CONTROL OF ENERGY EFFICIENCY IN INDUSTRY AND HOUSING AND COMMUNAL SERVICES
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UDC 517.9
Dynamic characteristics measuring system with sensor model to analyze the electrical input signals
Ekaterina Valer'evna Yurasova , South Ural State University (national research University), Chelyabinsk, Associate Professor, urasova2004@gmail.com
Abstract
The structure of the measuring system that based on a sensor model and implements modal control of dynamic characteristics is examined. On its basis a method of dynamic parameters adjustment depending on the noise level at the output of the sensor is developed. The proposed system can be used to analyze the electrical input signals in operation and emergency operation.
Keywords
measurement system, modal control, en dynamic measurement
References
1. Bizyaev, M.N. Dynamic models and algorithms for restoring the dynamically destorted signals in measuring systems using in sliding modese [Text]: Ph.D. Thesis: 05.13.01 / M.N. Bizyaev. – Chelyabinsk, 2004.– 179 с (in Russian)
2. Volosnikov A.S. Neural network models and algorithms for signal recovery dynamic measurement systems [Text]: Ph.D. Thesis: 05.13.01 / A.S. Volosnikov. – Chelyabinsk, 2006.– 20 p. (in Russian)
3. Soldatkina E.V. Adaptation algorithms of parameters measuring system to minimize the dynamic error assessment [Text]: Ph.D. Thesis: 05.13.14 / E.V.Soldatkina. – Chelyabinsk, 2000. – 20 p. (in Russian).
4. Solopchenko G.N. Inverse problems in measurement procedures. Izmereniya, kontrol', avtomatizatsiya. 1983. no 2, pp. 32–46.
5. Shestakov A.L., Sviridyuk G.A. Optimal Measurement of Dynamically Distorted Signals. Vestnik Yuzhno-Ural’skogo gosudarstvennogo universiteta. Seriya «Matematicheskoe modelirovanie i programmirovanie». 2011, no. 17 (234), pp. 70–75.
6. Shestakov A.L., Ibryaeva O.L., Iosifov D.Yu. The solution of inverse dynamics measurements using status vector of the primary measuring converter. Avtometriya. 2012, vol. 48. no 5, pp. 74—81.
7. Shestakov A.L. Dynamic error correction method // IEEE Transactions on Instrumentation and Measurement. — 1996. — Т. 45. — № 1. — С. 250—255.
2. Volosnikov A.S. Neural network models and algorithms for signal recovery dynamic measurement systems [Text]: Ph.D. Thesis: 05.13.01 / A.S. Volosnikov. – Chelyabinsk, 2006.– 20 p. (in Russian)
3. Soldatkina E.V. Adaptation algorithms of parameters measuring system to minimize the dynamic error assessment [Text]: Ph.D. Thesis: 05.13.14 / E.V.Soldatkina. – Chelyabinsk, 2000. – 20 p. (in Russian).
4. Solopchenko G.N. Inverse problems in measurement procedures. Izmereniya, kontrol', avtomatizatsiya. 1983. no 2, pp. 32–46.
5. Shestakov A.L., Sviridyuk G.A. Optimal Measurement of Dynamically Distorted Signals. Vestnik Yuzhno-Ural’skogo gosudarstvennogo universiteta. Seriya «Matematicheskoe modelirovanie i programmirovanie». 2011, no. 17 (234), pp. 70–75.
6. Shestakov A.L., Ibryaeva O.L., Iosifov D.Yu. The solution of inverse dynamics measurements using status vector of the primary measuring converter. Avtometriya. 2012, vol. 48. no 5, pp. 74—81.
7. Shestakov A.L. Dynamic error correction method // IEEE Transactions on Instrumentation and Measurement. — 1996. — Т. 45. — № 1. — С. 250—255.
Source
Technical science – from theory to practice: 20TH international correspondence materials of scientific-practical Conference (17 april 2013), Novosibirsk: “SibAK” Publ. 2013, pp. 134–142. (The main)