Analysis of Real-Time Rotor Stall Detection Methods

Main rotor stall in rotorcraft is characterized by the loss of lift, increased vibrations and significant structural loads on the main rotor control system. The primary focus of the current study is the analysis of new and previously developed methods for real-time detection of rotor stall. The discussion related to rotor stall specifically pertains to an increase in control system fixed pitch-link peak-to-peak loads (FPLPPL). Data from the UH-60A Airloads Project obtained through the TRENDS database is used in this study. An existing method based on the Equivalent Retreating Indicated Tip Speed (ERITS) parameter consists of setting a limit on ERITS which corresponds to high FPLPPL. This method is evaluated using the UH-60A data, and is shown to be overly conservative for rotor stall detection. A new method requires that a rotor stall limit based on ERITS be modified with respect to additional parameters. It is observed that air density affects FPLPPL to a higher degree than predicted by ERITS. Taking into account this additional affect of air density may increase the robustness of ERITS as a real-time rotor stall detection parameter. Unlike the method that uses limiting value of a certain parameter as an indication of rotor stall, rotor stall could also be detected with the use of limit detection algorithms if FPLPPL models are available such that the limit may directly be set on FPLPPL. Current study examines this approach by modeling FPLPPL with the use of neural networks and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), with the later showing promise by giving some reasonable results.