A Demonstration of Artificial Neural-Networks-Based Data Mining for
                    Gas-Turbine-Driven Compressor Stations

Botros, K. K.; Kibrya, G.; Glover, Alan

doi:10.1115/1.1414130

Cited by 18 publications

(5 citation statements)

References 8 publications

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“…The literature review reveals that use of MLP for modeling engine performance and emission characteristics is common [18][19][20][21][22]. But the application of radial basis function (RBF) networks for modeling of thermal systems is very limited [23][24][25][26]. In this context RBF technique has been used for modeling performance and emission characteristics of a biodiesel engine.…”

Section: Advances In Artificial Intelligencementioning

confidence: 99%

Radial-Basis-Function-Network-Based Prediction of Performance and Emission Characteristics in a Bio Diesel Engine Run on WCO Ester

Pai¹,

Rao²

2012

Advances in Artificial Intelligence

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Radial basis function neural networks (RBFNNs), which is a relatively new class of neural networks, have been investigated for their applicability for prediction of performance and emission characteristics of a diesel engine fuelled with waste cooking oil (WCO). The RBF networks were trained using the experimental data, where in load percentage, compression ratio, blend percentage, injection timing, and injection pressure were taken as the input parameters, and brake thermal efficiency (BTE), brake specific energy consumption (BSEC), exhaust gas temperature (), and engine emissions were used as the output parameters. The number of RBF centers was selected randomly. The network was initially trained using variable width values for the RBF units using a heuristic and then was trained by using fixed width values. Studies showed that RBFNN predicted results matched well with the experimental results over a wide range of operating conditions. Prediction accuracy for all the output parameters was above 90% in case of performance parameters and above 70% in case of emission parameters.

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Section: Advances In Artificial Intelligencementioning

confidence: 99%

Radial-Basis-Function-Network-Based Prediction of Performance and Emission Characteristics in a Bio Diesel Engine Run on WCO Ester

Pai¹,

Rao²

2012

Advances in Artificial Intelligence

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“…Song et al [10] have presented an ANN controller for gas turbine. Botros [3] demonstrated the application of ANN and RBF network for backup of critical parameters and health monitoring for gas turbine driven compressor station. Boccaletti [4] assessed the feasibility of NN approach in gas turbine combined cycle power plant process evaluation.…”

Section: Introductionmentioning

confidence: 99%

Soft Computation of Turbine Inlet Temperature of Gas Turbine Power Plant Using Type-2 Fuzzy Logic Systems

Gupta

Pareek

Kar

2007

2007 IEEE International Fuzzy Systems Conference

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This paper aims to demonstrate application of Type-2 Fuzzy Logic Systems (FLS) to predict a critical parameter of Gas Turbine in a power plant viz., the Turbine Inlet Temperature (TIT). Maintaining higher TIT than allowed severely affects the life of the components whereas operating at lower TIT may cause low efficiency and low load. Nonavailability of TIT, which cannot be measured directly, puts great limitations on efficient gas turbine operation. Accurate estimation of this parameter requires significant computing power and the time required places limitations on the conventional modeling methods for use in real time applications. It is also demonstrated here by way of comparison, that a type-2 FLS is more robust in the presence of noise uncertainties than a type-1 conventional FLS for this application. Results are verified through the practical plant data obtained from an 88 MW gas turbine power plant.

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“…Fault diagnosis-based methods are categorized by model-based and data-driven methods, and the most representative methods include Kalman filtering, fault observers, and artificial intelligence method such as neural network. Fault observer-based method shows great conve-nience and application prospects in the design of FTC system [4][5][6][7][8][9][10][11][12][13][14][15][16]. However, the traditional fault observer-based FTC method focuses on a certain type of faults, but the fault situation is very complex in actual situation.…”

Section: Introductionmentioning

confidence: 99%

Design of an Improved Hybrid FTC for Faults in Aero-Engine Closed-Loop Control System

Liu

Luo

Xiong

2021

International Journal of Aerospace Engineering

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Due to the aero-engines in a high temperature, pressure, and spool speed environment, the concurrent faults in actuator/sensor combined with degradation of the aero-engine could arise the problem of closed-loop instability during the flight. For this purpose, an improved hybrid fault-tolerant control (FTC) technique has been studied in this paper to deal with simultaneous failure of actuators and sensors associated with health parameters of the typical components’ degradation in aero-engines. The improved hybrid FTC structure combined with the nonlinear thermodynamic component-level (NCL) model-based estimation method merges fault estimation of actuators/sensors and typical components’ degradation estimation process into the FTC process. A robust H ∞ state feedback controller under the disturbance of simultaneous actuator and sensor faults is designed in the proposed method, together with the switching algorithm serving for the fault estimation and improved hybrid FTC channels. In order to show the feasibility of the proposed method, several semiphysical experiments are engaged to illustrate that the improved hybrid FTC structure can save the tolerant-control time and improve performance of the control system.

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A Demonstration of Artificial Neural-Networks-Based Data Mining for Gas-Turbine-Driven Compressor Stations

Cited by 18 publications

References 8 publications

Radial-Basis-Function-Network-Based Prediction of Performance and Emission Characteristics in a Bio Diesel Engine Run on WCO Ester

Radial-Basis-Function-Network-Based Prediction of Performance and Emission Characteristics in a Bio Diesel Engine Run on WCO Ester

Soft Computation of Turbine Inlet Temperature of Gas Turbine Power Plant Using Type-2 Fuzzy Logic Systems

Design of an Improved Hybrid FTC for Faults in Aero-Engine Closed-Loop Control System

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