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Predictive Health Management Services

RESOURCES

Resources including theory, algorithms and implementing codes are available for selected real-world problems.
They are made in two platforms:
livescript in MATLAB and jupyter notebook in Python so that the developer can learn and practice, or customize by themselves with less intervention. By providing these resources and supervising how to apply or customize in their developments, their challenges can be resolved. Eventually, they are capable to continue expanding applications by their own ability.

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Signal processing and feature engineering for gears and bearings

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Model based prognostics of electric motor

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Maintenance scheduling of turbine blades by field inspection data

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Fault diagnosis of rotating machinery: ISO standard and PHM approach

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Prognostics demonstration via cooling fan bearings

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Fault diagnosis of planetary gearbox using ANN

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Prognostics of aircraft engine degradation by deep learning algorithms

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Fault diagnosis of robot by systems approach

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SOC/SOH of Li-ion batteries by model-based approach

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Room 306, Research building, Korea Aerospace University 76, Hanggongdaehang-ro, Deogyang-gu, Goyang-city Gyeonggi-do, 412-791, KOREA

E-Mail

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