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gas turbine sensor data, if available, will be utilized to validate the developed digital twin in order to estimate non-measurable health parameters of major gas path components, including compressors
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based on both visual and tactile information. The candidate will be responsible for developing detailed simulation models of both robots, sensors, and components to be assembled. In addition
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monitoring disturbances from both satellites and ground-based sensors. The latter is expected to contribute to the further development of the pylidar repository. This PhD project will be promoted by prof. Kim
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