Prediction Reliability of a Statistical Methodology for Gas Turbine Prognostics

2012 ◽  
Vol 134 (10) ◽  
Author(s):  
Mauro Venturini ◽  
Nicola Puggina
Keyword(s):  
Gas Turbine ◽  
Correction Factor ◽  
Gas Turbines ◽  
Threshold Value ◽  
False Alarms ◽  
Prediction Errors ◽  
Past Behavior ◽  
Turbine Performance ◽  
Performance Deterioration ◽  
Prediction Reliability

The performance of gas turbines degrades over time and, as a consequence, a decrease in gas turbine performance parameters also occurs, so that they may fall below a given threshold value. Therefore, corrective maintenance actions are required to bring the system back to an acceptable operating condition. In today’s competitive market, the prognosis of the time evolution of system performance is also recommended, in such a manner as to take appropriate action before any serious malfunctioning has occurred and, as a consequence, to improve system reliability and availability. Successful prognostics should be as accurate as possible, because false alarms cause unnecessary maintenance and nonprofitable stops. For these reasons, a prognostic methodology, developed by the authors, is applied in this paper to assess its prediction reliability for several degradation scenarios typical of gas turbine performance deterioration. The methodology makes use of the Monte Carlo statistical method to provide, on the basis of the recordings of past behavior, a prediction of future availability, i.e., the probability that the considered machine or component can be found in the operational state at a given time in the future. The analyses carried out in this paper aim to assess the influence of the degradation scenario on methodology prediction reliability, as a function of a user-defined threshold and minimum value allowed for the parameter under consideration. A technique is also presented and discussed, in order to improve methodology prediction reliability by means a correction factor applied to the time points used for methodology calibration. The results presented in this paper show that, for all the considered degradation scenarios, the prediction error is lower than 4% (in most cases, it is even lower than 2%), if the availability is estimated for the next trend, while it is not higher than 12%, if the availability is estimated five trends ahead. The application of a proper correction factor allows the prediction errors after five trends to be reduced to approximately 5%.

Prediction Reliability of a Statistical Methodology for Gas Turbine Prognostics

2012 ◽  
Author(s):  
Mauro Venturini ◽  
Nicola Puggina
Keyword(s):  
Gas Turbine ◽  
Correction Factor ◽  
Gas Turbines ◽  
Threshold Value ◽  
False Alarms ◽  
Prediction Errors ◽  
Past Behavior ◽  
Turbine Performance ◽  
Performance Deterioration ◽  
Prediction Reliability

The performance of gas turbines degrades over time and, as a consequence, a decrease in gas turbine performance parameters also occurs, so that they may fall below a given threshold value. Therefore, corrective maintenance actions are required to bring the system back to an acceptable operating condition. In today’s competitive market, the prognosis of the time evolution of system performance is also recommended, in such a manner as to take appropriate action before any serious malfunctioning has occurred and, as a consequence, to improve system reliability and availability. Successful prognostics should be as accurate as possible, because false alarms cause unnecessary maintenance and non-profitable stops. For these reasons, a prognostic methodology, developed by the authors, is applied in this paper to assess its prediction reliability for several degradation scenarios typical of gas turbine performance deterioration. The methodology makes use of the Monte Carlo statistical method to provide, on the basis of the recordings of past behavior, a prediction of future availability, i.e. the probability that the considered machine or component can be found in the operational state at a given time in the future. The analyses carried out in this paper aim to assess the influence of the degradation scenario on methodology prediction reliability, as a function of a user-defined threshold and minimum value allowed for the parameter under consideration. A technique is also presented and discussed, in order to improve methodology prediction reliability by means a correction factor applied to the time points used for methodology calibration. The results presented in this paper show that, for all the considered degradation scenarios, the prediction error is lower than 4% (in most cases, it is even lower than 2%), if the availability is estimated for the next trend, while it is not higher than 12%, if the availability is estimated five trends ahead. The application of a proper correction factor allows the prediction errors after five trends to be reduced to approximately 5%.

Modeling and Analysis of Gas Turbine Performance Deterioration

1994 ◽  
Vol 116 (1) ◽  
pp. 46-52 ◽  
Author(s):  
A. N. Lakshminarasimha ◽  
M. P. Boyce ◽  
C. B. Meher-Homji
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Field Data ◽  
Field Observations ◽  
Modeling And Analysis ◽  
Turbine Performance ◽  
Common Causes ◽  
Performance Deterioration ◽  
Simulation Results ◽  
Compressor Map

The effects of performance deterioration in both land and aircraft gas turbines are presented in this paper. Models for two of the most common causes of deterioration, viz., fouling and erosion, are presented. A stage-stacking procedure, which uses new installed engine field data for compressor map development, is described. The results of the effect of fouling in a powerplant gas turbine and that of erosion in a aircraft gas turbine are presented. Also described are methods of fault threshold quantification and fault matrix simulation. Results of the analyses were found to be consistent with field observations.

Modelling and Analysis of Gas Turbine Performance Deterioration

1992 ◽  
Author(s):  
A. N. Lakshminarasimha ◽  
M. P. Boyce ◽  
C. B. Meher-Homji
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Field Data ◽  
Field Observations ◽  
Turbine Performance ◽  
Common Causes ◽  
Performance Deterioration ◽  
Simulation Results ◽  
Compressor Map

The effects of performance deterioration in both land and aircraft gas turbines are presented in this paper. Models for two of the most common causes of deterioration viz. fouling and deterioration are presented. A stage stacking procedure which uses new installed engine field data for compressor map development is described. The results of the effect of fouling in a powerplant gas turbine and that of erosion in a aircraft gas turbine are presented. Also described are methods of fault threshold quantification and fault matrix simulation. Results of the analyses were found to be consistent with field observations.

Evolution of Gas Turbine Intake Air Filtration in a 420 MW Cogeneration Plant

2014 ◽  
Author(s):  
Steve Ingistov ◽  
Michael Milos ◽  
Rakesh K. Bhargava
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Economic Benefits ◽  
Cogeneration Plant ◽  
Air Filtration ◽  
Air Filter ◽  
Filter System ◽  
Turbine Performance ◽  
Filtration System ◽  
Operational Data

A suitable inlet air filter system is required for a gas turbine, depending on installation site and its environmental conditions, to minimize contaminants entering the compressor section in order to maintain gas turbine performance. This paper describes evolution of inlet air filter systems utilized at the 420 MW Watson Cogeneration Plant consisting of four GE 7EA gas turbines since commissioning of the plant in November 1987. Changes to the inlet air filtration system became necessary due to system limitations, a desire to reduce operational and maintenance costs, and enhance overall plant performance. Based on approximately 2 years of operational data with the latest filtration system combined with other operational experiences of more than 25 years, it is shown that implementation of the high efficiency particulate air filter system provides reduced number of crank washes, gas turbine performance improvement and significant economic benefits compared to the traditional synthetic media type filters. Reasons for improved gas turbine performance and associated economic benefits, observed via actual operational data, with use of the latest filter system are discussed in this paper.

Marine Gas Turbine Performance Model for More Electric Ships

2011 ◽  
Author(s):  
George M. Koutsothanasis ◽  
Anestis I. Kalfas ◽  
Georgios Doulgeris
Keyword(s):  
Gas Turbine ◽  
Fuel Consumption ◽  
Diesel Engines ◽  
Gas Turbines ◽  
Electric Propulsion ◽  
Operating Conditions ◽  
Prime Mover ◽  
Creep Life ◽  
Hull Fouling ◽  
Turbine Performance

This paper presents the benefits of the more electric vessels powered by hybrid engines and investigates the suitability of a particular prime-mover for a specific ship type using a simulation environment which can approach the actual operating conditions. The performance of a mega yacht (70m), powered by two 4.5MW recuperated gas turbines is examined in different voyage scenarios. The analysis is accomplished for a variety of weather and hull fouling conditions using a marine gas turbine performance software which is constituted by six modules based on analytical methods. In the present study, the marine simulation model is used to predict the fuel consumption and emission levels for various conditions of sea state, ambient and sea temperatures and hull fouling profiles. In addition, using the aforementioned parameters, the variation of engine and propeller efficiency can be estimated. Finally, the software is coupled to a creep life prediction tool, able to calculate the consumption of creep life of the high pressure turbine blading for the predefined missions. The results of the performance analysis show that a mega yacht powered by gas turbines can have comparable fuel consumption with the same vessel powered by high speed Diesel engines in the range of 10MW. In such Integrated Full Electric Propulsion (IFEP) environment the gas turbine provides a comprehensive candidate as a prime mover, mainly due to its compactness being highly valued in such application and its eco-friendly operation. The simulation of different voyage cases shows that cleaning the hull of the vessel, the fuel consumption reduces up to 16%. The benefit of the clean hull becomes even greater when adverse weather condition is considered. Additionally, the specific mega yacht when powered by two 4.2MW Diesel engines has a cruising speed of 15 knots with an average fuel consumption of 10.5 [tonne/day]. The same ship powered by two 4.5MW gas turbines has a cruising speed of 22 knots which means that a journey can be completed 31.8% faster, which reduces impressively the total steaming time. However the gas turbine powered yacht consumes 9 [tonne/day] more fuel. Considering the above, Gas Turbine looks to be the only solution which fulfills the next generation sophisticated high powered ship engine requirements.

scholarly journals Comparison of Coriolis and Turbine Type Flow Meters for Fuel Measurement in Gas Turbine Testing

1993 ◽  
Author(s):  
J. D. MacLeod ◽  
W. Grabe
Keyword(s):  
Steady State ◽  
Gas Turbine ◽  
Mass Flow ◽  
Gas Turbines ◽  
Gas Turbine Engine ◽  
Turbine Engine ◽  
Turbine Flowmeter ◽  
Turbine Performance ◽  
Coriolis Flowmeter ◽  
Project Objectives

The Machinery and Engine Technology (MET) Program of the National Research Council of Canada (NRCC) has established a program for the evaluation of sensors to measure gas turbine engine performance accurately. The precise measurement of fuel flow is an essential part of steady-state gas turbine performance assessment. Prompted by an international engine testing and information exchange program, and a mandate to improve all aspects of gas turbine performance evaluation, the MET Laboratory has critically examined two types of fuel flowmeters, Coriolis and turbine. The two flowmeter types are different in that the Coriolis flowmeter measures mass flow directly, while the turbine flowmeter measures volumetric flow, which must be converted to mass flow for conventional performance analysis. The direct measurement of mass flow, using a Coriolis flowmeter, has many advantages in field testing of gas turbines, because it reduces the risk of errors resulting from the conversion process. Turbine flowmeters, on the other hand, have been regarded as an industry standard because they are compact, rugged, reliable, and relatively inexpensive. This paper describes the project objectives, the experimental installation, and the results of the comparison of the Coriolis and turbine type flowmeters in steady-state performance testing. Discussed are variations between the two types of flowmeters due to fuel characteristics, fuel handling equipment, acoustic and vibration interference and installation effects. Also included in this paper are estimations of measurement uncertainties for both types of flowmeters. Results indicate that the agreement between Coriolis and turbine type flowmeters is good over the entire steady-state operating range of a typical gas turbine engine. In some cases the repeatability of the Coriolis flowmeter is better than the manufacturers specification. Even a significant variation in fuel density (10%), and viscosity (300%), did not appear to compromise the ability of the Coriolis flowmeter to match the performance of the turbine flowmeter.

Gas Turbine Performance Improvement by Retrofit of Advanced Technology

1983 ◽  
Author(s):  
V. C. Tendon ◽  
A. Zabrodsky
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Advanced Technology ◽  
Inlet Temperature ◽  
Performance Improvements ◽  
Turbine Performance ◽  
Higher Power ◽  
Available Technology ◽  
Life Consumption ◽  
Implementation Technique

Development and operation of larger size gas turbines have demonstrated that higher turbine inlet temperature can be sustained due to advancement in material and cooling technology. After a feasibility study it was determined that modern available technology can be applied to existing previous generation of machines. These programs are identified as “The Performance Upgrade of Gas Turbine”. Amongst the significant benefits that can be realized by retrofitting state of art parts in existing machines are higher power and more durable parts. This paper discusses various programs that are currently offered and implementation technique of upgrading the machines. A recent example is also presented. These unique programs are particularly attractive at the time of overall life consumption of the initial set of hot parts. At that point in an operating gas turbine it will be beneficial to retrofit the latest configuration parts to realize the performance improvements.

Gas Turbine Health State Prognostics by Means of Bayesian Hierarchical Models

2019 ◽  
Author(s):  
Enzo Losi ◽  
Mauro Venturini ◽  
Lucrezia Manservigi
Keyword(s):  
Gas Turbine ◽  
Field Data ◽  
Health Management ◽  
Theoretical Background ◽  
Health State ◽  
Prediction Errors ◽  
Probabilistic Prediction ◽  
Future Health ◽  
Bayesian Hierarchical ◽  
Prediction Reliability

Abstract The prediction of the time evolution of gas turbine performance is an emerging requirement of modern prognostics and health management (PHM), aimed at improving system reliability and availability, while reducing life cycle costs. In this work, a data-driven Bayesian Hierarchical Model (BHM) is employed to perform a probabilistic prediction of gas turbine future health state thanks to its capability to deal with fleet data from multiple units. First, the theoretical background of the predictive methodology is outlined to highlight the inference mechanism and data processing for estimating BHM predicted outputs. Then, BHM is applied to both simulated and field data representative of gas turbine degradation to assess its prediction reliability and grasp some rules of thumb for minimizing BHM prediction error. For the considered field data, the average values of the prediction errors were found to be lower than 1.0 % or 1.7 % for single- or multi-step prediction, respectively.

Determination of the optimum performance of gas turbines

2000 ◽  
Vol 214 (1) ◽  
pp. 243-255 ◽  
Author(s):  
J. H. Horlock ◽  
W. A. Woods
Keyword(s):  
Gas Turbine ◽  
Thermal Efficiency ◽  
Gas Turbines ◽  
Working Fluid ◽  
Optimum Conditions ◽  
Perfect Gas ◽  
Pressure Losses ◽  
Real Effects ◽  
Turbine Performance

Earlier analytical and graphical treatments of gas turbine performance, assuming the working fluid to be a perfect gas, are developed to allow for ‘non-perfect’ gas effects and pressure losses. The pressure ratios for maximum power and maximum thermal efficiency are determined analytically; the graphical presentations of performance based on the earlier approach are also modified. It is shown that the optimum conditions previously determined from the ‘air standard’ analyses may be changed quite substantially by the inclusion of the ‘real’ effects.

scholarly journals Industrial Gas Turbine Performance: Compressor Fouling and On-Line Washing

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Uyioghosa Igie ◽  
Pericles Pilidis ◽  
Dimitrios Fouflias ◽  
Kenneth Ramsden ◽  
Panagiotis Laskaridis
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Engine Performance ◽  
Operating Conditions ◽  
Compressor Cascade ◽  
Compressor Blades ◽  
Turbine Performance ◽  
Industrial Gas Turbines ◽  
On Line ◽  
The Impact

Industrial gas turbines are susceptible to compressor fouling, which is the deposition and accretion of airborne particles or contaminants on the compressor blades. This paper demonstrates the blade aerodynamic effects of fouling through experimental compressor cascade tests and the accompanied engine performance degradation using turbomatch, an in-house gas turbine performance software. Similarly, on-line compressor washing is implemented taking into account typical operating conditions comparable with industry high pressure washing. The fouling study shows the changes in the individual stage maps of the compressor in this condition, the impact of degradation during part-load, influence of control variables, and the identification of key parameters to ascertain fouling levels. Applying demineralized water for 10 min, with a liquid-to-air ratio of 0.2%, the aerodynamic performance of the blade is shown to improve, however most of the cleaning effect occurred in the first 5 min. The most effectively washed part of the blade was the pressure side, in which most of the particles deposited during the accelerated fouling. The simulation of fouled and washed engine conditions indicates 30% recovery of the lost power due to washing.

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