2011, 2011(Special): 614-623. doi: 10.3934/proc.2011.2011.614

New regularizing approach to determining the influence coefficient matrix for gas-turbine engines

1. 

Institute of Mathematical Sciences and Information Technologies, University of Liepaja, Transport and Telecommunication Institute, 1 Lomonosov Street, Riga LV-1019, Latvia

2. 

Transport and Telecommunication Institute, 1 Lomonosov Street, Riga LV-1019, Latvia

Received  July 2010 Revised  April 2011 Published  October 2011

This paper presents the new approach to the formation of the gas turbine engine diagnostic matrix employing Tikhonov regularization method and taking into account the compressor properties shift under the condition of engine air-gas channel alteration. This method allows eliminating the certain inadequacy of the diagnostic matrices in some cases and removes the restrictions on their implementation for gas turbine engines diagnostics. The elabo- rated regularization algorithm of the calculation-identi cation matrix reversion permits to determine the diagnostic matrix persistently. The suggested method of registration of the compressor properties shift allows providing the adequacy of the engine mathematical model taking into consideration the depreciation of the engine and air-gas channel and consequently obtaining the adequate diagnostic matrix. It is o ered to employ the obtained diagnostic model in the on-board systems of the gas turbine engine control and diagnostics.
Citation: Sharif E. Guseynov, Sergey M. Yunusov. New regularizing approach to determining the influence coefficient matrix for gas-turbine engines. Conference Publications, 2011, 2011 (Special) : 614-623. doi: 10.3934/proc.2011.2011.614
[1]

Stefan Kindermann, Andreas Neubauer. On the convergence of the quasioptimality criterion for (iterated) Tikhonov regularization. Inverse Problems & Imaging, 2008, 2 (2) : 291-299. doi: 10.3934/ipi.2008.2.291

[2]

Vinicius Albani, Adriano De Cezaro, Jorge P. Zubelli. On the choice of the Tikhonov regularization parameter and the discretization level: A discrepancy-based strategy. Inverse Problems & Imaging, 2016, 10 (1) : 1-25. doi: 10.3934/ipi.2016.10.1

[3]

Bernard Ducomet, Alexander Zlotnik. On a regularization of the magnetic gas dynamics system of equations. Kinetic & Related Models, 2013, 6 (3) : 533-543. doi: 10.3934/krm.2013.6.533

[4]

Armin Lechleiter, Marcel Rennoch. Non-linear Tikhonov regularization in Banach spaces for inverse scattering from anisotropic penetrable media. Inverse Problems & Imaging, 2017, 11 (1) : 151-176. doi: 10.3934/ipi.2017008

[5]

Thorsten Hohage, Mihaela Pricop. Nonlinear Tikhonov regularization in Hilbert scales for inverse boundary value problems with random noise. Inverse Problems & Imaging, 2008, 2 (2) : 271-290. doi: 10.3934/ipi.2008.2.271

[6]

Guozhi Dong, Bert Jüttler, Otmar Scherzer, Thomas Takacs. Convergence of Tikhonov regularization for solving ill--posed operator equations with solutions defined on surfaces. Inverse Problems & Imaging, 2017, 11 (2) : 221-246. doi: 10.3934/ipi.2017011

[7]

Frank Pörner, Daniel Wachsmuth. Tikhonov regularization of optimal control problems governed by semi-linear partial differential equations. Mathematical Control & Related Fields, 2018, 8 (1) : 315-335. doi: 10.3934/mcrf.2018013

[8]

Bernd Hofmann, Barbara Kaltenbacher, Elena Resmerita. Lavrentiev's regularization method in Hilbert spaces revisited. Inverse Problems & Imaging, 2016, 10 (3) : 741-764. doi: 10.3934/ipi.2016019

[9]

Qinghua Ma, Zuoliang Xu, Liping Wang. Recovery of the local volatility function using regularization and a gradient projection method. Journal of Industrial & Management Optimization, 2015, 11 (2) : 421-437. doi: 10.3934/jimo.2015.11.421

[10]

El-Sayed M.E. Mostafa. A nonlinear conjugate gradient method for a special class of matrix optimization problems. Journal of Industrial & Management Optimization, 2014, 10 (3) : 883-903. doi: 10.3934/jimo.2014.10.883

[11]

Tao Wu, Yu Lei, Jiao Shi, Maoguo Gong. An evolutionary multiobjective method for low-rank and sparse matrix decomposition. Big Data & Information Analytics, 2017, 2 (1) : 23-37. doi: 10.3934/bdia.2017006

[12]

Liying Wang, Weiguo Zhao, Dan Zhang, Linming Zhao. A geometric inversion algorithm for parameters calculation in Francis turbine. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1373-1384. doi: 10.3934/dcdss.2015.8.1373

[13]

Hiroshi Nishiura. Joint quantification of transmission dynamics and diagnostic accuracy applied to influenza. Mathematical Biosciences & Engineering, 2011, 8 (1) : 49-64. doi: 10.3934/mbe.2011.8.49

[14]

Jie Zhang, Shuang Lin, Li-Wei Zhang. A log-exponential regularization method for a mathematical program with general vertical complementarity constraints. Journal of Industrial & Management Optimization, 2013, 9 (3) : 561-577. doi: 10.3934/jimo.2013.9.561

[15]

Tim Hoheisel, Christian Kanzow, Alexandra Schwartz. Improved convergence properties of the Lin-Fukushima-Regularization method for mathematical programs with complementarity constraints. Numerical Algebra, Control & Optimization, 2011, 1 (1) : 49-60. doi: 10.3934/naco.2011.1.49

[16]

Yuanchang Sun, Lisa M. Wingen, Barbara J. Finlayson-Pitts, Jack Xin. A semi-blind source separation method for differential optical absorption spectroscopy of atmospheric gas mixtures. Inverse Problems & Imaging, 2014, 8 (2) : 587-610. doi: 10.3934/ipi.2014.8.587

[17]

Lena Noethen, Sebastian Walcher. Tikhonov's theorem and quasi-steady state. Discrete & Continuous Dynamical Systems - B, 2011, 16 (3) : 945-961. doi: 10.3934/dcdsb.2011.16.945

[18]

Bruno Sixou, Valentina Davidoiu, Max Langer, Francoise Peyrin. Absorption and phase retrieval with Tikhonov and joint sparsity regularizations. Inverse Problems & Imaging, 2013, 7 (1) : 267-282. doi: 10.3934/ipi.2013.7.267

[19]

Daniela Calvetti, Erkki Somersalo. Microlocal sequential regularization in imaging. Inverse Problems & Imaging, 2007, 1 (1) : 1-11. doi: 10.3934/ipi.2007.1.1

[20]

Martin Gugat, Falk M. Hante, Markus Hirsch-Dick, Günter Leugering. Stationary states in gas networks. Networks & Heterogeneous Media, 2015, 10 (2) : 295-320. doi: 10.3934/nhm.2015.10.295

 Impact Factor: 

Metrics

  • PDF downloads (0)
  • HTML views (0)
  • Cited by (0)

Other articles
by authors

[Back to Top]