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Abstract
This paper presents the results from several load estimation methods developed at the National Research Council Canada (NRC) which enable the estimation of helicopter loads and tracking load exceedances and fatigue damage for a targeted component using computational intelligence techniques. The approach relies only on flight state and control system (FSCS) parameters, such as those recorded by a flight data recorder (FDR), and can also be applied to legacy aircraft or to those aircraft not equipped with HUMS. The methodologies adapt to the input data available so are not constrained to one particular system or platform, and enable the estimation of loads through the duration of a manoeuvre instead of assuming a constant load for an entire manoeuvre. So far, the three methods have been tested on data obtained from two different helicopter platforms, the S-70A-9 Australian Black Hawk and the CH-146 Griffon (Bell 412). Significant improvements are made over previous results presented for the S-70A-9 Black Hawk using the NRC developed Signal Approximation Method (SAM) while using uniquely FSCS parameters obtained from a FDR to obtain full manouevre dynamic load signals in time. Furthermore, the application of the technology to a different platform and different original equipment manufacturer (OEM), namely the CH-146 Griffon, demonstrates the possibility of applying this methodology and its adaptability across different platforms.

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  Improved Load Estimation And Fatigue Life Tracking Demonstrated On Multiple Platforms Using The Signal Approximation Method

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