EVALUATION OF THE STATE OF DYNAMIC WEIGHING BY THE KALMAN FILTER METHOD
Abstract
Currently, due to widespread computerization, the development of automated control systems is relevant. Due to the development of small businesses, the purchase of commercially available systems is a very expensive solution. It is possible to create similar control systems based on inexpensive microprocessor kits (in this particular case, the K1816VE35 microprocessor kit is used). In the future, such a system will not be difficult to improve, and it is also easy to implementinterfacing with various electronic computers (control from a personal computer). A system for measuring and regulating bulk raw materials (an automated weighing system) is to be developed, which provides control of the pneumatic transport automation with a 2-speed rotary dispenser, through which bulk raw materials are fed to a weighing hopper suspended on a load-bearing device. Measuring the weight of the bulk mass in the hopper of the scales, followed by automatic control of unloading of bulk raw materials from the hopper. The profitability of any industrial operation involving the weighing of raw materials, work in progress and finished products directly depends on the accuracy of the weight data. However, even when using high-precision weighing equipment, the method of collecting, recording and processing weight data for the micro ingredients system may be subject to errors and inaccuracies. This can cause a potential revenue drain that is difficult to detect and verify. In many cases, it is assumed that the cause of the problem is related to the weighing equipment, whereas in fact it is related to the traditional data collection and management system. In many factories where bulk products are mixed in batches, dosing scales is a manual, time-consuming operation in which the ingredients are weighed separately before loading into a blender or other technological container. A significant number of such plants can benefit from the installation of an automated weighing and dosing system.
References
1. Zaytsev S.A., Gribanov D.D., Tolstov A.N., Merkulov R.V. Kontrol'no-izmeritel'nye pribory i
instrumenty [Control and measuring instruments and instruments]. Moscow: Akademiya,
2003, pp. 18-19.
2. Manych A.S.. Zargaryan E.V. Kontrol'no-izmeritel'nye sredstva dlya vzveshivaniya sypuchikh
gruzov [Control and measuring means for weighing bulk cargoes], Fundamental'nye i
prikladnye aspekty komp'yuternykh tekhnologiy i informatsionnoy bezopasnosti: materialy VII
Vserossiyskoy nauchno-tekhnicheskoy konferentsii [Fundamental and applied aspects of
computer technologies and information security: materials of the VII All-Russian
Scientific and Technical Conference]. Taganrog, 2021, 493 p.
3. Zargaryan Yu.A. Zadacha upravlyaemosti v adaptivnoy avtomatnoy obuchaemoy sisteme
upravleniya [The problem of controllability in an adaptive automatic trainable control system.
In the collection], Tekhnologii razrabotki informatsionnykh sistem TRIS-2020: Mater. X
Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii. "Tekhnologii razrabotki informatsionnykh
sistem", 2020 [Technologies for the development of information systems TRIS-
2020. Materials of the X International Scientific and Technical Conference. "Information Systems
Development Technologies", 2020].
4. Zargaryan E.V., Zargaryan Y.A., Dmitrieva I.A., Sakharova O.N. and Pushnina I.V. Modeling design
information systems with many criteria. Information Technologies and Engineering –
APITECH – 2020, Journal of Physics: Conference Series, 2020, Vol. 2085 (3), pp. 032057(1-7).
DOI: 10.1088/1742-6596/1679/3/032057.
5. Manych A.S., Zargaryan E.V. Kontrol'no-izmeritel'nye sredstva dlya vzveshivaniya sypuchikh
gruzov [Control and measuring means for weighing bulk cargoes], Issledovanie i
proektirovanie intellektual'nykh sistem v avtomobile-stroenii, aviastroenii i mashinostroenii:
Mater. vserossiyskoy nauchno-prakticheskoy konferentsii s mezhdunarodnym uchastiem [Research
and design of intelligent systems in the automotive, aircraft and mechanical engineering:
Materials of the All-Russian scientific and practical conference with international participation]
ed. col.: Svetlichnaya L.A., Chernova T.V.; Taganrog: El'Direkt – IP Shkurkin D.V.
(DirektSayns), 2021, 358 p.
6. Zargaryan E.V., Zargaryan Y.A., Kapc I.V., Sakharova O.N., Kalyakina I.M and Dmitrieva
I.A. Method of estimating the Pareto-optimal solutions based on the usefulness, International
Conference on Advances in Material Science and Technology - CAMSTech-2020. IOP Conf.
Series: Materials Science and Engineering, 2020, Vol. 919 (2), pp. 022027 (1-8). DOI:
10.1088/1757-899X/919/2/022027.
7. Nagatani T. The physics of traffic jams, Rep. Prog. Phys., Sept. 2002, Vol. 65, No. 9,
pp. 1331-1386.
8. Jiber M., Lamouik I., Ali Y., et Sabri M.A. Traffic flow prediction using neural network, 2018 International
Conference on Intelligent Systems and Computer Vision (ISCV), Fez, 2018, pp. 1-4.
9. Zhang Y.et Liu Y. Comparison of Parametric and Nonparametric Techniques for Non-peak
Traffic Forecasting , 2009, Vol. 3, No. 3, pp. 7.
10. Senyanskiy D.M. Programmnaya realizatsiya algoritmov vzveshivaniya vagonov v dvizhenii
[Software implementation of algorithms for weighing wagons in motion], Vserossiyskaya
molodezhnaya nauchnaya konferentsiya VII Korolevskie chteniya: Tezisy doklada [All-
Russian Youth Scientific Conference VII Royal Readings: Abstracts of the report]. Samara:
SGAU, 2003.
11. Zargarjan E.V., Zargarjan Ju.A., Finaev V.I. Information support for the training of fuzzy
production account balance in the conditions of incomplete data, Innovative technologies and
didactics in teaching (ITDT-2016): Collected papers, 2016, pp. 128-138.
12. Ivanov V.A., Maslenko V.O., Kharchenko K.A. Eksperimental'noe ustroystvo dlya
gidravlicheskogo vzveshivaniya gruza [Experimental device for hydraulic weighing of cargo],
Uchenye zametki TOGU [Scientific Notes of TOGU], 2017, Vol. 8, No. 1, pp. 128-137.
– Available at: http://pnu.edu.ru/ejournal/pub/articles/1505.
13. Finaev V.I., Zargaryan Yu.A., Zargaryan E.V., Solov'ev V.V. Formalizatsiya grupp
podvizhnykh ob"ektov v usloviyakh neopredelennosti dlya vybora upravlyayushchikh resheniy
[Formalization of groups of moving objects under uncertainty for the choice of control solutions],
Informatizatsiya i svyaz' [Informatization and Communication], 2016, No. 3, pp. 56-62.
14. Slimani I., Farissi I. El, et Achchab S. Artificial Neural Networks for Demand Forecasting:
Application Using Moroccan Supermarket Data, 2015.
15. Slimani I., Farissi I. El, et Achchab S. Configuration and implementation of a daily artificial
neural network-based forecasting system using real supermarket data, Int. J. Logist. Syst.
Manag., 2017, Vol. 28, No. 2, pp. 144-163.
16. Pushnina I.V. Sistema upravleniya podvizhnym ob"ektom v usloviyakh neopredelennosti [The
control system of a moving object in conditions of uncertainty], Nauka i obrazovanie na
rubezhe tysyacheletiy: Sb. nauchno-issledovatel'skikh rabot. Kislovodskiy gumanitarnotekhnicheskiy
institut, Yuzhnyy federal'nyy universitet [Science and Education at the turn of the
Millennium. collection of research papers. Kislovodsk Humanitarian and Technical Institute,
Southern Federal University]. Kislovodsk, 2018, pp. 65-74.
17. Wang X., Wang C. Time series data cleaning: A survey, IEEE Access, 2020, Vol. 8, pp. 1866-1881.
DOI: 10.1109/ACCESS.2019.2962152.
18. Mikhaylov P.G. Mikroelektronnyy datchik davleniya i temperatury [Microelectronic pressure
and temperature sensor], Pribory i sistemy. Upravlenie, kontrol', diagnostika [Devices and systems.
Management, control, diagnostics], 2003, No. 11, pp. 29-31.
19. Alamir Kh.S., Zargaryan E.V., Zargaryan Yu.A. Model' prognozirovaniya transportnogo potoka na
osnove neyronnykh setey dlya predskazaniya trafika na dorogakh [A traffic flow prediction model
based on neural networks for predicting traffic on the roads], Izvestiya YuFU. Tekhnicheskie nauki
[Izvestiya SFedU. Engineering Sciences], 2021, No. 6 (223), pp. 124-132.
20. Ol'khovskaya E.S., Palashkin A.A., Kulesh V.V., Nomerchuk A.Ya., Solov'ev V.V. Razrabotka
modul'noy sistemy vyrashchivaniya rasteniy GROWBOX [Development of a modular system
for growing plants GROWBOX], Problemy avtomatizatsii. Regional'noe upravlenie. Svyaz' i
akustika: Sb. trudov X Vserossiyskoy nauchnoy konferentsii i molodezhnogo nauchnogo
foruma v ramkakh meropriyatiy, posvyashchennykh godu Nauki i tekhnologiy v Rossiyskoy
Federatsii [Problems of automation. Regional management. Communication and acoustics:
Proceedings of the X All-Russian Scientific Conference and Youth Scientific Forum within the
framework of events dedicated to the Year of Science and Technology in the Russian Federation].
Rostov-on-Don, 2021, pp. 168-173.
21. Nomerchuk A.Ya., Kryukov V.V., Kukanov R.S. Analitichesko-eksperimental'nye issledovaniya
funktsionirovaniya elektrotekhnicheskogo kompleksa na primere pishchevykh proizvodstv
[Analytical and experimental studies of the functioning of the electrical complex on the example
of food production], Issledovaniya i tvorcheskie proekty dlya razvitiya i osvoeniya
problemnykh i pribrezhno-shel'fovykh zon yuga Rossii: Sb. trudov XI Vserossiyskoy Shkolyseminara,
posvyashchennoy 25-letiyu filiala YuFU v g. Gelendzhike. Sostaviteli: Yu.B.
Shchemeleva, S.V. Kiril'chik; Yuzhnyy federal'nyy universitet [Research and creative projects
for the development and development of problematic and coastal shelf zones of the South of
Russia: Proceedings of the XI All-Russian School-seminar dedicated to the 25th anniversary of
the branch of the SFU in Gelendzhik. Compiled by Yu.B. Shchemeleva, S.V. Kirilchik; Southern
Federal University], 2020, pp. 214-218.
22. Ivanova N.A., Begun O.V., Dmitrieva I.A., Mileshko L.P., Sklifus R.V. Impact Of Road
Transport On The Environmental Situation In The Urban Environment, European Proceedings
of Social and Behavioural Sciences EpSBS. Krasnoyarsk, Russia, 2021], pp. 2600-2606.
23. Babenko L.K., Shumilin A.S., Alekseev D.M. Algoritm obespecheniya bezopasnosti
konfidentsial'nykh dannykh meditsinskoy informatsionnoy sistemy khraneniya i obrabotki
rezul'tatov obsledovaniy [Algorithm for ensuring the security of confidential data of the medical
information system for storing and processing survey results], Izvestiya YuFU.
Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2020, No. 5 (215), pp. 6-16.
instrumenty [Control and measuring instruments and instruments]. Moscow: Akademiya,
2003, pp. 18-19.
2. Manych A.S.. Zargaryan E.V. Kontrol'no-izmeritel'nye sredstva dlya vzveshivaniya sypuchikh
gruzov [Control and measuring means for weighing bulk cargoes], Fundamental'nye i
prikladnye aspekty komp'yuternykh tekhnologiy i informatsionnoy bezopasnosti: materialy VII
Vserossiyskoy nauchno-tekhnicheskoy konferentsii [Fundamental and applied aspects of
computer technologies and information security: materials of the VII All-Russian
Scientific and Technical Conference]. Taganrog, 2021, 493 p.
3. Zargaryan Yu.A. Zadacha upravlyaemosti v adaptivnoy avtomatnoy obuchaemoy sisteme
upravleniya [The problem of controllability in an adaptive automatic trainable control system.
In the collection], Tekhnologii razrabotki informatsionnykh sistem TRIS-2020: Mater. X
Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii. "Tekhnologii razrabotki informatsionnykh
sistem", 2020 [Technologies for the development of information systems TRIS-
2020. Materials of the X International Scientific and Technical Conference. "Information Systems
Development Technologies", 2020].
4. Zargaryan E.V., Zargaryan Y.A., Dmitrieva I.A., Sakharova O.N. and Pushnina I.V. Modeling design
information systems with many criteria. Information Technologies and Engineering –
APITECH – 2020, Journal of Physics: Conference Series, 2020, Vol. 2085 (3), pp. 032057(1-7).
DOI: 10.1088/1742-6596/1679/3/032057.
5. Manych A.S., Zargaryan E.V. Kontrol'no-izmeritel'nye sredstva dlya vzveshivaniya sypuchikh
gruzov [Control and measuring means for weighing bulk cargoes], Issledovanie i
proektirovanie intellektual'nykh sistem v avtomobile-stroenii, aviastroenii i mashinostroenii:
Mater. vserossiyskoy nauchno-prakticheskoy konferentsii s mezhdunarodnym uchastiem [Research
and design of intelligent systems in the automotive, aircraft and mechanical engineering:
Materials of the All-Russian scientific and practical conference with international participation]
ed. col.: Svetlichnaya L.A., Chernova T.V.; Taganrog: El'Direkt – IP Shkurkin D.V.
(DirektSayns), 2021, 358 p.
6. Zargaryan E.V., Zargaryan Y.A., Kapc I.V., Sakharova O.N., Kalyakina I.M and Dmitrieva
I.A. Method of estimating the Pareto-optimal solutions based on the usefulness, International
Conference on Advances in Material Science and Technology - CAMSTech-2020. IOP Conf.
Series: Materials Science and Engineering, 2020, Vol. 919 (2), pp. 022027 (1-8). DOI:
10.1088/1757-899X/919/2/022027.
7. Nagatani T. The physics of traffic jams, Rep. Prog. Phys., Sept. 2002, Vol. 65, No. 9,
pp. 1331-1386.
8. Jiber M., Lamouik I., Ali Y., et Sabri M.A. Traffic flow prediction using neural network, 2018 International
Conference on Intelligent Systems and Computer Vision (ISCV), Fez, 2018, pp. 1-4.
9. Zhang Y.et Liu Y. Comparison of Parametric and Nonparametric Techniques for Non-peak
Traffic Forecasting , 2009, Vol. 3, No. 3, pp. 7.
10. Senyanskiy D.M. Programmnaya realizatsiya algoritmov vzveshivaniya vagonov v dvizhenii
[Software implementation of algorithms for weighing wagons in motion], Vserossiyskaya
molodezhnaya nauchnaya konferentsiya VII Korolevskie chteniya: Tezisy doklada [All-
Russian Youth Scientific Conference VII Royal Readings: Abstracts of the report]. Samara:
SGAU, 2003.
11. Zargarjan E.V., Zargarjan Ju.A., Finaev V.I. Information support for the training of fuzzy
production account balance in the conditions of incomplete data, Innovative technologies and
didactics in teaching (ITDT-2016): Collected papers, 2016, pp. 128-138.
12. Ivanov V.A., Maslenko V.O., Kharchenko K.A. Eksperimental'noe ustroystvo dlya
gidravlicheskogo vzveshivaniya gruza [Experimental device for hydraulic weighing of cargo],
Uchenye zametki TOGU [Scientific Notes of TOGU], 2017, Vol. 8, No. 1, pp. 128-137.
– Available at: http://pnu.edu.ru/ejournal/pub/articles/1505.
13. Finaev V.I., Zargaryan Yu.A., Zargaryan E.V., Solov'ev V.V. Formalizatsiya grupp
podvizhnykh ob"ektov v usloviyakh neopredelennosti dlya vybora upravlyayushchikh resheniy
[Formalization of groups of moving objects under uncertainty for the choice of control solutions],
Informatizatsiya i svyaz' [Informatization and Communication], 2016, No. 3, pp. 56-62.
14. Slimani I., Farissi I. El, et Achchab S. Artificial Neural Networks for Demand Forecasting:
Application Using Moroccan Supermarket Data, 2015.
15. Slimani I., Farissi I. El, et Achchab S. Configuration and implementation of a daily artificial
neural network-based forecasting system using real supermarket data, Int. J. Logist. Syst.
Manag., 2017, Vol. 28, No. 2, pp. 144-163.
16. Pushnina I.V. Sistema upravleniya podvizhnym ob"ektom v usloviyakh neopredelennosti [The
control system of a moving object in conditions of uncertainty], Nauka i obrazovanie na
rubezhe tysyacheletiy: Sb. nauchno-issledovatel'skikh rabot. Kislovodskiy gumanitarnotekhnicheskiy
institut, Yuzhnyy federal'nyy universitet [Science and Education at the turn of the
Millennium. collection of research papers. Kislovodsk Humanitarian and Technical Institute,
Southern Federal University]. Kislovodsk, 2018, pp. 65-74.
17. Wang X., Wang C. Time series data cleaning: A survey, IEEE Access, 2020, Vol. 8, pp. 1866-1881.
DOI: 10.1109/ACCESS.2019.2962152.
18. Mikhaylov P.G. Mikroelektronnyy datchik davleniya i temperatury [Microelectronic pressure
and temperature sensor], Pribory i sistemy. Upravlenie, kontrol', diagnostika [Devices and systems.
Management, control, diagnostics], 2003, No. 11, pp. 29-31.
19. Alamir Kh.S., Zargaryan E.V., Zargaryan Yu.A. Model' prognozirovaniya transportnogo potoka na
osnove neyronnykh setey dlya predskazaniya trafika na dorogakh [A traffic flow prediction model
based on neural networks for predicting traffic on the roads], Izvestiya YuFU. Tekhnicheskie nauki
[Izvestiya SFedU. Engineering Sciences], 2021, No. 6 (223), pp. 124-132.
20. Ol'khovskaya E.S., Palashkin A.A., Kulesh V.V., Nomerchuk A.Ya., Solov'ev V.V. Razrabotka
modul'noy sistemy vyrashchivaniya rasteniy GROWBOX [Development of a modular system
for growing plants GROWBOX], Problemy avtomatizatsii. Regional'noe upravlenie. Svyaz' i
akustika: Sb. trudov X Vserossiyskoy nauchnoy konferentsii i molodezhnogo nauchnogo
foruma v ramkakh meropriyatiy, posvyashchennykh godu Nauki i tekhnologiy v Rossiyskoy
Federatsii [Problems of automation. Regional management. Communication and acoustics:
Proceedings of the X All-Russian Scientific Conference and Youth Scientific Forum within the
framework of events dedicated to the Year of Science and Technology in the Russian Federation].
Rostov-on-Don, 2021, pp. 168-173.
21. Nomerchuk A.Ya., Kryukov V.V., Kukanov R.S. Analitichesko-eksperimental'nye issledovaniya
funktsionirovaniya elektrotekhnicheskogo kompleksa na primere pishchevykh proizvodstv
[Analytical and experimental studies of the functioning of the electrical complex on the example
of food production], Issledovaniya i tvorcheskie proekty dlya razvitiya i osvoeniya
problemnykh i pribrezhno-shel'fovykh zon yuga Rossii: Sb. trudov XI Vserossiyskoy Shkolyseminara,
posvyashchennoy 25-letiyu filiala YuFU v g. Gelendzhike. Sostaviteli: Yu.B.
Shchemeleva, S.V. Kiril'chik; Yuzhnyy federal'nyy universitet [Research and creative projects
for the development and development of problematic and coastal shelf zones of the South of
Russia: Proceedings of the XI All-Russian School-seminar dedicated to the 25th anniversary of
the branch of the SFU in Gelendzhik. Compiled by Yu.B. Shchemeleva, S.V. Kirilchik; Southern
Federal University], 2020, pp. 214-218.
22. Ivanova N.A., Begun O.V., Dmitrieva I.A., Mileshko L.P., Sklifus R.V. Impact Of Road
Transport On The Environmental Situation In The Urban Environment, European Proceedings
of Social and Behavioural Sciences EpSBS. Krasnoyarsk, Russia, 2021], pp. 2600-2606.
23. Babenko L.K., Shumilin A.S., Alekseev D.M. Algoritm obespecheniya bezopasnosti
konfidentsial'nykh dannykh meditsinskoy informatsionnoy sistemy khraneniya i obrabotki
rezul'tatov obsledovaniy [Algorithm for ensuring the security of confidential data of the medical
information system for storing and processing survey results], Izvestiya YuFU.
Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2020, No. 5 (215), pp. 6-16.
Скачивания
Published:
2022-05-26
Issue:
Section:
SECTION III. INFORMATION PROCESSING ALGORITHMS
