Objective
The objective of this project is to develop a gas turbine health monitoring demonstrator which will be able to identify faults in more detail than other systems currently available, enabling better fault diagnosis, improved maintenance planning, higher plant reliability and reduced operating costs.
The results included:
- the development of a specific acoustical imaging software (acoustic holography in cylindrical geometry),
- the design and development of an acoustical imaging system including a double-layer array of microphones,
- a multi-channels acquisition system, based on a 32 bits HP Unix work station),
- the preparation of an engine simulation software (thermodynamic and performance model),
- the preparation and the performance of the tests (engine at characteristic operating rates of its components, and engine containing realistic simulated faults),
- data reduction of acoustical and thermodynamical measurements, as well as the investigation of faults signatures for different unsteady quantity measurements (acoustic, vibration, internal pressure and shaft displacements).
Simulated faults were: rotor stage fouling, individual rotor blade fouling, individual rotor blade twisted, and stator blade restaggering.
For each of these faults, as tested on an individual gas turbine, a correct identification has been accomplished. This includes both the detection of gross component faults (eg minor compressor fouling) and the detection of local faults within the engine component (eg an individual damaged blade). This capability has not been achieved by any other non-intrusive gas turbine health monitoring system.
The demonstrator will be able to identify and process the following classes of fault : blade vibrations (at extreme ambient conditions or unusual speeds), compressor faults (blade erosion, mechanical damage), combustor faults, performance loss (with identification of the parts of the engine causing the loss).
To achieve this goal, the demonstrator will :
-use multisensors acquisition
-use new sensors technologies (for high temperatures)
-use advanced data processing, namely acoustical imaging and gas path analysis method
-use an expertise to be acquired theoretically and experimentally on a large range of faults
-integrate in a high level expert software the acquired expertise and data handling capability to improve monitoring efficiency and decision making quality for both designers and operators.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences mathematics pure mathematics geometry
- natural sciences computer and information sciences data science data processing
- natural sciences computer and information sciences software software applications simulation software
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Coordinator
69132 Ecully
France
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