Comparison of Linear and Non-Linear Gas Turbine Performance Diagnostics

2003 ◽  
Author(s):  
Ph. Kamboukos ◽  
K. Mathioudakis
Keyword(s):  
Gas Turbine ◽  
Condition Monitoring ◽  
Theoretical Background ◽  
Diagnostic Methods ◽  
Turbine Performance ◽  
Different Types ◽  
Non Linear ◽  
Computational Procedures ◽  
Monitoring And Diagnostics ◽  
Performance Diagnostics

The features of linear performance diagnostic methods are discussed, in comparison to methods based on full non-linear calculation of performance deviations, for the purpose of condition monitoring and diagnostics. First, the theoretical background of linear methods is overviewed to establish a relationship to the principles used by non-linear methods. Then computational procedures are discussed and compared. The effectiveness of determining component performance deviations by the two types of approaches is examined, on different types of diagnostic situations. A way of establishing criteria to define whether non-linear methods have to be employed is presented. An overall assessment of merits or weaknesses of the two types of methods is attempted, based on the results presented in the paper.

Comparison of Linear and Nonlinear Gas Turbine Performance Diagnostics

2005 ◽  
Vol 127 (1) ◽  
pp. 49-56 ◽  
Author(s):  
Ph. Kamboukos ◽  
K. Mathioudakis
Keyword(s):  
Gas Turbine ◽  
Theoretical Background ◽  
Diagnostic Methods ◽  
Nonlinear Methods ◽  
Turbine Performance ◽  
Different Types ◽  
Linear And Nonlinear ◽  
Computational Procedures ◽  
Monitoring And Diagnostics ◽  
Performance Diagnostics

The features of linear performance diagnostic methods are discussed, in comparison to methods based on full nonlinear calculation of performance deviations, for the purpose of condition monitoring and diagnostics. First, the theoretical background of linear methods is reviewed to establish a relationship to the principles used by nonlinear methods. Then computational procedures are discussed and compared. The effectiveness of determining component performance deviations by the two types of approaches is examined, on different types of diagnostic situations. A way of establishing criteria to define whether nonlinear methods have to be employed is presented. An overall assessment of merits or weaknesses of the two types of methods is attempted, based on the results presented in the paper.

The Use of Kalman Filter and Neural Network Methodologies in Gas Turbine Performance Diagnostics: A Comparative Study

2000 ◽  
Author(s):  
Allan J. Volponi ◽  
Hans DePold ◽  
Ranjan Ganguli ◽  
Chen Daguang
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Gas Turbine ◽  
Engine Operation ◽  
The Past ◽  
Fuel Flow ◽  
Turbine Performance ◽  
Engine System ◽  
Module Performance ◽  
Performance Diagnostics

The goal of Gas Turbine Performance Diagnostics is to accurately detect, isolate and assess the changes in engine module performance, engine system malfunctions and instrumentation problems from knowledge of measured parameters taken along the engine’s gas path. Discernable shifts in engine speeds, temperatures, pressures, fuel flow, etc., provide the requisite information for determining the underlying shift in engine operation from a presumed nominal state. Historically, this type of analysis was performed through the use of a Kalman Filter or one of its derivatives to simultaneously estimate a plurality of engine faults. In the past decade, Artificial Neural Networks (ANN) have been employed as a pattern recognition device to accomplish the same task. Both methods have enjoyed a reasonable success.

The Use of Kalman Filter and Neural Network Methodologies in Gas Turbine Performance Diagnostics: A Comparative Study

2003 ◽  
Vol 125 (4) ◽  
pp. 917-924 ◽  
Author(s):  
A. J. Volponi ◽  
H. DePold ◽  
R. Ganguli ◽  
C. Daguang
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Gas Turbine ◽  
Kalman Filters ◽  
Fault Isolation ◽  
Turbine Performance ◽  
Reasonable Degree ◽  
Engine System ◽  
Module Performance ◽  
Performance Diagnostics

The goal of gas turbine performance diagnositcs is to accurately detect, isolate, and assess the changes in engine module performance, engine system malfunctions and instrumentation problems from knowledge of measured parameters taken along the engine’s gas path. The method has been applied to a wide variety of commercial and military engines in the three decades since its inception as a diagnostic tool and has enjoyed a reasonable degree of success. During that time many methodologies and implementations of the basic concept have been investigated ranging from the statistically based methods to those employing elements from the field of artificial intelligence. The two most publicized methods involve the use of either Kalman filters or artificial neural networks (ANN) as the primary vehicle for the fault isolation process. The present paper makes a comparison of these two techniques.

scholarly journals A gas turbine diagnostic approach with transient measurements

2003 ◽  
Vol 217 (2) ◽  
pp. 169-177 ◽  
Author(s):  
Y. G. Li
Keyword(s):  
Steady State ◽  
Gas Turbine ◽  
Operating Conditions ◽  
Diagnostic Methods ◽  
Transient Processes ◽  
Diagnostic Approach ◽  
Turbine Performance ◽  
State Measurement ◽  
Transient Measurement ◽  
Steady State Measurement

Most gas turbine performance analysis based diagnostic methods use the information from steady state measurements. Unfortunately, steady state measurement may not be obtained easily in some situations, and some types of gas turbine fault contribute little to performance deviation at steady state operating conditions but significantly during transient processes. Therefore, gas turbine diagnostics with transient measurement is superior to that with steady state measurement. In this paper, an accumulated deviation is defined for gas turbine performance parameters in order to measure the level of performance deviation during transient processes. The features of the accumulated deviation are analysed and compared with traditionally defined performance deviation at a steady state condition. A non-linear model based diagnostic method, combined with a genetic algorithm (GA), is developed and applied to a model gas turbine engine to diagnose engine faults by using the accumulated deviation obtained from transient measurement. Typical transient measurable parameters of gas turbine engines are used for fault diagnostics, and a typical slam acceleration process from idle to maximum power is chosen in the analysis. The developed diagnostic approach is applied to the model engine implanted with three typical single-component faults and is shown to be very successful.

scholarly journals On-Board Condition Management for Aircraft Gas Turbines

1992 ◽  
Author(s):  
G. W. Gallops ◽  
F. D. Gass ◽  
M. H. Kennedy
Keyword(s):  
Control System ◽  
Gas Turbine ◽  
Condition Monitoring ◽  
System Architecture ◽  
Gas Turbines ◽  
Performance Model ◽  
Performance Models ◽  
Turbine Performance ◽  
Secondary Air ◽  
System Operating

A revolutionary approach to gas turbine condition monitoring is made possible by the recent development of accurate real-time gas turbine performance models. This paper describes an approach for an integrated condition management system operating concurrently with the gas turbine control system for improved availability, safety and economy. This paper considers the system subject to the requirements and constraints of aircraft gas turbines. A system architecture is described based on a primary, gas path performance model with supplementary models representing the secondary air, fuel and lubrication systems and the rotor system dynamics. Measurement and processing requirements for the system are defined. Preflight, in-flight and postflight application and analysis by the gas turbine operator are discussed.

Uncertainty Reduction in Gas Turbine Performance Diagnostics by Accounting for Humidity Effects

2001 ◽  
Author(s):  
K. Mathioudakis ◽  
A. Tsalavoutas
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Ambient Conditions ◽  
Ambient Temperatures ◽  
Turbine Performance ◽  
Industrial Gas Turbines ◽  
Industrial Gas Turbine ◽  
The Impact ◽  
Performance Diagnostics ◽  
Health Parameters

The paper presents an analysis of the effect of ambient humidity on the performance of industrial gas turbines and examines the impact of humidity on methods used for engine condition assessment and fault diagnostics. First, the way of incorporating the effect of humidity into a computer model of gas turbine performance is described. The model is then used to derive parameters indicative of the “health” of a gas turbine and thus diagnose the presence of deterioration or faults. The impact of humidity magnitude on the values of these health parameters is studied and the uncertainty introduced, if humidity is not taken into account, is assessed. It is shown that the magnitude of the effect of humidity depends on ambient conditions and is more severe for higher ambient temperatures. Data from an industrial gas turbine are presented to demonstrate these effects and to show that if humidity is appropriately taken into account, the uncertainty in the estimation of health parameters is reduced

Non-Linear Multiple Points Gas Turbine Off-Design Performance Adaptation Using a Genetic Algorithm

2010 ◽  
Author(s):  
Y. G. Li ◽  
M. F. Abdul Ghafir ◽  
L. Wang ◽  
R. Singh ◽  
K. Huang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Scaling Factor ◽  
Operating Conditions ◽  
Performance Models ◽  
Design Performance ◽  
Turbine Performance ◽  
Thermodynamic Performance ◽  
Non Linear ◽  
Performance Adaptation

Accurate gas turbine performance models are crucial in many gas turbine performance analysis and gas path diagnostic applications. With current thermodynamic performance modelling techniques, the accuracy of gas turbine performance models at off-design conditions is determined by engine component characteristic maps obtained in rig tests and these maps may not be available to gas turbine users or may not be accurate for individual engines. In this paper, a non-linear multiple point performance adaptation approach using a Genetic Algorithm is introduced with the aim to improve the performance prediction accuracy of gas turbine engines at different off-design conditions by calibrating the engine performance models against available test data. Such calibration is carried out with introduced non-linear map scaling factor functions by ‘modifying’ initially implemented component characteristic maps in the gas turbine thermodynamic performance models. A Genetic Algorithm is used to search for an optimal set of non-linear scaling factor functions for the maps via an objective function that measures the difference between the simulated and actual gas path measurements. The developed off-design performance adaptation approach has been applied to a model single spool turboshaft aero gas turbine engine and demonstrated a significant improvement in the performance model accuracy at off-design operating conditions.

scholarly journals Directional Solidification of Land-Based Gas Turbine Buckets

1989 ◽  
Author(s):  
Lance G. Peterson
Keyword(s):  
Directional Solidification ◽  
Gas Turbine ◽  
Process Improvement ◽  
Research Program ◽  
Mechanical Tests ◽  
Theoretical Background ◽  
Directionally Solidified ◽  
Product Lines ◽  
Turbine Performance ◽  
Complex Parts

Improvements in land-based gas turbine performance require materials capable of operating at increasingly higher temperatures. Innovative approaches to alloy and process improvement, such as directional solidification, can meet the more demanding conditions of new gas turbine designs. This paper outlines GE TBO’s multi-faceted research program for the development of directionally solidified GTD-111 first stage turbine buckets. Included are discussions of the theoretical background, casting program, mechanical tests and machining studies. The GTD-111 directional solidification program successfully met the technological challenges encountered in scaling up directional solidification experience from relatively small aircraft parts. Directionally solidified buckets are in production for several first stage product lines. Improvements in mold technology coupled with experience gained in the on-going research program indicate that more complex parts as well as single crystal parts are now feasible.

scholarly journals Gas Turbine Assessment for Air Management of Pressurized SOFC/GT Hybrid Systems

2006 ◽  
Vol 4 (4) ◽  
pp. 373-383 ◽  
Author(s):  
Alberto Traverso ◽  
Aristide Massardo ◽  
Rory A. Roberts ◽  
Jack Brouwer ◽  
Scott Samuelsen
Keyword(s):  
Gas Turbine ◽  
Hybrid System ◽  
Variable Speed ◽  
Ambient Conditions ◽  
Safety Measures ◽  
Turbine Performance ◽  
Wide Range ◽  
Different Types ◽  
Transient And Steady State

This paper analyzes and compares transient and steady-state performance characteristics of different types of single-shaft turbo-machinery for controlling the air through a pressurized solid oxide fuel cell (SOFC) stack that is integrated into a SOFC/GT pressurized hybrid system. Analyses are focused on the bottoming part of the cycle, where the gas turbine (GT) has the role of properly managing airflow to the SOFC stack for various loads and at different ambient conditions. Analyses were accomplished using two disparate computer programs, which each modeled a similar SOFC/GT cycle using identical generic gas turbine performance maps. The models are shown to provide consistent results, and they are used to assess: (1) the influence of SOFC exhaust composition on expander behavior for on-design conditions, (2) the off-design performance of the bypass, bleed, and variable speed controls for various part-load conditions and for different ambient conditions; (3) the features of such controls during abrupt transients such as load trip and bypass/bleed valve failure. The results show that a variable speed microturbine is the best option for off-design operation of a SOFC/GT hybrid system. For safety measures a bleed valve provides adequate control of the system during load trip. General specifications for a radial GT engine for integration with a 550kW pressurized SOFC stack are identified, which allow operation under a wide range of ambient conditions as well as several different cycle configurations.

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