1 9/8/2015 INSTITUTE OF INFORMATION AND COMMUNICATION TECHNOLOGIES BULGARIAN ACADEMY OF SCIENCE Assoc. Prof. PhD Lyubka Doukovska Intelligent Systems Department AComIn: Advanced Computing for Innovation

9/8/ DIAGNOSTIC AND RISK ASSESSMENT PREDICTIVE ASSET MAINTENANCE The DVU /10 is a project of the Institute of Information and Communication Technologies, Bulgarian Academy of Sciences AComIn: Advanced Computing for Innovation

9/8/ The goal of the project is a holistic research of the theoretical foundations, alternative algorithms, software and techniques for predictive asset maintenance. This includes prognosis diagnostics, risk assessment, decision making for preventive or corrective actions and generating a schedule for their execution. AComIn: Advanced Computing for Innovation

9/8/ The subject of analysis is a device from Maritsa East 2 thermal power plant - a mill fan. The choice of the given power plant is not occasional. This is the largest thermal power plant on the Balkan Peninsula. AComIn: Advanced Computing for Innovation

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9/8/ Mill fans are main part of the fuel preparation in the coal fired power plants. The mill fans are used to mill, dry and feed the coal to the burners of the furnace chamber. They are together milling and transporting devices. Mill fans are most often used for power plants burning brown and lignite coal. AComIn: Advanced Computing for Innovation

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9/8/ AComIn: Advanced Computing for Innovation Mill Fan 1 — rotor; 2 — body; 3 — separator; 4 — internal circulation duct; 5 — maintenance and control flap; 6 — duct for bigger fraction recirculation; 7 — dust quality control flap.

9/8/ AComIn: Advanced Computing for Innovation The boiler which milling system is studied is a Benson type once- though sub-critical boiler. There are four mills per boiler. Each mill fan system has four radial bearings – two in the mill and two in the motor. Boiler Ep ,4-540 LT

9/8/ The Maritsa East 2 thermal power plant has four double blocks with direct-current boilers 175 MW each and four monoblocks with drum boilers 210 MW each. The fuel for both types of blocks is one and the same, low-quality Bulgarian lignite coal from the “Trayanovo 1” and “Trayanovo 2” mines. AComIn: Advanced Computing for Innovation

9/8/ AComIn: Advanced Computing for Innovation Maritsa East 2 Unit 1 Control Room

9/8/ AComIn: Advanced Computing for Innovation Standard statistical and probabilistic (Bayesian) approaches for diagnostics are inapplicable to estimate mill fan vibration state due to non-stationarity, non-ergodicity and the significant noise level of the monitored vibrations.

9/8/ List of papers Koprinkova-Hristova P., M. Hadjiski, L. Doukovska, S. Beloreshki - Recurrent Neural Networks for Predictive Maintenance of Mill Fan Systems, International Journal of Electronics and Telecommunications (JET), Versita, Warsaw, Poland, vol. 57, №3, ISSN , pp , Balabanov T., Koprinkova-Hristova P., L. Doukovska, M. Hadjiski, S. Beloreshki - Neural Network Model of Mill-Fan System Elements Vibration for Predictive Maintenance, Proc. of the International Symposium on Innovations in Intelligent SysTems and Applications, INISTA’11, June 2011, Istanbul, Turkey, ISBN: , pp , AComIn: Advanced Computing for Innovation

9/8/ List of papers Doukovska L., P. Koprinkova-Hristova, S. Beloreshki - Analysis of Mill Fan System for Predictive Maintenance, Proc. of the International Conference Automatics and Informatics, 3-7 October 2011, Sofia, Bulgaria, ISSN , pp , Hadjiski M., L. Doukovska, St. Kojnov - Nonlinear Trend Analysis of Mill Fan System Vibrations for Predictive Maintenance and Diagnostics, International Journal of Electronics and Telecommunications (JET), Versita, Warsaw, Poland, ISSN , vol. 58, 4, pp , DOI: /v , AComIn: Advanced Computing for Innovation

9/8/ List of papers Hadjiski M., L. Doukovska, P. Koprinkova-Hristova - Intelligent Diagnostic on Mill Fan System, Proc. of the 6th IEEE International Conference on Intelligent Systems – IS’12, 6-8 September 2012, Sofia, Bulgaria, ISBN , pp , Nikov V., P. Koprinkova-Hristova, L. Doukovska - Fuzzy Methods for Mill Fan Systems Technical Diagnostics, Proc. of the Federated Conference on Computer Science and Information Systems - FedCSIS’12, 9-12 September 2012, Wroclaw, Poland, ISBN , CD, pp , AComIn: Advanced Computing for Innovation

9/8/ List of papers Hadjiski M., L. Doukovska - Technical Diagnostics of Mill Fan System, Comptes rendus de l’Academie bulgare des Sciences, ISSN , vol. 65, 12, pp , Hadjiski M., L. Doukovska - CBR approach for Technical Diagnostics of Mill Fan System, Comptes rendus de l’Academie bulgare des Sciences, ISSN , vol. 66, 1, pp , AComIn: Advanced Computing for Innovation

9/8/ List of papers Koprinkova-Hristova P., L. Doukovska, P. Kostov - Working Regimes Classification for Predictive Maintenance of Mill Fan Systems, Proc. of the International Symposium on INnovations in Intelligent SysTems and Applications – INISTA’13, CD, ISBN IEEE, Doukovska L., S. Vassileva - Knowledge-based Mill Fan System Technical Condition Prognosis, Journal of the World Scientific and Engineering Academy and Society – WSEAS Transactions on Systems, Special Issue on Knowledge-based Modeling and Control of Мulti- factorial Processes, Print ISSN , E-ISSN , 2013 (accepted to review). AComIn: Advanced Computing for Innovation

9/8/ List of papers Hadjiski M., L. Doukovska, S. Vassileva - Intelligent Diagnostics of Mill Fan Technical Condition in Dust- Preparing Systems for 210 MW Power Units, International Journal of Computing and Informatics, Bratislava, Slovakia, ISSN , 2013, (to be published). Doukovska L., S. Vassileva - Intelligent Methods for Process Control and Diagnostics of Mill Fan System, Cybernetics and Information Technologies (CIT), ISSN , 2013, (to be published). AComIn: Advanced Computing for Innovation

9/8/ In the papers are presented promising results only using computational intelligence methods. Adequate for the case methods of computational intelligence (fuzzy logic, neural networks and more general AI techniques – the precedents’ method (CBR), machine learning (ML)) must be used. AComIn: Advanced Computing for Innovation Conclusion

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