Article Review Procedure
Academic Areas and Subjects
Applied Aspects of Information Technology
Search by article
Vol. 4 № 1
Vol. 4 № 2
Vol. 3 № 1
Vol. 3 № 2
Vol. 3 № 3
Vol. 3 № 4
Vol. 2 № 1
Vol. 2 № 2
Vol. 2 № 3
Vol. 2 № 4
Vol. 1 № 1
5 Oct 2021
On October 5, 2021, a business meeting was held between representatives of the EPAM Systems IT Company Denis Grinev and Sergey Garashchuk with the Rector of the State University “Odessa Polytechnic” Gennadii Alexandrovich Oborskiy
17 Sept 2021
International Summer School
15 July 2021
Until November 1, 2021, enrollment in the double degree program of Slovakia 2ouble Degree is carried out.
ALGORITHM FOR ESTIMATION OF SHIP REFRIGERATION UNIT ENERGY EFFICIENCY USING FULL ORDER OBSERVERS
The article considers the construction of an algorithm for estimation the energy efficiency of a ship refrigeration unit using the minimum required number of sensors. It is established that the existing methods for diagnosing and monitoring the technical condition of ship refrigeration units are imperfect due to the presence of a large number of sensors and the necessity to suspend the unit. The choice of the refrigeration coefficient as an indicator of energy efficiency is justified. A method that allows determining the refrigeration coefficient in real time without the necessity to stop the operation of the ship's refrigeration unit and use pressure sensors is proposed. For this, the method supposes the calculation of the specific cooling capacity and compressor compression work, the mechanical power on the shaft and the mass flow rate of the refrigerant. The algorithm for determining the cooling capacity and compression work using only four temperature sensors is considered. This algorithm supposes the determination of enthalpies at characteristic points of the refrigeration cycle using the equations of the refrigerant state. A method for evaluating the mechanical power on the compressor shaft using full order adaptive state observers is proposed. A decision of using the electromagnetic torque of the compressor motor as a measured quantity is substantiated. A state observer is synthesized using a modal method based on a linearized model of the electric motor. An expression for calculating the geometric mean root and elements of the observer matrix is proposed. The resulting observer structure allows constructing it on the basis of a complete mathematical model of the electric motor and evaluating not only the speed, but also the load torque on the compressor shaft. In the environment of Matlab / Simulink, a simulation model of the compressor motor state observer is built. The obtained simulation results confirm the efficiency of the proposed method. An algorithm for determining the electromechanical parameters of a compressor for a given period of time using three voltage and current sensors is considered. A general algorithm for estimation energy efficiency, which can be the basis for creating a system for diagnosing and monitoring the technical condition of a ship refrigeration unit, is constructed.
Andrii Y. Bukaros
, Cand. of Tech. Sciences, Associate Professor
( email@example.com )
Oleg A. Onishchenko
, Dr. of Tech. Sciences, Professor
( firstname.lastname@example.org )
Valeriia M. Bukaros
( email@example.com )
Volodymyr V. Sergeiev
, Cand. of Tech. Sciences, Associate Professor
( firstname.lastname@example.org )
ship refrigeration unit; state observer; diagnostics, modeling, algorithm, energy efficiency
1. Koliev, I. D. (2009). “Sudovye kholodil'nye ustanovki”. [Marine refrigeration units]. Odessa, Ukraine, Publ. FENIKS, 264 p. (in Russian).
2. “Registr sudnoplavstva Ukrai'ny. Pravyla klasyfikacii' ta pobudovy suden”. [Shipping Register of Ukraine. Rules for classification and construction of ships]. Kyiv, Ukraine, (3), 632 p. (in Ukrainian).
3. Kumar, M. & Kar, I. (2013). “Fault detection and diagnosis of air-conditioning systems using residuals”. Preprints of the 10th IFAC International Symposium on Dynamics and Control of Process Systems.
4. Isermann, R. (1984). “Process fault detection based on modeling and estimation methods: A survey”. Automatica 20 (4), pp. 387- 404. DOI: 10.1016/0005-1098(84)90098-0.
5. Snihovskij, E. L. (2014). “K voprosu formirovanija algoritma diagnostirovanija tehnicheskogo sostojanija parokompressionnyh holodil'nyh mashin”. [On the formation of an algorithm for diagnosing the technical condition of vapor compression refrigeration machines]. Vestnik NTU “HPI”, No. 11, pp. 154-159 (in Russian).
6. “System and method for monitoring and diagnosing faults in environmentally controlled containers, such system and method being especially adapted for remote computer controlled monitoring numerous transportable containers over existing onsite power wiring”, patent 966785 USA: G01D9/005, No. US4234926A; Filled: 05.12.1978; Issued: 18.11.1980, 64 p.
7. “Tracking and monitoring device and system for a shipping container”, patent 13/515795 USA: G06Q10/08, No. US20120252488A1; Filled: 20.10.2010; Issued: 04.10.2012, 10 p.
8. Jun, Ji & Houde, Han. (2013). “The Monitoring System of Marine Refrigerated Containers Based on RFID Temperature Tags”. Research Journal of Applied Sciences, Engineering and Technology, (08), pp. 2551-2555. DOI: 10.19026/rjaset.5.4695.
9. Zhao, H. & Liang, Y. (2014). “Maritime Information Integration Based on RFID Middleware”. Seventh International Symposium on Computational Intelligence and Design. Hangzhou, 2014, pp. 459-462. DOI: 10.1109/ISCID.2014.120 (in English).
10. Kužnar, D.; Piltaver, R., Gradišek, A., Gams, M. & Luštrek, M. (2017), “An intelligent system to monitor refrigeration devices”. Expert Systems, 34:e12199. DOI:10.1111/exsy.12199.
11. Ji, J. & Han, H. (2013). “A Fault Detection Model of Marine Refrigerated Containers”. Research Journal of Applied Sciences, Engineering and Technology, 16, pp. 4066-4070. DOI:10.19026/rjaset.5.4626.
12. “Apparatus, method, and system for communicating with a shipping container”: patent TW105117258A, G05D23/19, No. TWI590201B; Filled: 09.03.2011; Issued: 01.07.2017, 39 p.
13. Jaszczak, S. & Łokietek, T. (2016). “The energy efficiency monitoring a refrigeration unit”. Measurement Automation Monitoring, (62 (6)), pp. 202-205.
14. Nikol'skij, V. V., Ocheretjanyj, Ju. A. & Tanasijchuk, M. I. (2014). “Monitoring sudovoj holodil'noj tehniki s ispol'zovaniem programmiruemyh logicheskih kontrollerov (PLK)”. [Monitoring marine refrigeration equipment using programmable logic controllers (PLCs)]. Sudovye jenergeticheskie ustanovki, (14), pp. 41-52 (in Russian).
15. Han, H., Kan, A. & Ji, J. (2009). “Investigation of Monitor-and-Control Software of Marine Refrigerated Container”. International Forum on Computer Science-Technology and Applications. Chongqing, pp. 350-353. DOI:10.1109/IFCSTA.2009.355.
16. Zhyvytsya, Y., Vaynfeld, E., Glazeva, O. & Onishchenko, O. (2009). “Indirect determination of refrigerant mass flow to estimate the current value of energy efficiency in small scale systems”. Compressors: 7th International IIR Conference on Compressors and Coolants. Papiernicka, 30 September – 02 October 2009: proceeding, NY, Curran Associates, Inc, pp. 415-420.
17. Costa, G. S. R. & Namal, D. D. A. (2019). “Analysis of Energy Efficiency of Domestic Refrigerators”. Engineer: Journal of the Institution of Engineers, Sri Lanka, 52(3), pp. 43-50. DOI:10.4038/engineer.v52i3.7364.
18. Ocheretjanyj, Ju. A. (2013). “Opredelenie termodinamicheskih pokazatelej sudovoj holodil'noj ustanovki v processe jekspluatacii”. [Determination of thermodynamic parameters of ship refrigeration unit during operation]. Problemy tehniky, (2), pp. 119-125 (in Russian).
19. Grimmelius, H. T. (2005). “Condition monitoring for marine refrigeration plants based on process models”, DUP, 297 p.
20. Vyngra, A. V. (2017). “Ispol'zovanie programmno-apparatnogo modelirovanija pri proektirovanii sistemy upravlenija sudovoj holodil'noj ustanovkoj”. [Using hardware and software modeling in the design of a ship refrigeration unit control system]. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova, 9 (4), pp. 806-813 (in Russian).
21. Estupinan, E. A. & Santos, I. (2007). “Dynamic Modeling Hermetic Reciprocating Compressors, Combining Multibody Dynamics, Finite Elements Method and Fluid Film Lubrication”. International journal of mechanics, (1 (4)), pp. 36-43.
22. Vasylets, D., Kozminyih, N. & Onishchenko, O. “Analiz metodov modelirovanija sistem kondicionirovanija sudovyh pomeshhenij”. [Analysis methods of air conditioning simulation of ship premises]. Bulletin of NTU “KhPI”. Series: New solutions in modern technologies, (7 (1229)), pp. 24-29. DOI: 10.20998/2413-4295.2017.07.04 (in Russian).
23. Plastinin, P. I., (2013) “Porshnevyye kompressory. Teoriya i raschet”. [Piston compressors. In 2 Vol. Vol. 1. Theory and calculation]. Moscow, Russian Federation, Kolos S Publ., 2(1), 456 p. ISBN 5-9532-0428-0 (in Russian).
24. Krause, P. C., Wasynczuk, O. & Sudhoff, S. D. (2002). “Analysis of Electric Machinery and Drive Systems”. New York, Wiley-IEEE, 680 p. DOI: 10.1002/9781118524336.
25. Bukaros, A. Ju., Bukaros, V. N. & Onishchenko, O. A. (2015). “Modelirovanie momenta soprotivlenija odnoporshnevogo kompressora sudovoj holodil''noj ustanovki”. [Simulation of the resistance moment of singlepiston compressor of ship refrigeration unit]. Technology audit and production reserves, (4/1(24)), pp. 46-51. DOI: 10.15587/2312- 8372.2015.47765 (in Russian).
26. Kubota, H., Matsuse, K. & Nakano, T. (1993). “DSP-based speed adaptive flux observer of induction motor”. IEEE Transactions on Industry Applications, 29(2), pp. 344-348. DOI:10.1109/ 28.216542. 27. Bukaros, A., Onyshchenko, O., Montik, P., Malyshev, V. & Bukaros, V. (2019). “Modernization of Luenberger observer for control system of hermetic compressor electric drives”. Radio Electronics, Computer Science, Control, (1), pp. 230-237. DOI: 10.15588/1607-3274-2019-1-21.
28. Pankratov, V. V. & Maslov, M. O. (2007), “Zadachi sinteza algoritmov identifikacii dlja bezdatchikovyh asinhronnyh jelektroprivodov s vektornym upravleniem i variant ih reshenija”. [Problems of synthesis of identification algorithms for sensorless asynchronous electric drives with vector control and a variant of their solution]. Silovaja intellektual'naja jelektronika, 1(6), pp. 23- 43 (in Russian).
29. Sokolovskiy, G. G. (2006), “Elektroprivody peremennogo toka s chastotnym upravleniem”. [Alternating-current electric drives with variablefrequency control]. Moscow, Russian Federation, Akademiya Publ, 272 p. (in Russian).
30. Sazonov, A. E., Saharov, V. V. & Chertkov, A. A. (2016), “Modal'nyj metod sinteza nabljudatelja dlja sistemy upravlenija kursom sudna”. [Modal observer synthesis method for ship heading control system]. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova, 4(38), pp. 211-223. DOI: 10.21821/2309-5180-2016-8-4-211-223(in Russian).
31. Pankratov, V. V., Nos, O. V. & Zima, E. A. (2011), “Izbrannye razdely teorii avtomaticheskogo upravlenija”. [Selected sections of the automatic control theory]. Novosibirsk, Russian Federation, Publ. NGTU, 223 p. (in Russian)/
Received after revision 25.01.2020
Vol. 3 № 1, 2020
17 Oct 2021
Search by author
Information Systems and Technologies
1. Models and Methods of Information Technology
2. Design of Information Systems and Technologies
3. Mathematical Issues of Information Technologies
4. Innovative Technologies in Education, Culture and art
5. Game Technologies, Augmented and Virtual Reality
6. Theoretical and Applied Issues of Computer Science
7. Project, Program and Portfolio Management
Digital control of Technical and Social Systems
1. Adaptive and optimal Control Systems
2. Parametric and System Identification
3. Interconnected Systems and Systems with Distributed Parameter
4. Renewable Energy Systems
5. Machine Learning and Artificial Intelligence in General Technical Problems and Electromechanics
6. Management of Production and Power Plants
7. Control Systems for Robotic Systems and Complexes, Electric Vehicles
8. Diagnosis and Evaluation of Complex Systems
9. Simulation of Physical Objects and Processes
Sensor less Control Systems
Software Engineering and Systems Analysis
1. Methods and Means of Intellectual Information Processing
2. Recognition, Decision Making, Forecasting
3. Neural Network Technologies and Machine Learning Methods
4. Semantic Models. Natural Language Processing
5. Theoretical and Applied Issues of Software Engineering
6. Models and Methods of Software Quality Management
Computer Systems and Cybersecurity
1. Parallel and Distributed Information Processing
2. Internet of Things
3. Information Security and Cybersecurity
4. Computer Networks and Systems
5. Components of Robotic Systems
KarelWintersky ] [
[ © Odessa National Polytechnic University, 2018.]