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Model-Based Tool for the Automatic Validation of Rotorcraft Regime Recognition Algorithms

Description:

Due to practical, technical, and logistical limitations associated with achieving direct loads monitoring for every fatigue sensitive component on an aircraft, the Navy is relying on flight maneuver recognition to provide usage data across a fleet of aircraft in order to refine fatigue life calculations. However, current RR tools have trouble accurately and precisely recognizing flight regimes. These existing RR tools are based off of empirical or rule-based systems. They are derived from actual flight tests, which makes them vehicle-, load out-, weather-, and pilot- dependent. In addition, their development is costly and time-consuming, since each air vehicle system and maneuver type must be individually flight tested and verified against the RR code. As a result, RR codes do not have the accuracy required for fleet usage in HUMS. It is therefore important to verify that future RR codes for use in rotorcraft applications correctly represent as many flight conditions as possible. In order to ensure the fitness of RR tools, per ADS-79D-HDBK, new RR codes require an independent verification and validation (IV&V) effort. Current verification of RR tools is performed by manually comparing the input of physical flight test data to the RR tool’s output. This process is often labor intensive and error prone. Without an automatic and standardized way of comparing codes, selecting the ‘best’ code can be a subjective process. Automating the validation process would not only expedite the process considerably, it would also allow for the quantitative comparison of RR codes. The use of physics-based simulation to recreate a set of validation test flights can reduce flight test costs and streamline the RR validation process. Despite their present shortcomings, an effective RR code would be invaluable for tracking fatigue damage to parts through the accurate detection and measurement of flight regimes experienced by a rotorcraft. RR schemes have many other possible benefits to rotorcraft operations, including updating service usage spectrums, as well as component damage tracking. These improvements could drastically reduce unscheduled maintenance and downtime. An automated validation tool which leverages physics-based simulation that will provide validation of RR codes, be fast, simple to use, and provide feedback on the accuracy of the RR tool’s identification of regimes is sought. This validation tool should be able to identify codes that capture at least 97 percent of maneuvers, or sufficient maneuvers in order to not under-predict the fatigue damage fraction of life-limited parts by more than 0.5 percent. The tool should alert users to inconsistencies between the outputs of the RR code and the performed maneuvers. The validation tool should use scripted HUMS flights on instrumented aircraft. PHASE I: Design and develop a model/concept for a physics-based tool for the automatic validation of rotorcraft RR software. Demonstrate the feasibility of the approach. PHASE II: Provide practical implementation of the methodology developed in Phase I and incorporate it into a prototype tool which includes a suitable graphical user interface (GUI). The prototype tool must be able to analyze RR code for a specific rotorcraft platform and mission load out. Improve the accuracy, robustness, and speed of the tool to help spur the development of more robust RR codes. Demonstrate the developed prototype tool with scripted HUMS flights on instrumented aircraft and eventually streaming data from a flight simulator. PHASE III: Transition and integrate the validation tool into a software package for use with RR code outputs obtained from actual flight data from onboard a Navy/Marine helicopter. Perform field testing to demonstrate the robustness of the system when dealing with real flight data. Expand the tool to be able to analyze code for actual production platforms (e.g. H-53E/K, H-60R/S, and H-1) and different load outs for each required platform, as well as for use in commercial establishments. Evaluate qualification test results and provide procurement specification for transition to an actual production platform.
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