New technological diagnostics algorithm of required electric motors
DOI:
https://doi.org/10.14529/power170211Keywords:
diagnostics, algorithm, rowing electric motor, mathematical model, functional modelAbstract
The paper illustrates one of the directions determining the improvement of the quality of the ship electrical equipment technical condition control and diagnostics. We consider a new algorithm to diagnose the technical condition of propulsion motors based on the representation of a propulsion motor as a variable object the operation of which consists in the object structure transformation under the influence of various factors. The parameters of propulsion motors diagnostics are determined. Functional and mathematical models for diagnosing propellers have been created. The developed algorithm for propulsion motor diagnostics allows detecting faults with a given diagnosis depth. This algorithm can be used as a part of expert systems to monitor the technical condition of ship electric power plants. A complex approach to the construction of an algorithm for the propulsion motors technical diagnostics of based on the logical diagnosis model is proposed. A distinctive feature and novelty of the proposed algorithm for propulsion motor diagnostics is that it allows one to take into account
the mutual influence of diagnostic features on the object state and assess the technical condition of any propulsion motor from consistent methodological positions.
References
Patel M.R. Shipboard Electrical Power Systems CRC Press. Taylor & Francis Group, 2012. 370 p.
Lukyanov S.I., Karandaev A.S., Sarvarov A. S. [Development and Implementation of Intelligent Sys-tems for Electrical Equipment State Diagnostics]. Vestnik Magnitogorskogo gosudarstvennogo technich-eskogo universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University], 2014, no. 1, pp. 129–134. (in Russ.)
Barkov A.V., Barkova N.A. [Intelligent Monitoring and Diagnostics Systems of Machines by Vibra-tion]. Trudy Peterburgskogo energeticheskogo instituta povysheniya kvalifikatsii Mintopenergo Rossiyskoy Federatsii i Instituta vibratsii SShA [Proceedings of Petersburg Energy Institute of Training Executives and Experts of the Mi¬nistry of Energy of the Russian Federation and USA Vibration Institute], vol. 9, 1999. (in Russ.)
Kryukov O.V. Intelligent Electric Drives with IT algorithms. Automation and Remote Control, 2013,
vol. 74, no. 6, pp. 1043–1048. DOI: 10.1134/S0005117913060143
Babichev S.A. Automated Monitoring System for Drive Motors of Gas-Compressor Units. Automation and Remote Control, 2011, vol. 72, no. 1, pp. 175–180. DOI: 10.1134/S0005117911010176
Kryukov O.V. Methodology and Tools for Neuro-Fuzzy Prediction of the Status of Electric Drives of Gas Com-pressor Units. Russian Electrical Engineering, 2012, vol. 83, no. 9, pp. 516–520. DOI: 10.3103/S1068371212090064
Kryukov O.V., Titov V.V. Development of CAC Systems for Autonomous Wind-Energy Installations.
Automation in the Industry, 2009, no. 4, pp. 35–37.
Milov V.R., Kryukov O.V. Intellectual Management Decisions Support in Gas Industry. Automation and Remote Control, 2011, vol. 72, no. 5, pp. 1095–1101. DOI: 10.1134/S0005117911050183
Kalnynsh N.N., Kryukov O.V. Rubtsova I.E, Ryabkova E.Yu. Innovative Solutions in Design of Sys-tems of Compressor Station Illumination. Automation in the Industry, 2011, no. 9, pp. 19–21.
Podkovyrin D.S. [Neuro-Fuzzy Model of Synchronous Generator Technical Condition Diagnostics]. Glavnyi energetik [Chief Power Engineer], 2015, no. 11–12, pp. 55–60. (in Russ.)
Korobeinikov A.B., Sarvarov A.S. Analysis of Existing Methods for Diagnostics of Electric Motors and Perspectives of Their Development. Vestnik of Nosov Magnitogorsk State Technical University, 2015, no. 1, pp. 4–9.
Dar'enkov A.B., Khvatov O.S. [Highly Autonomous Electricity Generating Station]. Trudy Nizhe-gorodskogo gosudarstvennogo tekhnicheskogo universiteta [Proceedings of the Nizhny Novgorod State Tech-nical University], 2009, vol. 77, pp. 68–72. (in Russ.)
Steklov A.S., Titov V.G., Serebryakov A.V. [System for Diagnostics of Marine Synchronous Genera-tor Technical Condition]. Trudy Nizhe-gorodskogo gosudarstvennogo tekhnicheskogo universiteta im. R.E. Alekseeva [Proceedings of the R.E. Alekseev Nizhny Novgorod State Technical University], 2016, no. 1, pp. 60–64.
(in Russ.)
Kryukov O.V. [Method and System of Decision-making on Forecasting of Electrically Driven Gas Pum¬ping Units Technical Condition ]. Elektrotekhnicheskie sistemy i kompleksy [Electrotechnical systems and complexes], 2015, no. 4 (29), pp. 35–38. (in Russ.)
Kalyavin V.P., Rybakov L.M. Nadezhnost' i diagnostika elementov elektroustanovok [Reliability and
Diagnostics of Electrical Installation Elements]. St. Petersburg, Elmor Publ., 2009. 336 p.
Kadin S.N., Kazachenko A.P., Kryukov O.V., Reunov A.V. Questions Related to the Development of Metrological Assurance in the Design of Gazprom Facilities. Measurement Techniques, 2011, vol. 54, no. 8,
pp. 944–952. DOI: 10.1007/s11018-011-9832-7
Kryukov O.V. [Diagnostics of Electromechanical Parts of Wind Power Plants]. Elektromekhanichni I energoz-berigayuchi sistemi [Electromechanical and Energy Saving Systems], 2012, no. 3, pp. 549–552.
Babichev S.A., Bychkov E.V., Kryukov O.V. Analysis of Technical Condition and Safety of Gas-Pumping Units. Russian Electrical Engineering, 2010, vol. 81, no. 9, pp. 489–494. DOI: 10.3103/S1068371210090075
Kryukov O.V. [Unified Monitoring and Control System of Electric Driven Gas Compressor Units]. Advanced Information Technology, Automation Tools and Systems and their Implementation at Russian En-terprises: MNPK Collected Papers, AITA-2011, Moscow, IPU RAN, 2011, pp. 329–350. (in Russ.)
Steklov A.S., Titov V.G., Serebryakov A.V. [Determining the Degree of Efficiency of Marine Syn-chronous Generators with the Use of Artificial Neural Networks, Fuzzy]. Vestnik Chuvashskogo universiteta [Bulletin of Chuvash University], 2016, no. 1, pp. 97–104. (in Russ.)
