SR-30 turbojet engine real-time sensor health monitoring using neural networks, and Bayesian belief networks

Cameron Nott; Semih Ölçmen; Charles L. Karr; Luis C. Trevino

doi:10.1007/s10489-006-0017-z

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SR-30 turbojet engine real-time sensor health monitoring using neural networks, and Bayesian belief networks

Cameron Nott Semih Ölçmen Charles L. Karr Luis C. Trevino

Year: 2006 Journal: Applied Intelligence Vol: 26 (3)Pages: 251-265 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-006-0017-z

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Keywords:

Turbojet Computer science Artificial neural network Bayesian network Artificial intelligence Noise (video) Bayesian probability Machine learning Real-time computing Engineering

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Topics

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Advanced Sensor Technologies Research

Physical Sciences → Engineering → Biomedical Engineering

Scientific Measurement and Uncertainty Evaluation

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

SR-30 turbojet engine real-time sensor health monitoring using neural networks, and Bayesian belief networks

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