Influence of Blade Deterioration on Compressor and Turbine Performance

2009 ◽  
Vol 132 (3) ◽  
Author(s):  
M. Morini ◽  
M. Pinelli ◽  
P. R. Spina ◽  
M. Venturini
Keyword(s):  
Gas Turbine ◽  
Rotational Speed ◽  
Mechanical Damage ◽  
Health State ◽  
Scaling Factors ◽  
Health Indices ◽  
Turbine Performance ◽  
Operating Region ◽  
State Determination ◽  
Simple Scaling

Gas turbine operating state determination consists of the assessment of the modification due to deterioration and fault of performance and geometric data characterizing machine components. One of the main effects of deterioration and fault is the modification of compressor and turbine performance maps. Since detailed information about actual modification of component maps is usually unavailable, many authors simulate the effects of deterioration and fault by a simple scaling of the map itself. In this paper, stage-by-stage models of the compressor and the turbine are used in order to assess the actual modification of compressor and turbine performance maps due to blade deterioration. The compressor is modeled by using generalized performance curves of each stage matched by means of a stage-stacking procedure. Each turbine stage is instead modeled as two nozzles, a fixed one (stator) and a moving one (rotor). The results obtained by simulating some of the most common causes of blade deterioration (i.e., compressor fouling, compressor mechanical damage, turbine fouling, and turbine erosion), occurring in one or more stages simultaneously, are reported in this paper. Moreover, compressor and turbine maps obtained through the stage-by-stage procedure are compared with the ones obtained by means of map scaling. The results show that the values of the scaling factors depend on the corrected rotational speed and on the load. However, since the variation in the scaling factors in the operating region close to the design corrected rotational speed is small, the use of the scaling factor as health indices can be considered acceptable for gas turbine health state determination at full load. Moreover, also the use of scaled maps in order to represent compressor and turbine behavior in deteriorated conditions close to the design corrected rotational speed can be considered acceptable.

Influence of Blade Deterioration on Compressor and Turbine Performance

2008 ◽  
Author(s):  
M. Morini ◽  
M. Pinelli ◽  
P. R. Spina ◽  
M. Venturini
Keyword(s):  
Gas Turbine ◽  
Mechanical Damage ◽  
Turbine Stage ◽  
Geometric Data ◽  
Turbine Performance ◽  
State Determination ◽  
Performance Curves ◽  
Common Causes ◽  
Simple Scaling ◽  
Main Effects

Gas turbine operating state determination consists of the assessment of the modification, due to deterioration and fault, of performance and geometric data characterizing machine components. One of the main effects of deterioration and fault is the modification of compressor and turbine performance maps. Since detailed information about actual modification of component maps is usually unavailable, many authors simulate the effects of deterioration and fault by a simple scaling of the map itself. In this paper, stage-by-stage models of the compressor and the turbine are used in order to assess the actual modification of compressor and turbine performance maps due to blade deterioration. The compressor is modeled by using generalized performance curves of each stage matched by means of a stage-stacking procedure. Each turbine stage is instead modeled as a couple of nozzles, a fixed one (stator) and a moving one (rotor). The results obtained by simulating some of the most common causes of blade deterioration (i.e., compressor fouling, compressor mechanical damage, turbine fouling and turbine erosion, occurring in one or more stages simultaneously) are reported in this paper. Moreover, compressor and turbine maps obtained through a stage-by-stage procedure are compared to the ones obtained by means of map scaling.

scholarly journals Gas Turbine Health State Determination: Methodology Approach and Field Application

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Michele Pinelli ◽  
Pier Ruggero Spina ◽  
Mauro Venturini
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Field Measurements ◽  
Field Application ◽  
Diagnostic Process ◽  
Health State ◽  
Gas Compression ◽  
State Determination ◽  
Measurement Validation ◽  
Machine Health

A reduction of gas turbine maintenance costs, together with the increase in machine availability and the reduction of management costs, is usually expected when gas turbine preventive maintenance is performed in parallel to on-condition maintenance. However, on-condition maintenance requires up-to-date knowledge of the machine health state. The gas turbine health state can be determined by means of Gas Path Analysis (GPA) techniques, which allow the calculation of machine health state indices, starting from measurements taken on the machine. Since the GPA technique makes use of field measurements, the reliability of the diagnostic process also depends on measurement reliability. In this paper, a comprehensive approach for both the measurement validation and health state determination of gas turbines is discussed, and its application to a 5 MW gas turbine working in a natural gas compression plant is presented.

A Multiple Operating Point Minimization Technique for Gas Turbine Operating State Determination

2002 ◽  
Author(s):  
M. Pinelli ◽  
P. R. Spina ◽  
M. Venturini
Keyword(s):  
Gas Turbine ◽  
Field Application ◽  
Operating Point ◽  
Health State ◽  
Characteristic Parameters ◽  
Estimation Errors ◽  
State Determination ◽  
Minimization Technique ◽  
Machine Health ◽  
Operating Points

Gas turbine operating state determination can be performed using Gas Path Analysis (GPA) techniques, which use measurements taken on the machine to calculate the characteristic parameters that are indices of the machine health state. The number and type of characteristic parameters that can be evaluated depend on the number and type of the available measured variables. Thus, when there are not enough measured variables to determine all the characteristic parameters, some of them have to be estimated independently of the actual gas turbine health state. In this way, variations due to aging or deterioration which, in the actual machine, may occur on these last characteristic parameters, cause estimation errors on the characteristic parameters assumed as problem unknowns. In the field application of GPA techniques the available instrumentation is often inadequate to ensure reliable operating state analysis. This problem may be partially overcome using a multiple operating point minimization technique. This consists of the determination of the characteristic parameters that minimize the sum of the square differences between measured and computed values of the measurable variables in multiple operating points. In this way the lack of data is overcome by data obtained in different operating points. This paper describes a procedure for gas turbine operating state determination based on a multiple operating point minimization technique and presents a study aimed at selecting the best set and number of operating points that have to be used.

Optimized Operating Point Selection for Gas Turbine Health State Analysis by Using a Multi-Point Technique

2003 ◽  
Author(s):  
M. Pinelli ◽  
P. R. Spina ◽  
M. Venturini
Keyword(s):  
Gas Turbine ◽  
Operating Point ◽  
Health State ◽  
Characteristic Parameters ◽  
Point Selection ◽  
Estimation Errors ◽  
State Determination ◽  
Minimization Technique ◽  
Operating Points ◽  
State Analysis

Gas turbine operating state determination can be performed using Gas Path Analysis (GPA) techniques, which use measurements taken on the machine to calculate the characteristic parameters that are indices of the machine health state. The number and type of characteristic parameters that can be evaluated depend on the number and type of the available measured variables. Thus, when there are not enough measured variables to determine all the characteristic parameters, some of them have to be estimated independently of the actual gas turbine health state. In this way, variations due to aging or deterioration which, in the actual machine, may occur on these last characteristic parameters, cause estimation errors on the characteristic parameters assumed as problem unknowns. The available instrumentation in field applications is often inadequate to ensure reliable operating state analysis when GPA-based techniques are used. This problem may be partially overcome using a multiple operating point minimization technique. This consists of the determination of the characteristic parameters that minimize the sum of the square differences between measured and computed values of the measurable variables in multiple operating points. In this way the lack of data is overcome by data obtained in different operating points. This paper describes a procedure for gas turbine operating state determination based on a multiple operating point minimization technique and presents a study aimed at selecting the best set and number of operating points that should be used.

Improvement of the Accuracy in Gas Turbine Health Determination

2001 ◽  
Author(s):  
M. Pinelli ◽  
M. Venturini
Keyword(s):  
Gas Turbine ◽  
Health Monitoring ◽  
Field Measurements ◽  
Monitoring Systems ◽  
Health State ◽  
State Determination ◽  
Health Monitoring Systems ◽  
Health Parameters

Health Monitoring Systems (HMS) based on operating state determination techniques that make use of field measurements are subjected to inaccuracies arising from measurements unreliability due to various kinds of uncertainties (such as sensors faults, measurements inaccuracies, etc.). In this paper, some techniques to improve the accuracy of gas turbine health state determination are presented: - a measurement conditioning technique based on the expected and trend values of measurements; - the evaluation of the best measurements/health parameters combination that should be used with respect to the gas turbine operating state determination.

Operating State Historical Data Analysis to Support Gas Turbine Malfunction Detection

2001 ◽  
Author(s):  
M. Pinelli ◽  
M. Venturini
Keyword(s):  
Gas Turbine ◽  
Field Measurements ◽  
Health State ◽  
Gas Compression ◽  
State Determination ◽  
First Results ◽  
Historical Data Analysis ◽  
On Line ◽  
Compressor Performance ◽  
Machine Health

Abstract The paper describes a methodology to determine gas turbine operating state based on the analysis of normalized field data. This methodology consists in normalizing measured value with respect to that expected, calculated in the actual boundary conditions and working point. The normalization procedure, if applied on line, provides useful information to support the machine Health State determination. In this paper, the methodology has been applied to field measurements taken on a 5 MW gas turbine running in a natural gas compression plant. The first results of field measurements analysis along a two year period are presented. Relations between compressor performance drops and the probable causes of malfunctioning have been identified. Some significant results are then presented.

Fusing unscented Kalman filter for performance monitoring and fault accommodation in gas turbine

2016 ◽  
Vol 232 (3) ◽  
pp. 556-570 ◽  
Author(s):  
Feng Lu ◽  
Yafan Wang ◽  
Jinquan Huang ◽  
Yihuan Huang ◽  
Xiaojie Qiu
Keyword(s):  
Kalman Filter ◽  
Gas Turbine ◽  
Extended Kalman Filter ◽  
Kalman Filters ◽  
Performance Monitoring ◽  
Unscented Kalman Filter ◽  
Estimation Accuracy ◽  
Health State ◽  
Sensor Failure ◽  
Turbine Performance

The Kalman filter is widely utilized for gas turbine health monitoring due to its simplicity, robustness, and suitability for real-time implementations. The most common Kalman filter for linear systems is linearized Kalman filter, and for nonlinear systems are extended Kalman filter and unscented Kalman filter. These algorithms have proven their capabilities to estimate gas turbine performance variations with a good accuracy, and the studies are done provided that all sensor measurements are available. In this paper, a nonlinear fusion approach with consistent diagnostic mechanism based on unscented Kalman filter is proposed, especially for gas turbine performance monitoring in the case of sensor failure. The architecture of fusion method comprises a set of local unscented Kalman filters and an information mixer. The local unscented Kalman filters are utilized to estimate health parameters of various component combinations, and the results are then transferred to the mixer for the integrated estimation of global health state in fusion structure. The consistent fault diagnosis and isolation logic is designed based on the fusion architecture and combined with the fusing unscented Kalman filter, called an improved fusing unscented Kalman filter. A systematic comparison of the generic linearized Kalman filter, extended Kalman filter, and unscented Kalman filter to their fusion filter kinds is presented for engine health estimation of gradual deterioration and abrupt fault. The studies show that the fusing unscented Kalman filter evidently outperforms the fusing linearized Kalman filter and fusing extended Kalman filter, while the fusing Kalman filters have slightly better estimation accuracy than the basic Kalman filters. In addition, the proposed methodology can reach the reliable performance monitoring with measurement uncertainty while the conventional Kalman filters collapse.

scholarly journals Gas Turbine Performance Forecast and Assessment: GE LM2500 in Outlook

2021 ◽  
Vol 1107 (1) ◽  
pp. 012025
Author(s):  
A. El-Suleiman ◽  
O.D. Samuel ◽  
S.T. Amosun ◽  
I. Emovon ◽  
F. I. Ashiedu ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Turbine Performance

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.

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