Diagnostic Systems
The working experience of the group has led to the development of a general real time modular Monitoring and Diagnostic System (EGEFALOS) which can be easily customized to meet specific requirements. Implementations of this system have been used in practice to monitor service gas turbine engines operating on the field:
- FIAT TG20(55 MW)
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- GEC EM610B (60 MW)
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- ABB SULZER TYPE 10 (21 MW)
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- Military turbojet engine (GE J79) in test bed
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The group has also successfully developed and installed two customised Health Monitoring Systems for Combined Cycle Power Plants:
- the PPC single shaft configuration 385 MW CCPP at Lavrion, Attica, Greece and
- the Aluminium of Greece 334 MW Combined Heat and Power (CHP) plant at Ag. Nikolaos, Viotia, Greece.
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The specific systems connect online to the plant’s measurement database in order to continuously monitor and assess the health condition of the plant components (Gas Turbine, Steam Turbine, Heat Recovery Steam Generator and Condenser) with the aim to optimize plant operation and maintenance.
Also, the group possesses know-how for performing measurements for diagnostic tasks and a wide range of instrumentation is available at LTT/NTUA for this purpose.
The group has valuable experience in setting-up customized diagnostic systems by its participation in several European projects and collaboration with industrial partners and organizations. Relevant work has led to the development of specialized diagnostic software specially designed to meet each application’s particularity.
In the field of Engine Condition Monitoring and Fault Diagnosis extensive and substantial research has been performed by a team active since 1990, resulting in novel findings and establishment of innovative methods. The research work lies within two different categories, namely:
- Techniques using aerothermodynamic data (e.g. pressure, temperature). Applied indicatively to individual fault detection/identification, overall and component deterioration tracking, real time model-based diagnostics, etc.
- Techniques using fast response measurement data (e.g. vibration, sound, internal unsteady pressure) with utilization of signal processing methods for feature extraction. The techniques of this category have demonstrated the possibility of detecting and identifying faults of very small size, which would have remained unnoticed by conventional techniques, but can nevertheless evolve to catastrophic failures.