0
Research Papers: Gas Turbines: Turbomachinery

An Algebraic Approach to Fault Detection for Surge Avoidance in Turbo Compressor

[+] Author and Article Information
Sayyid Mahdi Alavinia

Department of Electrical and
Robotic Engineering,
Shahrood University of Technology,
Shahrood 3619995161, Iran
e-mail: zalloi@shahroodut.ac.ir

Mohammad Javad Khosrowjerdi

Department of Electrical Engineering,
Sahand University of Technology,
Tabriz 513351996, Iran
e-mail: khosrowjerdi@sut.ac.ir

Mohammad Ali Sadrnia

Department of Electrical and
Robotic Engineering,
Shahrood University of Technology,
Shahrood 3619995161, Iran
e-mail: masadrnia@shahroodut.ac.ir

Hossein Kheiri

Department of Mathematical Science,
Tabriz University,
Tabriz 5166616471, Iran

Mohammad Mehdi Fateh

Department of Electrical
and Robotic Engineering,
Shahrood University of Technology,
Shahrood 3619995161, Iran
e-mail: mmfateh@shahroodut.ac.ir

1Corresponding author.

2In this paper natural gas is referred to simply as gas.

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received February 17, 2014; final manuscript received June 29, 2014; published online September 16, 2014. Editor: David Wisler.

J. Eng. Gas Turbines Power 137(2), 022601 (Sep 16, 2014) (8 pages) Paper No: GTP-14-1105; doi: 10.1115/1.4028370 History: Received February 17, 2014; Revised June 29, 2014

This paper presents an innovative algebraic sensor fault detection approach for surge avoidance in turbo compressors (TC) in the natural gas compressor stations (GCS). The main objective is surge avoidance in the presence of sensor faults in TC. In this way, the robust parity space approach for fault detection is extended to highly nonlinear dynamic of TC based on Groebner basis and elimination technique. No work has been previously reported on the use of this technique for nonlinear dynamic systems with parametric uncertainties. This algebraic approach is simulated on the Moore–Greitzer control oriented model in the presence of parametric uncertainties, disturbances, and sensor faults. Simulation results are presented to demonstrate the effectiveness of the proposed fault detection approach.

FIGURES IN THIS ARTICLE
<>
Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.

References

U.S. Energy Information Administration, 2013, “International Energy Outlook 2013,” U.S. Department of Energy, Washington, DC, available at: http://www.eia.gov/forecasts/ieo/
U.S. Energy Information Administration, 2008, “About U.S. Natural Gas Pipelines-Transporting Natural Gas, Based on Data Through 2007/2008 With Selected Updates,” U.S. Department of Energy, Washington, DC, available at: http://www.eia.gov/
Spectra Energy, 2013, “Inside a Natural Gas Compressor Station,” Spectra Energy Corp., Houston, TX, available at: http://www.spectraenergy.com/content/documents/Media_Resources_PDFs/InsideNatGasCompressStn.pdf
Folga, S. M., 2007, “Natural Gas Pipeline Technology Overview, Decision and Information Sciences Division,” Argonne National Laboratory, Lemont, IL, Technical Report No. ANL/EVS/TM/08-5.
Janicka, J., Sadiki, A., Schäfer, M., and Heeger, C., 2013, Flow and Combustion in Advanced Gas Turbine Combustors, Springer, New York.
Saravanamuttoo, H. I. H., Rogers, G. F. C., Cohen, H., and Straznicky, P., 2008, Gas Turbine Theory, 6th ed., Pearson Education, Don Mills, ON, Canada.
Helivort, J. V., 2007, “Centrifugal Compressor Surge Modeling and Identification for Control,” Ph.D. thesis, Eindhoven University of Technology, Eindhoven, Netherlands.
Bohagen, B., 2007, “Active Surge Control of Centrifugal Compression Systems,” PhD thesis, Norwegian University of Science and Technology, Trondheim, Norway.
Bloch, H. P., 2006, Compressors and Modern Applications, 2nd ed., Wiley, Hoboken, NJ, pp. 115–127.
Reddy, B., 2011, “Compressors Used in Oil and Gas Industry,” Dresser-Rand Inc., New York, Technical Report.
Gatewood, J., 2012, “Future Compressor Station Technologies and Applications,” Gas/Electric Partnership Conference, Houston, TX, February 8–9.
Khosrowjerdi, M. J., 2011, “Robust Sensor Fault Reconstruction for Lipschitz Nonlinear Systems,” Math. Probl. Eng., 2011, p. 146038. [CrossRef]
Witczak, M., 2014, Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems (19 Lecture Notes in Electrical Engineering 266), Springer, Zurich, Switzerland.
Hua-Ming, Q., Zhen-Duo, F., Jun-Bao, L., and Lei-Lei, Y., 2013, “Robust Fault Diagnosis Algorithm for a Class of Lipschitz System With Unknown Exogenous Disturbances,” Measurement, 46(8), pp. 2324–2334. [CrossRef]
Davis, M. W., and O'Brien, W. F., 1987, “A Stage-by-Stage Post Stall Compression System Modeling Technique,” AIAA/SAE/ASME/ASEE 23rd Joint Propulsion Conference, San Diego, CA, June 29–July 2, AIAA Paper No. 87-2088. [CrossRef]
Badmus, O. O., Nett, C. N., and Schork, F. J., 1991, “An Integrated Full-Range Surge Control/Rotating Stall Avoidance Compressor Control System,” American Control Conference, Boston, MA, June 26–28, pp. 3173–3180.
Onions, R. A., and Foss, A. M., 1982, “Improvements in the Dynamic Simulation of Gas Turbines,” AGARD Conference Proceedings, Engine Handling, Marathon, Greece, Oct. 11–14, pp. 18-1–18-6.
Rowen, W. I., 1983, “Simplified Mathematical Representations of Heavy-Duty Gas Turbines,” ASME J. Eng. Gas Turbines Power, 105(4), pp. 865–869. [CrossRef]
Gravdahl, J. T., and Egeland, O., 1999, Compressor Surge and Rotating Stall: Modelling and Control, Springer, London.
Greitzer, E. M., 1997, “Surge and Rotating Stall in Axial Flow Compressors: Part I—Theoretical Compression System Model,” ASME J. Eng. Gas Turbines Power, 98(2), pp. 190–198. [CrossRef]
Greitzer, E. M., 1997, “Surge and Rotating Stall in Axial Flow Compressors: Part II—Experimental Results and Comparison With Theory,” ASME J. Eng. Gas Turbines Power, 98(2), pp. 199–217. [CrossRef]
Hahn, A., 2000, “Modeling and Control of Solid Oxide Fuel Cell–Gas Turbine Power Plant Systems,” M.Sc thesis, University of Pittsburgh, Pittsburgh, PA.
Gravdahl, J. T., and Egeland, O., 1997, “A Moore–Greitzer Axial Compressor Model With Spool Dynamics,” 36th IEEE Conference on Decision and Control, San Diego, CA, Dec. 10–12, pp. 4714–4719. [CrossRef]
Patton, R. J., Frank, P. M., and Clark, R. N., 1989, Fault Diagnosis in Dynamic Systems: Theory and Application, Prentice-Hall, Upper Saddle River, NJ.
Patton, R. J., Frank, P. M., and Clark, R. N., 2000, Issues of Fault Diagnosis for Dynamic Systems, Springer, Berlin.
Mahadevan, S., and Shah, S. L., 2009, “Fault Detection and Diagnosis in Process Data Using One-Class Support Vector Machines,” J. Process Control, 19(10), pp. 1627–1639. [CrossRef]
Perk, S., Teymour, F., and Cinar, A., 2010, “Statistical Monitoring of Complex Chemical Processes Using Agent-Based Systems,” Ind. Eng. Chem. Res., 49(11), pp. 5080–5093. [CrossRef]
Perk, S., Teymour, F., and Cinar, A., 2011, “Adaptive Agent-Based System for Process Fault Diagnosis,” Ind. Eng. Chem. Res., 50(15), pp. 9138–9155. [CrossRef]
Alcala, C. F., and Qin, S. J., 2011, “Analysis and Generalization of Fault Diagnosis Methods for Process Monitoring,” J. Process Control, 21(3), pp. 322–330. [CrossRef]
Venkatasubramanian, V., Rengaswamy, R., Kavuri, S. N., and Yin, K., 2003, “A Review of Process Fault Detection and Diagnosis Part III: Process History Based Methods,” Comput. Chem. Eng., 27(3), pp. 327–346. [CrossRef]
Kresta, J. V., MacGregor, J. F., and Marlin, T. E., 1991, “Multivariate Statistical Monitoring of Process Operating Performance,” Can. J. Chem. Eng., 69(1), pp. 35–47. [CrossRef]
Du, M., 2012, “Fault Diagnosis and Fault Tolerant Control of Chemical Process Systems,” Ph.D. thesis, McMaster University, Hamilton, ON, Canada.
Venkatasubramanian, V., Rengaswamy, R., Kavuri, S. N., and Yin, K., 2003, “A Review of Process Fault Detection and Diagnosis: Part I—Quantitative Model-Based Methods,” Comput. Chem. Eng., 27(3), pp. 293–311. [CrossRef]
Isermann, R., 2005, “Model-Based Fault-Detection and Diagnosis-Status and Applications,” Annu. Rev. Control, 29(1), pp. 71–85. [CrossRef]
Sami Shaker, M., 2012, “Active Fault-Tolerant Control of Nonlinear Systems With Wind Turbine Application,” Ph.D. thesis, The University of Hull, Hull, UK.
Clark, R. N., Fosth, D. C., and Walton, V. M., 1975, “Detecting Instrument Malfunctions in Control Systems,” IEEE Trans. Aerosp. Electron. Syst., AES-11(4), pp. 465–473. [CrossRef]
Li, W., Shah, S. L., and Xiao, D., 2008, “Kalman Filters in Non-Uniformly Sampled Multirate Systems: For FDI and Beyond,” Automatica, 44(1), pp. 199–208. [CrossRef]
Martínez-Sibaja, A., Alvarado-Lassman, A., Posada-Gómez, R., Blanca, E., Gonzalez-Sanchez, J., and Sandoval-González, O., 2013, “Dedicated Observer Scheme for Fault Diagnosis and Isolation in Instruments of an Anaerobic Reactor,” Procedia Technol., 7, pp. 173–180. [CrossRef]
HieuTrinh, D., and Chafouk, H., 2011, “Current Sensor FDI by Generalized Observer Scheme for a Generator in Wind Turbine,” 2011 International Conference on Communications, Computing and Control Applications (CCCA), Hammamet, Tunisia, Mar. 3–5. [CrossRef]
Simani, S., Fantuzzi, C., and Patton, R. J., 2002, Model-Based Fault Diagnosis in Dynamic System Using Identification Technique, Springer, London.
Frisk, E., 2001, “Residual Generation for Fault Diagnosis,” Ph.D. thesis, Linkoping University, Linkoping, Sweden.
Liu, L., 2006, “Robust Fault Detection and Diagnosis for Permanent Agent Synchronous Motors,” Ph.D. thesis, The Florida State University, Tallahassee, FL.
Cox, D., Little, J., and O'Shea, D., 2007, Ideals, Varieties, and Algorithms, 3rd ed., Springer, Heidelberg, Germany.
Shifler, R. M., 2013, “Computational Algebraic Geometry Applied to Invariant Theory,” M.Sc. thesis, VirginiaTech, Blacksburg, VA.
Svärd, C., Frisk, E., and Krysander, M., 2014, “Data-Driven and Adaptive Statistical Residual Evaluation for Fault Detection With an Automotive Application,” Mech. Syst. Signal Process., 45(1,3), pp. 170–192. [CrossRef]
Gertler, J. J., 1998, Fault Detection and Diagnosis in Engineering Systems, Marcel Dekker Inc., New York.
Zhi-wu, H., Ying-ze, Y., Jing, W., and Yun, L., 2013, “Parity Space-Based Fault Diagnosis of CCBII Braking System,” J. Cent. South Univ., 20(10), pp. 2922–2928. [CrossRef]
Rahkooy, H., and Zafeirakopoulos, Z., 2013, “On Computing Elimination Ideals Using Resultants With Applications to Gröbner Bases,” Doctoral Program on Computational Mathematics, Johannes Kepler University Linz and Austrian Academy of Sciences, Linz, Austria, DK Report 2013-04.

Figures

Grahic Jump Location
Fig. 1

Inside a natural gas station compressor [3]

Grahic Jump Location
Fig. 2

Schematic view of TC

Grahic Jump Location
Fig. 3

TC performance curves

Grahic Jump Location
Fig. 4

Compressor performance curve

Grahic Jump Location
Fig. 5

Model-based fault detection

Grahic Jump Location
Fig. 7

Annulus averaged dimensionless axial flow Φ when the sensor fault occurs at 26 s

Grahic Jump Location
Fig. 8

(a) Fault-free case. (b) Compressor speed B with the sensor fault occurs at 163 s.

Grahic Jump Location
Fig. 9

Fault detection for operating point determining in TC

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In