Computer Models for Education on Performance Monitoring and Diagnostics of Gas Turbines

2002 ◽  
Vol 30 (3) ◽  
pp. 204-218 ◽  
Author(s):  
K. Mathioudakis ◽  
A. Stamatis ◽  
A. Tsalavoutas ◽  
N. Aretakis
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Measurement Data ◽  
Performance Model ◽  
Operating Conditions ◽  
Engine Operation ◽  
Monitoring And Diagnostics ◽  
Engine Components ◽  
The Way

The paper discusses how performance models can be incorporated in education on the subject of gas turbine performance monitoring and diagnostics. A particular performance model, built for educational purposes, is employed to demonstrate the different aspects of this process. The way of building a model is discussed, in order to ensure the connection between the physical principles used for diagnostics and the structure of the software. The first aspect discussed is model usage for understanding gas turbine behaviour under different operating conditions. Understanding this behaviour is essential, in order to have the possibility to distinguish between operation in ‘healthy’ and ‘faulty’ engine condition. A graphics interface is used to present information in different ways such as operating line, operating points on component maps, interrelation between performance variables and parameters. The way of studying faulty engine operation is then presented, featuring a novel comparison to existing simulation programs. Faults can be implanted into different engine components and their impact on engine performance studied. The notion of fault signatures on measured quantities is explained. The model has also a diagnostic capability, allowing the introduction of measurement data from faulty engines and providing a diagnosis, namely a picture of how the performance of engine components has deviated from a ‘healthy’ condition

Instructing the Principles of Gas Turbine Performance Monitoring and Diagnostics by Means of Interactive Computer Models

2000 ◽  
Author(s):  
K. Mathioudakis ◽  
A. Stamatis ◽  
A. Tsalavoutas ◽  
N. Aretakis
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Measurement Data ◽  
Engine Performance ◽  
Performance Model ◽  
Operating Conditions ◽  
Engine Operation ◽  
Turbine Performance ◽  
Engine Components

The paper discusses how the principles employed for monitoring the performance of gas turbines in industrial duty can be explained by using suitable Gas Turbine performance models. A particular performance model that can be used for educational purposes is presented. The model allows the presentation of basic rules of gas turbine engine behavior and helps understanding different aspects of its operation. It is equipped with a graphics interface, so it can present engine operating point data in a number of different ways: operating line, operating points of the components, variation of particular quantities with operating conditions etc. Its novel feature, compared to existing simulation programs, is that it can be used for studying cases of faulty engine operation. Faults can be implanted into different engine components and their impact on engine performance studied. The notion of fault signatures on measured quantities is clearly demonstrated. On the other hand, the model has a diagnostic capability, allowing the introduction of measurement data from faulty engines and providing a diagnosis, namely a picture of how the performance of engine components has deviated from nominal condition, and how this information gives the possibility for fault identification.

Hybrid Modeling of Heavy Duty Gas Turbines for On-Line Performance Monitoring

2014 ◽  
Author(s):  
Thomas Palmé ◽  
Francois Liard ◽  
Dan Cameron
Keyword(s):  
Gas Turbine ◽  
Surrogate Model ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Performance Model ◽  
Heavy Duty ◽  
Operational Parameters ◽  
Actual Performance ◽  
Real Gas ◽  
The Real

Due to their complex physics, accurate modeling of modern heavy duty gas turbines can be both challenging and time consuming. For online performance monitoring, the purpose of modeling is to predict operational parameters to assess the current performance and identify any possible deviation between the model’s expected performance parameters and the actual performance. In this paper, a method is presented to tune a physical model to a specific gas turbine by applying a data-driven approach to correct for the differences between the real gas turbine operation and the performance model prediction of the same. The first step in this process is to generate a surrogate model of the 1st principle performance model through the use of a neural network. A second “correction model” is then developed from selected operational data to correct the differences between the surrogate model and the real gas turbine. This corrects for the inaccuracies between the performance model and the real operation. The methodology is described and the results from its application to a heavy duty gas turbine are presented in this paper.

Gas Turbine Performance: New Application and Test Correction Curves

1995 ◽  
Author(s):  
Scott T. Cloyd ◽  
Arthur J. Harris
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Engine Performance ◽  
Exhaust System ◽  
Operating Parameter ◽  
Operating Conditions ◽  
Engine Operation ◽  
Pressure Losses ◽  
System Pressure ◽  
Oil Fuel

The gas turbine industry has adopted the practice of rating engine performance at ISO standard conditions; 15 degrees C, 1.033 ata, 100% methane fuel, and no inlet or exhaust system pressure losses with power output referenced to the generator terminals. (ISO, 1989) While these standards are useful in putting original equipment manufacturers’ (OEM’s) ratings on an equivalent basis it is not likely that an engine would be installed or tested under these types of conditions. To account for variations in engine operating conditions equipment manufacturers’ have utilized performance correction curves to show the influence of changing one operating parameter while holding all others constant. The purpose of this paper is to review the correction curves that are used for initial project application studies, and the variations to the curves that occur when a unit is put into service as a result of the methods used to control engine operation. Sample corrections curves and a brief explanation of the correction curves are presented to illustrate the variations in the curves. The paper also presents a new method for illustrating the influence of fuel heating value and composition on engine performance for natural gas and oil fuel. All data presented is for a single shaft, constant speed gas turbine. Two shaft or three shaft gas turbines will not have these correction curves.

Modelling and Assessment of Compressor Faults on Marine Gas Turbines

2012 ◽  
Author(s):  
I. Roumeliotis ◽  
N. Aretakis ◽  
K. Mathioudakis ◽  
E. A. Yfantis
Keyword(s):  
Gas Turbines ◽  
Engine Performance ◽  
Performance Model ◽  
Operating Conditions ◽  
Pollutant Emissions ◽  
Maximum Speed ◽  
Performance Modelling ◽  
Engine Operation ◽  
Marine Propulsion ◽  
And Performance

Any prime mover exhibits the effects of wear and tear over time, especially when operating in a hostile environment. Marine gas turbines operation in the hostile marine environment results in the degradation of their performance characteristics. A method for predicting the effects of common compressor degradation mechanisms on the engine operation and performance by exploiting the “zooming” feature of current performance modelling techniques is presented. Specifically a 0D engine performance model is coupled with a higher fidelity compressor model which is based on the “stage stacking” method. In this way the compressor faults can be simulated in a physical meaningful way and the overall engine performance and off design operation of a faulty engine can be predicted. The method is applied to the case of a twin shaft engine, a configuration that is commonly used for marine propulsion. In the case of marine propulsion the operating profile includes a large portion of off-design operation, thus in order to assess the engine’s faults effects, the engine operation should be examined with respect to the marine vessel’s operation. For this reason, the engine performance model is coupled to a marine vessel’s mission model that evaluates the prime mover’s operating conditions. In this way the effect of a faulty engine on vessels’ mission parameters like overall fuel consumption, maximum speed, pollutant emissions and mission duration can be quantified.

Application of Gas Path Analysis to Compressor Diagnosis of an Industrial Gas Turbine Using Field Data

2014 ◽  
Author(s):  
J. Blinstrub ◽  
Y. G. Li ◽  
M. Newby ◽  
Q. Zhou ◽  
G. Stigant ◽  
...  
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Field Data ◽  
Measurement Data ◽  
Diagnostic Technique ◽  
Operating Conditions ◽  
Maintenance Cost ◽  
Diagnostic Analysis ◽  
Major Life ◽  
Monitoring And Diagnostics

Maintenance cost is one of the major life cycle costs of gas turbine engines. To reduce the maintenance costs, the maintenance should be changed from preventive (or scheduled) maintenance to predictive (or condition-based) maintenance where condition monitoring and diagnostics become crucially important. This paper represents the application of a gas path diagnostic technique, Gas Path Analysis, to the diagnostic analysis of an aero-derivative gas turbine (GE LM2500+) operated by Manx Electricity Authority in the Isle of Man, UK. In the application, an engine thermodynamic model is created and adapted to the performance of the engine using field data obtained at different operating conditions. Different data pre-processing methods are presented and compared in the diagnostic analysis. The uncertainty of measurement data is analysed and the most suitable measurements are identified in the prediction of key gas path component degradation. A non-linear GPA diagnostic analysis provides promising results for the prediction of compressor degradation and the performance improvement due to a compressor water washing. Such diagnostic information would be very useful for maintenance engineers to optimise their maintenance activities including overhauls and compressor washing.

scholarly journals A Comparative Study on Fault Detection Methods for Gas Turbine Combustion Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 389
Author(s):  
Jinfu Liu ◽  
Zhenhua Long ◽  
Mingliang Bai ◽  
Linhai Zhu ◽  
Daren Yu
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Detection Methods ◽  
Distribution Model ◽  
Outlet Temperature ◽  
Combustion System ◽  
Comparison Results ◽  
Gas Turbine Combustion

As one of the core components of gas turbines, the combustion system operates in a high-temperature and high-pressure adverse environment, which makes it extremely prone to faults and catastrophic accidents. Therefore, it is necessary to monitor the combustion system to detect in a timely way whether its performance has deteriorated, to improve the safety and economy of gas turbine operation. However, the combustor outlet temperature is so high that conventional sensors cannot work in such a harsh environment for a long time. In practical application, temperature thermocouples distributed at the turbine outlet are used to monitor the exhaust gas temperature (EGT) to indirectly monitor the performance of the combustion system, but, the EGT is not only affected by faults but also influenced by many interference factors, such as ambient conditions, operating conditions, rotation and mixing of uneven hot gas, performance degradation of compressor, etc., which will reduce the sensitivity and reliability of fault detection. For this reason, many scholars have devoted themselves to the research of combustion system fault detection and proposed many excellent methods. However, few studies have compared these methods. This paper will introduce the main methods of combustion system fault detection and select current mainstream methods for analysis. And a circumferential temperature distribution model of gas turbine is established to simulate the EGT profile when a fault is coupled with interference factors, then use the simulation data to compare the detection results of selected methods. Besides, the comparison results are verified by the actual operation data of a gas turbine. Finally, through comparative research and mechanism analysis, the study points out a more suitable method for gas turbine combustion system fault detection and proposes possible development directions.

Assessment of Solar Steam Injection in Gas Turbines

2016 ◽  
Author(s):  
C. Kalathakis ◽  
N. Aretakis ◽  
I. Roumeliotis ◽  
A. Alexiou ◽  
K. Mathioudakis
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Fuel Efficiency ◽  
Thermal Power ◽  
Steam Injection ◽  
Power Production ◽  
Engine Operation ◽  
Efficiency Increase ◽  
Solar Receiver ◽  
Steam Production

The concept of solar steam production for injection in a gas turbine combustion chamber is studied for both nominal and part load engine operation. First, a 5MW single shaft engine is considered which is then retrofitted for solar steam injection using either a tower receiver or a parabolic troughs scheme. Next, solar thermal power is used to augment steam production of an already steam injected single shaft engine without any modification of the existing HRSG by placing the solar receiver/evaporator in parallel with the conventional one. For the case examined in this paper, solar steam injection results to an increase of annual power production (∼15%) and annual fuel efficiency (∼6%) compared to the fuel-only engine. It is also shown that the tower receiver scheme has a more stable behavior throughout the year compared to the troughs scheme that has better performance at summer than at winter. In the case of doubling the steam-to-air ratio of an already steam injected gas turbine through the use of a solar evaporator, annual power production and fuel efficiency increase by 5% and 2% respectively.

Impact of Operating Conditions and Design Parameters on Gas Turbine Hot Section Creep Life

2010 ◽  
Author(s):  
S. Eshati ◽  
M. F. Abdul Ghafir ◽  
P. Laskaridis ◽  
Y. G. Li
Keyword(s):  
Gas Turbines ◽  
Performance Model ◽  
Operating Conditions ◽  
Creep Model ◽  
Design Parameters ◽  
Gas Temperature ◽  
Creep Life ◽  
Cooling Effectiveness ◽  
Radial Temperature ◽  
The Impact

This paper investigates the relationship between design parameters and creep life consumption of stationary gas turbines using a physics based life model. A representative thermodynamic performance model is used to simulate engine performance. The output from the performance model is used as an input to the physics based model. The model consists of blade sizing model which sizes the HPT blade using the constant nozzle method, mechanical stress model which performs the stress analysis, thermal model which performs thermal analysis by considering the radial distribution of gas temperature, and creep model which using the Larson-miller parameter to calculate the lowest blade creep life. The effect of different parameters including radial temperature distortion factor (RTDF), material properties, cooling effectiveness and turbine entry temperatures (TET) is investigated. The results show that different design parameter combined with a change in operating conditions can significantly affect the creep life of the HPT blade and the location along the span of the blade where the failure could occur. Using lower RTDF the lowest creep life is located at the lower section of the span, whereas at higher RTDF the lowest creep life is located at the upper side of the span. It also shows that at different cooling effectiveness and TET for both materials the lowest blade creep life is located between the mid and the tip of the span. The physics based model was found to be simple and useful tool to investigate the impact of the above parameters on creep life.

Adaptation Application to Engine Modelling

2007 ◽  
Author(s):  
Jude Iyinbor
Keyword(s):  
Measurement Data ◽  
Engine Performance ◽  
Performance Model ◽  
Operating Conditions ◽  
Adaptation Process ◽  
Design Point ◽  
Component Map ◽  
Important Measurement ◽  
Unknown Component ◽  
Selection Of

The optimisation of engine performance by predictive means can help save cost and reduce environmental pollution. This can be achieved by developing a performance model which depicts the operating conditions of a given engine. Such models can also be used for diagnostic and prognostic purposes. Creating such models requires a method that can cope with the lack of component parameters and some important measurement data. This kind of method is said to be adaptive since it predicts unknown component parameters that match available target measurement data. In this paper an industrial aeroderivative gas turbine has been modelled at design and off-design points using an adaptation approach. At design point, a sensitivity analysis has been used to evaluate the relationships between the available target performance parameters and the unknown component parameters. This ensured the proper selection of parameters for the adaptation process which led to a minimisation of the adaptation error and a comprehensive prediction of the unknown component and available target parameters. At off-design point, the adaptation process predicted component map scaling factors necessary to match available off-design point performance data.

Calibration and Uncertainty Quantification of Gas Turbine Performance Models

2015 ◽  
Author(s):  
Manuel Arias Chao ◽  
Darrel S. Lilley ◽  
Peter Mathé ◽  
Volker Schloßhauer
Keyword(s):  
Uncertainty Quantification ◽  
Gas Turbine ◽  
Bayesian Approach ◽  
Least Squares Method ◽  
Measurement Data ◽  
Operating Conditions ◽  
Performance Models ◽  
Regression Problem ◽  
Calibration Problem ◽  
Calibration Parameters

Calibration and uncertainty quantification for gas turbine (GT) performance models is a key activity for GT manufacturers. The adjustment between the numerical model and measured GT data is obtained with a calibration technique. Since both, the calibration parameters and the measurement data are uncertain the calibration process is intrinsically stochastic. Traditional approaches for calibration of a numerical GT model are deterministic. Therefore, quantification of the remaining uncertainty of the calibrated GT model is not clearly derived. However, there is the business need to provide the probability of the GT performance predictions at tested or untested conditions. Furthermore, a GT performance prediction might be required for a new GT model when no test data for this model are available yet. In this case, quantification of the uncertainty of the baseline GT, upon which the new development is based on, and propagation of the design uncertainty for the new GT is required for risk assessment and decision making reasons. By using as a benchmark a GT model, the calibration problem is discussed and several possible model calibration methodologies are presented. Uncertainty quantification based on both a conventional least squares method and a Bayesian approach will be presented and discussed. For the general nonlinear model a fully Bayesian approach is conducted, and the posterior of the calibration problem is computed based on a Markov Chain Monte Carlo simulation using a Metropolis-Hastings sampling scheme. When considering the calibration parameters dependent on operating conditions, a novel formulation of the GT calibration problem is presented in terms of a Gaussian process regression problem.

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