The DOI matches its Crossref record; 154 of the 154 references it cites were found in a registry or an index.
Model-based fault diagnosis for aerospace systems: a survey
Abstract
This survey of model-based fault diagnosis focuses on those methods that are applicable to aerospace systems. To highlight the characteristics of aerospace models, generic non-linear dynamical modelling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented. An extensive bibliographical review supports a description of the key points of fault detection methods that rely on analytical redundancy. The approaches that best suit the constraints of the field are emphasized and recommendations for future developments in in-flight fault diagnosis are provided.
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Cites
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
Fuzzy identification of systems and its applications to modeling and control
Takagi, T., & Sugeno, M. (1985) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1985.6313399 · Cited by 19,592
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
Statistical pattern recognition: a review
Jain, A. K., Duin, P. W., & Mao, J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.824819 · Cited by 6,767
Isidori, A. (1995) · Communications and Control Engineering · doi:10.1007/978-1-84628-615-5 · Cited by 6,755
Unscented Filtering and Nonlinear Estimation
Julier, S. J., & Uhlmann, J. K. (2004) · Proceedings of the IEEE · doi:10.1109/jproc.2003.823141 · Cited by 6,588
An overview of statistical learning theory
Vapnik, V. N. (1999) · IEEE Transactions on Neural Networks · doi:10.1109/72.788640 · Cited by 6,266
Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy
Frank, P. M. (1990) · Automatica · doi:10.1016/0005-1098(90)90018-d · Cited by 3,545
Detection of Abrupt Changes: Theory and Application
Riedel, K. S. (1994) · Technometrics · doi:10.1080/00401706.1994.10485821 · Cited by 3,518
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Ruff, L., Kauffmann, J. R., Vandermeulen, R. A., Montavon, G., Samek, W., Kloft, M., Dietterich, T. G., & Muller, K.-R. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2021.3052449 · Cited by 914
Speed/position sensor fault tolerant control in adjustable speed drives – A review
Bourogaoui, M., Sethom, H. B. A., & Belkhodja, I. S. (2016) · ISA Transactions · doi:10.1016/j.isatra.2016.05.003 · Cited by 67
GP-ARX-Based Structural Damage Detection and Localization under Varying Environmental Conditions
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Metadata
- Authors
- Marzat, J., Piet-Lahanier, H., Damongeot, F., & Walter, E.
- Venue
- Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
- Publisher
- SAGE Publications
- Published
- 2012-01-06
- Volume
- 226
- Issue
- 10
- Pages
- 1329-1360
- ISSN
- 0954-4100 (ISSN-L)
- 2041-3025
- OpenAlex
- W2024094473
- Cited by
- 278
- References
- 154
- FWCI
- 25.50
- Type
- journal article
- Language
- en
- Open access
- closed
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- Marzat, J., Piet-Lahanier, H., Damongeot, F., & Walter, E. (2012). Model-based fault diagnosis for aerospace systems: a survey. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. https://doi.org/10.1177/0954410011421717
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
