ageev, ORCID: 0000-0003-0362-6722
A.N. Minaev2, Doctor of Engineering, Assoc. Prof.
S.I. Roshchina3, Doctor of Engineering, Assoc. Prof.

Affiliation

1Saint Petersburg State University of Architecture and Civil Engineering ul. 2-ya Krasnoarmeyskaya, 4, Saint Petersburg, 190005, Russian Federation;
е-mail: doсtor.mart11@mail.ru
2St. Petersburg State Forest Technical University named after S.M. Kirov, prosp. Institutskiy, 5, Saint Petersburg, 194021, Russian Federation; e-mail: stl@spbftu.ru
3Vladimir State University named after Alexander and Nikolai Stoletovs, ul. Gor’kogo, 87, Vladimir, 600000, Russian Federation; e-mail: rsi3@mail.ru

Keywords

saw frame, sort load of logs, energy input, power consumption, energy losses, probability distribution, sawn raw material parameters

For citation

Ageev S.P., Minaev A.N., Roshchina S.I. Probability Analysis of Relations be-tween Operation Mode Parameters of Saw Frames. Lesnoy Zhurnal [Forestry Journal], 2019, no. 3, pp. 121–131. DOI: 10.17238/issn0536-1036.2019.3.121

References

1. Ageev S.P. Mathematical Modeling of Sawing Wood Processes. Izvestia Sankt-Peterburgskoj Lesotehniceskoj Akademii [News of the Saint Petersburg State Forest Tech-nical Academy], 2007, iss. 179, pp. 142–152.
2. Ageev S.P. Energetic Characteristic of Cutting Mechanism of Frame Saw. Lesnoy Zhurnal [Forestry Journal], 2009, no 1, pp. 95–100.
3. Ageev S.P. Energy Characteristic of Electric Drive for Cutting Mechanism of Saw Frame. Lesnoy Zhurnal [Forestry Journal], 2009, no 2, pp. 96–101.
4. Ageev S.P. Stochastic Pattern of the Sash Operating Cycles. Lesnoy Zhurnal [For-estry Journal], 2014, no. 4, pp. 80–89.
5. Aleksin M.V., Sinev V.S., Pizhurin P.A., Koperin I.F., Golovkov S.I., Pavlosyuk V.A. Energy Savings in Forest and Woodworking Industry. Moscow, Lesnaya promyshlen-nost’ Publ., 1982. 216 p.
6. Arkashov N.S., Kovalevskiy A.P. Theory of Probability and Stochastic Processes: Educational Textbook. Novosibirsk, NSTU Publ., 2014. 180 p.
7. Venttsel’ E.S., Ovcharov L.A. Theory of Probability and Its Engineering Applica-tions: Educational Textbook for Universities. Moscow, Vysshaya shkola Publ., 2000. 280 p.
8. Voskoboynikov D.M. Economic Incentives for Sustainable Use of Power in Industry. Moscow, Energoatomizdat Publ., 1988. 80 p.
9. Gusak A.L. Higher Mathematics. Moscow, Tetra Sistema Publ., 2009. 320 p.
10. Kolemaev V.A., Kalinina V.A. Theory of Probability and Mathematical Statistics. Moscow, Unity-Dana Publ., 2007. 250 p.
11. Konyukhova E.A. Electrical Power Supply of Facilities: Educational Textbook. Moscow, Masterstvo Publ., 2001. 320 p.
12. Mikhaylov V.V. Power Consumption Charges and Modes. Moscow, Energoatomizdat Publ., 1986. 216 p.
13. Mikhaylov V.V., Gudkov L.V., Tereshchenko A.V. Sustainable Use of Fuel and Energy in Industry. Moscow, Energoatomizdat Publ., 1985. 210 p.
14. Rykunin S.N., Pyatkov V.E. Methods for Compilation and Calculation of Sawing Schedules: Educational Textbook. Moscow, MGUL Publ., 2002. 69 p.
15. Sibikin Yu.D., Sibikin M.Yu., Yashkov V.A. Power Supply of Industrial Enter-prises and Installations. Moscow, Vysshaya shkola Publ., 2001. 336 p.
16. Ancharova T.V., Gamazin S.I., Shevchenko V.V. Energy Saving at Industrial Enterprises. Book 5. Power Saving Technology of Electricity Supply of National Economy: In 5 Books: Practical Guide. Ed. by V.A. Venikov. Мoscow, Vysshaya shkola Publ., 1990. 143 p.
17. Kreisel K., Jochem E. Druckluft rationell erzeugen und nutzen. Fachartikel im Rahmen der Initiative “Energie effizient nutzen ‒ Schwerpunkt Storm”. Baden-Wurttemberg, Germany, 1996.
18. Matthews M.B., Leber J.F. Neurale Netzwerke: Ein Ubersicht. Bulletin of the Swiss Electronic Society (SEV), 1989, vol. 15, pp. 923‒932.
19. Rumelhart D.E., Hinton G.E., Williams R.J. Learning Representations by Back-Propagating Errors. Nature, 1986, vol. 323, pp. 533–536.
20. Tonsing E. Stromsparende Beleuchtungssysteme – mehr Licht fur weniger Kosten. Fachartikel im Rahmen der Initiative “Energie effizient nutzen ‒ Schwerpunkt Storm”. Baden-Wurttemberg, Germany, 1996.

Received on February 14, 2019


Probability Analysis of Relations between Operation Mode Parameters of Saw Frames

 

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