Machine Learning Application on Aircraft Fatigue Stress Predictions
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
AI and ML algorithms can be used to predict when maintenance is needed on aircraft components.
“AI and ML algorithms can be used to predict when maintenance is needed on aircraft components.”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [116]
Cited by
Sorted by citations
Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Soori, M., Arezoo, B., & Dastres, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.001 · Cited by 1,131 · see citing works
- Authors
- O’Higgins, E., Graham, K., Daverschot, D., & Baris, J.
- Affiliations
- Airbus (Germany) (DE)
- Airbus (United Kingdom) (GB)
- Airbus (France) (FR)
- Corresponding author
- Daverschot, Derk
- Venue
- Lecture Notes in Mechanical Engineering
- Publisher
- Springer International Publishing
- Published
- 2019-07-03
- Pages
- 1031-1042
- ISSN
- 2195-4356 (ISSN-L)
- 2195-4364
- OpenAlex
- W2953427604
- Cited by
- 6
- References
- 0
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 1 · 2021: 1 · 2020: 1
- FWCI
- 2.40
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in mechanical engineering (publishedVersion)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Mechanics of Materials › Fatigue and fracture mechanics
- Physical Sciences › Engineering › Control and Systems Engineering › Aerospace Engineering and Applications
- Keywords
- aircraft fatigue, machine learning, flight data, aircraft maintenance, civil aviation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
