Broc Rovsing - Performance Monitoring

GAS TURBINE

Performance Monitoring

Aerothermal performance monitoring provides tools to optimise operation of gas turbines. Based on thermodynamic models, machinery component conditions are continuously supervised and compared to baseline conditions. Optimising inlet filter exchange, compressor on and off-line wash intervals, contributes to large cost savings and increased production.

PERFORMANCE MONITORING - provides all necessary parameters for assessment of the real performance

Component function deteriorates during normal operation of a gas turbine. Over an operational year, there is a substantial reduction in performance and efficiency resulting in power loss and increased fuel consumption. However, most of this loss is reversible by inlet filter exchange and compressor on-line or off-line wash. The optimum timing for filter exchange or compressor washing differs extremely

between geographical locations and through seasonal variations. Other faults, such as increased tip clearance, internal leakage and corrosion are permanent and develope typically at a much slower rate. Without an automated monitoring system, it is very difficult to judge the actual efficiency of a gas turbine, because the performance and heat rate depend on a set of operating conditions, for example:

• Ambient temperature, pressure and humidity • Power output • Fuel type • Filter/Inlet pressure loss • Turbine exhaust pressure loss • Speed (Multi-shaft gas turbine)

Classification

Integrated Aerothermal and Mechanical Condition Monitoring

Rotating equipment and Process Engineers no longer need to manually analyse massive amounts of data sets, which typically contain mostly redundant data. When the TM OPENpredictor system identifies deterioration in mechanical or aerothermal condition, the specialists are warned via the dedicated alarm systems.

OPENpredictor provides functions to classify data into different machine states. The performance monitoring (or Functional Condition Monitoring, FCM) uses the function to classify data into different load levels. The system uses recorded measurements of the gas turbine. This can be from the commissioning of the gas turbine or from any other arbitrary time. One set of measurements is needed for each load class. These measurements are valid for the actual machine and they form the baseline, the reference performance, against which future performance will be compared. TM

Example of OPENpredictor mimic for a heavy industrial gas turbine TM

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The OPENpredictor system performs both FCM and Mechanical Condition Monitoring, MCM. The system provides a complete condition assessment of the gas turbine, gearbox and drive unit, to minimise operation risk, optimise inspection and maintenance intervals, schedule filter exchange and optimise the compressor wash intervals. Operation risks are reduced, as all failure mode specific monitoring tasks are performed automatically.

Variation in these conditions may have an influence of more than 20% on the apparent performance and efficiency.

Each individual 'alert' or 'alarm' can be assigned to a dedicated user such as Operator, Process Engineer or Rotating Equipment Engineer. This provides maximum efficiency for the organisation related to individual responsibilities.

Compressor Fouling The compressor efficiency and airflow reduction is forecasted. The system will issue a forecast 'alert' showing that these two parameters will deteriorate to such values that a compressor wash will be required within a user specified time frame. The integrated function of MCM and FCM provides information that a wash was effective, without resulting in excessive unbalance or pressure pulsations in the compressor sections, which would lead to increased fatigue.

Therefore, to get an immediate indication of deviation from base line performance (the performance when the machine was new and commissioned) it requires a thermodynamic model of the process and a set of thermodynamic measurements to provide parameters for assessment of the real performance.

Combustor Pulsation Combustor pulsations lead to excessive dynamic loading of the combustor liners and power turbine blades and result in efficiency loss. Early identification of combustor pulsations can be used to change fuel flow and load conditions to avoid these problems. This function is provided in the MCM application packages, as pulsation frequency analysis is used in the combustor assessment.

Exhaust Gas Temperature plot

Filter Fouling Filter fouling results in efficiency and power loss. The user can specify the maximum deterioration acceptable. As the system corrects the actual measured data to reference conditions, a forecast can be calculated. The system will issue a forecast 'alert' showing the filter fouling will deteriorate to a value, which requires filter exchange within a user specified time frame. This allows planning of filter exchange at the most economical moment.

Turbine Fouling Reduced power turbine efficiency leads to increased fuel consumption, power reduction and increased CO2 production. Specifically at crude oil fired systems, power turbine fouling will develop. The forecasted efficiency reduction can be used to schedule inspection and cleaning. Exhaust Temperature Distribution Large variation in the exhaust gas temperature distribution to the average value indicates combustion problems leading to increased thermal stress in the power turbine, which has to be identified as soon as possible. The classification of data provides information on how to change operation conditions to minimise the deviation, avoiding shutdown of the turbine. Other gas turbine specific faults can be monitored, forecasted and diagnosed automatically, after specification of the fault patterns. Additional Manual Analysis tools are provided in the application package such as Multiple Trend Plots and 2 dimensional Scatter Plots with extensive filter options to display data only for specific operation conditions.

AND IT WORKS...

The OPENpredictor system installed at Helsinki Energy’s Vuosaari B Power Plant provides on-line mechanical health information of all critical machines. TM

The system also executes Performance Monitoring for the gas and steam turbines. Helsinki Energy’s overall objective was to combine machine mechanical health and performance assessment as the basis for O & M decisions. The standard delivered vibration protection systems could not provide diagnostic information on machinery faults. The OPENpredictor system was purchased to further process the signals from the vibration protection system sensors in order to identify fault symptoms hidden in the raw signals. The control system did not provide information on the gas and steam turbine performance. By transferring process data from the central system to OPENpredictor , it is possible to calculate the machine performance and to analyse deviations from normal behaviour. TM

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A gas turbine at Helsinki Energy’s Vuosaari B Power Plant, Finland

Further information: Please contact us for specific information on hard and/or software modules, available as Product Data Sheets. Reference Installation Sheets are also available. ROVSING Dynamics is globally represented by its subsidiaries and sales executives and exclusive contracts with distributors. All industries, no matter where they are located, can benefit from the use of OPENpredictor . ROVSING Dynamics Headquarters are situated in Copenhagen, Denmark. Copyright2001. All rights, title and interest in and the Software, Hardware and Services detailed in this document and all copyrights, patents, trademarks, service marks or other intellectual property or proprietary rights relating thereto belong exclusively to ROVSINGDynamics A/S

Marielundvej 41 · DK-2730 Herlev · Denmark Tel: +45 46 90 72 00 · Fax: +45 44 84 60 40 · VAT No. 20 05 24 73 e-mail: [email protected] · www.rovsing-dynamics.com

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