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Diagnostic Health Monitoring Modules for

Gas Turbines/Combined Cycles

This photo shows a 160 megawatt F-class gas turbine

readied for delivery.

Power generators are concerned with the maintenance

costs, availability, and reliability associated with bothconventional and advanced gas turbines. Monitoringgeneration assets using data historians interfaced to thecontrol system has become widely accepted. This type of

monitoring can be confined to the plant, but has becomeincreasingly more accessible remotely to technical support

staff and management.

While most monitoring systems rely heavily on basictrending capabilities or simple equipment models, few are

specific to combustion turbines (CTs)/combined-cycles(CCs) and it is rare to have monitoring provisions tailored

to the unique features of model-specific CTs. These types

of monitoring services are often bundled with morecomprehensive, long-term O&M service agreements. Plant

operators typically view these arrangements as an OEMmechanism to manage their own business interests.

Project Summary and Deliverables

EPRI has developed a series of diagnostic modules to helpimprove plant O&M and provide a foundation for

predictive-based maintenance activities. This project

addresses the implementation and model-specificadaptation of the EPRI monitoring modules.

EPRI has developed a series of real-time healthmanagement technologies that are rolling out of

development and field-testing. This project involvesimplementing one or more of these modules dependingon a companys individual needs:

Sensor Validation and Recovery Module (SVRM). Animportant front-end feature of the health-management

system, sensor validation checks the integrity of senseddata before they are passed to the diagnostic and

prognostic modules. The software uses a combination/

fusion of neural network model-based/generic signal-processing-based approaches to ensure the highest possiblesensor fault detection confidence with minimal false alarms.If a gas-path sensor fault is detected, neural network

models are used to calculate proxy or recoveredsignal values that allow diagnostic and component life

assessments until the fault is corrected.

Development of a comprehensive CombustionTurbine Health Management (CTHM) system willplay a critical role in the cost reduction of electricityby improving reliability, availability, andmaintainability. Specific benefits derived fromcomputer-based GT condition and health-monitoringpredictive systems include:

Reduced nuisance shutdowns andunplanned outages

Optimum engine operation Improved maintenance planning Protection against catastrophic

failure via real-time fault assessment

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1014465 September 2006

Electric Power Research Institute3420 Hillview Avenue, Palo Alto, California 94304-1395 PO Box 10412, Palo Alto, California 94303-0813 USA

800.313.3774 650.855.2121 askepri@epri.com www.epri.com 2006 Electric Power Research Institute (EPRI), Inc. All rights reserved. Electric Power Research Institute and EPRI are registered service marks of the Electric Power Research Institute.

Printed on recycled paper in the United States of America

Combustion Turbine Performance and Fault DiagnosticModule (CTPFDM). Monitoring the performance of CT

components allows users to determine which portion ofthe engine will be responsible for an observed decrease in

output or efficiency. Through regular monitoring, anoperator will know when to execute maintenance actions.

The CTPFDM carries out six main functions: data checking,measured (or actual) performance, expected performance,corrected performance, evaporative cooling performance,

and fault diagnostics. Thermodynamic engineering formulasderive key performance parameters such as heat rate and

compressor isentropic efficiency. Performance calculationsare based on the expected base and part-load performance

data. The revised performance calculations then transposethe actual performance results to standard day results byfactoring out the effects of ambient conditions on CT

performance.

The Combined-Cycle Performance and Fault DiagnosticModule (CCPFDM). This module offers a cost-effective,

easy-to-use solution for monitoring and diagnosing thecondition of a CC plant and determining the benefits of

maintenance actions. Four major plant pieces can impactCC unit performance: the CT, the heat recovery steam

generator (HRSG), the steam turbine (ST), and thecondenser/cooling water system (COND). The CCPFDMapproach for obtaining the overall expected performance

involves a series of correction curves to account for thechange in total plant output, heat rate, and steam-turbine

exhaust flow. The CCPFDM performance calculationoutput includes parameters that indicate the magnitude

of degradation of the CT, HRSG, ST, and COND

plant components.Remaining Life Module (RLM). This module is a low-cost,

easy-to-use software program for calculating hot-sectioncomponent maintenance intervals such as combustioninspection, hot gas-path inspection, and major overhauls as

noted by the CT supplier OEM. Adjustments to the basicOEM baseline can be introduced to address specific

component concerns. In a related project, EPRI isdeveloping its own alternative remaining-life correlations

that are model- and component-specific.

Start-Up/Combustion Process Health-Management Module(SCPHMM). The module addresses specific monitoring,

trend analysis, and fault classification of CT start-up/combustion process variables. It also performs

automated monitoring and analysis of the relationshipsand associated trends in fuel supply and overall exhaust

gas temperature.

Vibration Fault Diagnostics Module (VFDM). The moduleperforms real-time assessment of mechanical faults using

vibration signatures collected from specific turbine

locations using a combination of AI-based fault classifiers.Domain knowledge regarding particular vibration faultfrequencies, fixed-frequency ranges, per-rev excitations,

and structural resonance are extracted from the vibrationspectrums and used to develop a knowledge base. Fuzzylogic membership functions and trained neural networks

detect anomalous conditions and classify fault types.

Price of Project

Implementing one or more modules is dependent onspecific plant equipment and control/monitoring system

used. To receive a cost estimate to implement amonitoring module(s), provide the EPRI technical contactwith the CT model and control system/data historian type.

Schedule

The CTHM project set is an ongoing effort. The scheduleof individual projects will be dependent on the scope ofmodule implementation and module adaptations to site-

specific features.

Who Should Join

The CTHM project will benefit owner/operators of gasturbines in simple or combined service applications.

Contact Information

For more information, contact the EPRI CustomerAssistance Center at 800.313.3774 (askepri@epri.com).

Technical Contact

Leonard Angello at 650.855.7939 (langello@epri.com).