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.

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.

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.

Assessment of the Robustness of Gas Turbine Diagnostics Tools Based on Neural Networks

2006 ◽  
Author(s):  
R. Bettocchi ◽  
M. Pinelli ◽  
P. R. Spina ◽  
M. Venturini ◽  
G. A. Zanetta
Keyword(s):  
Neural Networks ◽  
Gas Turbine ◽  
Measurement Errors ◽  
Health State ◽  
Artificial Intelligence Technique ◽  
Boundary Load ◽  
Set Up ◽  
Operating Points ◽  
Range Of Variation ◽  
Selection Of

The paper deals with the set-up and the application of an Artificial Intelligence technique based on Neural Networks (NNs) to gas turbine diagnostics, in order to evaluate its capabilities and its robustness. The data used for both training and testing the NNs were generated by means of a Cycle Program, calibrated on a Siemens V94.3A gas turbine. Such data are representative of operating points characterized by different boundary, load and health state conditions. The analyses carried out are aimed at the selection of the most appropriate NN structure for gas turbine diagnostics, by evaluating NN robustness with respect to: • interpolation capability and accuracy in the presence of data affected by measurement errors; • extrapolation capability in the presence of data lying outside the range of variation adopted for NN training; • accuracy in the presence of input data corrupted by bias errors; • accuracy when one input is not available. This situation is simulated by replacing the value of the unavailable input with its nominal value.

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.

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.

Operating point selection for primary and secondary users in cognitive radio networks

2009 ◽  
Vol 53 (8) ◽  
pp. 1158-1170 ◽  
Author(s):  
Xavier Gelabert ◽  
Ian F. Akyildiz ◽  
Oriol Sallent ◽  
Ramon Agustí
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Operating Point ◽  
Point Selection ◽  
Secondary Users ◽  
Selection For ◽  
Primary And Secondary Users

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 A New Test Facility for Testing of Cooled Gasturbine Components

1998 ◽  
Author(s):  
Ulf R. Rådeklint ◽  
Christer S. Hjalmarsson
Keyword(s):  
Heat Transfer ◽  
Gas Turbine ◽  
Temperature Fields ◽  
Test Facility ◽  
Operating Point ◽  
Ir Camera ◽  
Turbine Cooling ◽  
Air Temperatures ◽  
Turbine Vanes ◽  
Conventional Instrumentation

A high pressure hot test facility for cooled gas turbine components has been developed for use in turbine cooling research. In this facility, heat transfer tests for a sector of real turbine vanes can be performed under continuous operation. The heat transfer tests are performed at an operating point that is scaled down from the real engine operating point. The compressor can deliver air at the rate of up to 10 kg/s at 20 bars. Air temperatures of up to 1170 K can be achieved by using an oil-fired combustor. Besides conventional instrumentation such as thermocouples and pressure probes, the facility is equipped with an IR-camera to map two-dimensional wall temperature fields. Hot wire anemometry and an LDV system are used to determine mean and fluctuating velocity components. This paper describes design and performance of the test facility as well as the control and measurement equipment. The test and evaluation procedures used for testing of cooled gas turbine vanes are also presented.

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