Diesel Fault Prediction Based on Optimized Gray Neural Network
In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1124665Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 957
 Hountalas. Dimitrios. T. Prediction of Marine Diesel Engine Performance under Fault Conditions. Applied Thermal Engineering, 2000, 20(18): 1753-1783P.
 Mustafa Canakci, Ahmet Necati Ozsezen, Erol Arcakioglu, et al. Prediction of Performance and Exhaust Emissions of Diesel Engine Fueled with Bio-diesel Produced from Wase Frying Palm Oil(J). Expert Systems Applications, 2009, 36(5): 9268-9280.
 S. F. Lu and N. M. Xie, Grey System Theory and Application (M). Beijing: Science Press, 2008, pp. 48-50.
 Z. W. Wang, T. Yu at al. The Application of GM (1.1) Model for Performance Prediction of Marine Diesel Engine(C). International Conference on Maritime Technology. 2012.
 X. B. Ye. Fault Forecast and Diagnosis of Sequential Turbocharging System Based on Gray Theory and Neural Network (J). Transactions of CSICE, 2008, 26(6): 543-549.
 X. Y. Li , “Optimized Grey RBF Prediction Model Based on Genetic Algorithm.” CSSE2008, pp. 74-77.
 M. Zhou, and S. D. Sun, The Principle and Application of Genetic Algorithm. Beijing: National Defence Industry Press, 1999, pp.15-22.
 J. L. Yuan, L. Zhong. The Dynamic Gray Radial Basis Function Prediction Model and Its Application(C). Proceeding of IEEE, ICICIC06, 2006: 582-585.
 Z. J. Yi and X. B. Ye, “Fault Prediction Model Based on Multiparameter Grey Error Neural Network.” Application Research of Computers, 2012.
 G. Y. Li, “Gray Neural Network Algorithm Improved by Genetic Algorithm.” Control Engineering, 2013.
 Z. Chen. Optimization Study on Ultra-short Term Wind Speed Forecasting of Wind Farms Based on BP Neural Network and Genetic Algorithm(J). Renewable Energy Resources, 2012, 30(2); 32-36.
 Benkaci M, Hoblos G, Langlois N, et al. Sensor Fault Detection and Isolation in Diesel Air Path Using Fuzzy-ARTMAP Neural Network. IEEE. ICNSC(C). Etienne DU, France, 2013, 728-733.
 Maass B, Stobart R. Control Oriented Real Time Model of Marine Power-station Diesel Engine Based on Neural Network (J). Computer Research and Development, 2011, 17(4): 386-390.
 Ghaffarpour, M, Esfahanian, V, Javaheri. A. Thermal Analysis of An SI Engine Piston Using Different Combustion Boundary Condition Treatments. Applied Thermal Engineering, 2006: 277-287P.
 Maja Krcum, Gojmir Radica, Zdeslav Juric. Application of The Expert Diagnostic System for Marine Diesel Engine Condition (C). The IASTED International Conference on Database and Applications. P169-173.
 Yuan Jingling, Zhong luo, Li X. Y. Intelligent Simulation and Prediction Methods of Structure State, 2008 Chinese Control and Decision Conference(2008CCDC), 1253-1255.
 W. Q. Zhao, D. X. Niu. A Mid-long Term Load Forecasting Model Based on Improved Gray Theory. 2010 2nd IEEE International Conference on Information Management and Engineering, 2010, (1):633-635.