Active interrogation of helicopter main rotor faults using trailing edge flap actuation

Over the past decade, the helicopter community has become increasingly interested in health monitoring. The rotor system, however, is not sufficiently covered in the current Health and Usage Monitoring Systems (HUMS). This dissertation describes the development and evaluation of a new approach for detecting helicopter rotor faults in which active trailing edge flaps are used to interrogate the system. This work is based on the presumption that trailing edge flaps would be installed for the primary purpose of vibration and/or noise control; health monitoring is a secondary use. Using this approach, the blade is excited by an interrogation signal, which is a low amplitude oscillation at a few discrete frequencies. The blade response is measured and the health of the system is determined using a frequency domain damage identification algorithm. Damage detection and location are achieved via the residual force vector. The residual force vector, coupled with an understanding of the system physics, also provides nature characterization. Quantification of damage extent is achieved via a frequency domain adaptation of the Asymmetric Minimum Rank Perturbation Theory. The active interrogation system is evaluated using an aeroelastic finite element model of the rotor system in hover, including an advanced unsteady aerodynamic model to predict the trailing edge flap loads. Realistic damage models, including distributed bending stiffness damage, torsional stiffness damage, control system stiffness damage, cracks and ballistic damage, are seeded in the rotor system model. Results demonstrate detection, location and quantification of extent of all of the faults tested. The effects of noise and modeling errors are discussed and mitigation techniques are developed. Additionally, a measurability study is included. Benefits of this work include both improved health monitoring for rotorcraft as well as insights into the application of structural damage detection algorithms to a complex system.