A Software Tool for Gas Turbine on-condition Monitoring and Diagnostics
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1 A Software Tool for Gas Turbine on-condition Monitoring and Diagnostics R. Bettocchi, M. Pinelli, M. Venturini - University of Ferrara P.R. Spina DIEM - University of Bologna S. Sebastianelli ENI E & P Division F. Bezzi CREA s.r.l.
2 Objectives a brief introduction to policy and objectives in compression system maintenance a methodology for gas turbine operating state analysis, based on a "Gas Path Analysis technique a software tool for gas turbine monitoring and diagnostics some results of the application of the methodology (natural gas treatment plant - ENI - E & P Division Casalborsetti - Ravenna)
3 Low Pressure Gas Compression 20 [GNm 3 ] 15 Low pressure compressed gas Total produced gas Percentage on total product year 2002
4 Gas Compressors 60 running stand by year
5 ENI s Maintenance Policy ENI E&P OUTSOURCING Years 80s Years 90s Since 96 Maintenance planning Maintenance execution Spares procurement & storage Maintenance planning Maintenance minor works execution Spares procurement & storage Contracts Management Capital Spares Storage Performances Analysis Maintenance History (CMMS) On call contracts with Vendors for work supervision Six open contracts with major Vendors for works execution Two MGS Contracts: - Maintenance engineering - Maintenance planning - Spares procurement & storage - Works execution - Continuous improvement
6 The change Outsourcing process ENI E&P Core Business focusing Quick and continuous technological improvement CHANGE MANAGEMENT New role of Operation and Maintenance personnel
7 Need for a decision-making support tool To enable operation and maintenance personnel to cope with: Global Service Contract Management Maintenance problems Operative problems Performances gap analysis A decision-making support tool based on actual gas compressor health state has been developed
8 Predictive maintenance Efficiency and productivity Adopting on-condition maintenance in order to reduce emergency stops and optimize scheduled maintenance
9 Research program To perform gas turbine, a software system was developed according to: - user-friendly and easy-to-use; - possibility of remote access; - useful for operators with different levels of interest Gas turbine user for natural gas compression Methodology and calculation programs Software system architecture
10 Gas turbine health state determination Program for the calculation of the gas turbine thermodynamic cycle (calibrated on the specific machine) Direct mode Linear Regression Measured value Q m Expected value Q m Q = * m Q Q m ' m Normalized value Normalized Cycle program measurements are independent from the actual working point and are comparable each other Inverse mode Health indices determination (as efficiencies, characteristic flow passage areas and pressure drops along the gas path) Health state determination allows the calculation of the loss of production
11 Software architecture Inserimento Manual manuale dati insertion Acquisition Acquisizione dati da DCS from DCS Regression Regressione Measurements Misure Input.txt Dati calcolo Data Database Database SATURN-D Direct Diretto Inverse Inverso Maintenance Interventi reports Regressione Ciclo Direct diretto cycle Ciclo Inverse inverso cycle Output Direct.out diretto.txt Output Inverse.out inverso.txt Visualizzazione su schermo
12 Database contents - acquired measurements - normalized measurements and acceptability bands - non-measured computed quantities (T it, power output) - health indices Correlation - loss of production measurements/health Indices to - maintenance actions maintenance actions Already stored data - 4 gas turbines - 1 measurement set per day (June today) - maintenance actions
13 Gas turbines under investigation Natural gas treatment plant of Casalborsetti (Ravenna - Italy) PGT5R/2 Power output 5180 kw Overall efficiency 34.7 % Inlet mass flow rate 25.7 kg/s Pressure ratio 9.13 Exhaust gas outlet temperature 543 C Gas generator rotational speed rpm Power turbine rotational speed rpm Test case Variation of normalized values and of health indices before and after a compressor off-line wash (14/07/00-01/01/01)
14 Normalized measurement analysis 1.2 Q* [%] Normalized measurements compressor outlet pressure compressor outlet temperature exhaust gas temperature day 168 Due to deterioration: p* oc decreases T* oc almost constant T* ot increases In agreement with previously analyzed data on the same machine Normalized value Variation [%] Outlet compressor pressure -3.4 Outlet compressor temperature +1.5 Exhaust gas temperature +3.8
15 Health indices analysis 1.2 X Health indices compressor efficiency compressor flow function gas generator efficiency day 168 Compressor fouling = compressor efficiency and mass flow function decrease GGT erosion = increase of the mass flow function and an apparent efficiency increase Health index Variation [%] Compressor efficiency -4.7 Compressor flow function -4.9 Gas generator turbine efficiency +2.8
16 Lost Production Index LPI = Q gasc Q Q gasc gasm C = clean condition - M = measured LPI increase = decrease of actual production LPI quantifies (also economically) gas turbine loss of performance 0.8 LPI [%] Lost Production Index % day 168
17 Conclusions (1/2) Through the application of the methodology, the most significant malfunctions can be detected and quantified: - planning the most appropriate moment for machine stop - on-line actions (compressor wash) - adaptation of control logic to actual gas turbine operating conditions - loss of production determination - support/control decision tool for maintenance actions (adaptation to actual health state)
18 Conclusions (2/2) plant manager: LPI evaluation (actual economical benefit of keeping the plant in operation rather than stop it to perform maintenance actions) maintenance manager: analysis of the normalized measurement and of the health indices variations overall performance deterioration components responsible for performance deterioration type and quantification of the deterioration maintenance chief engineer: analysis of the normalized measurement and of the health indices variations (performance recovery after maintenance actions)
19 Future developments improvement of knowledge on each gas turbine behavior development and application of Expert Systems (Fuzzy Logic based) development of AI techniques (decisional algorithms) Software DEMO
20 A Software Tool for Gas Turbine on-condition Monitoring and Diagnostics R. Bettocchi, M. Pinelli, M. Venturini - University of Ferrara P.R. Spina DIEM - University of Bologna S. Sebastianelli ENI E & P Division F. Bezzi CREA s.r.l.
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