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Expanded Fatigue Damage and Load Time Signal Estimation for Dynamic Helicopter Components Using Computational Intelligence Techniques

Catherine Cheung, Bruno Rocha, Julio Valdes, Mark Kotwicz-Herniczek, Anton Stefani, National Research Council Canada

May 20, 2014

https://doi.org/10.4050/F-0070-2014-9542

Abstract:
Load signal prediction and fatigue damage accumulation estimation results are presented for a wide range of flight conditions from the S-70A-9 Black Hawk flight loads survey performed in 2000. Results from twelve manoeuvres were included in this study, ranging from very specific steady state and transient manoeuvres to more general manoeuvres with varying speed, direction, and aircraft orientations. The load time signal predictions were obtained following a simplified methodology and then the resulting fatigue damage accumulation was calculated for each manoeuvre. These estimates were generated using developed computational models, consisting of a variety of computational intelligence techniques and statistical methods, coupled with online Rainflow counting, the material specific S-N curve, and Palmgren-Miner's linear damage rule.


Expanded Fatigue Damage and Load Time Signal Estimation for Dynamic Helicopter Components Using Computational Intelligence Techniques

  • Presented at Forum 70
  • 10 pages
  • SKU # : F-0070-2014-9542
  • HUMS-CBM

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Expanded Fatigue Damage and Load Time Signal Estimation for Dynamic Helicopter Components Using Computational Intelligence Techniques

Authors / Details:
Catherine Cheung, Bruno Rocha, Julio Valdes, Mark Kotwicz-Herniczek, Anton Stefani, National Research Council Canada