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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.

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Figures

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Fig. 2

Schematic view of TC

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Fig. 3

TC performance curves

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Fig. 4

Compressor performance curve

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Fig. 5

Model-based fault detection

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Fig. 7

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

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Fig. 8

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

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Fig. 9

Fault detection for operating point determining in TC

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Fig. 1

Inside a natural gas station compressor [3]

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