Affiliation:
1. Ph.D, School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA
2. Professor, School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA
Abstract
Accurate and online load monitoring of vital components located in the rotor system is important for not only inferring usage and estimating fatigue in those components but also for developing load alleviation/limiting control schemes. In the literature, on-board models for online
(i.e., real-time) estimation of rotor component loads using available in-flight aircraft fixed-frame measurements are developed using neural networks, a statistical-based approach, or a combination of both. These models are aircraft-specific, do not capture the higher harmonic dynamics of
the rotor system vibratory loads, and their synthesis requires obtaining a lot of data. To remedy these issues, this paper introduces a purely physics-based approach to online estimation of rotor system loads. The proposed approach can be applied to any rotary-wing vehicle, does not rely on
a large amount of data, and captures the higher harmonic dynamics of the rotor system vibratory loads. The developed model entitled LTI/LQE is synthesized using a linear time invariant (LTI) model of helicopter-coupled body-rotor-inflow dynamics and a linear quadratic estimator (LQE),
that is designed to correct the LTI model state response using fixed system measurements. The estimation fidelity of the LTI/LQE model is evaluated in simulation using a high-fidelity nonlinear model of a generic helicopter for online prediction of rotor blade pitch link loads arising
from vehicle maneuvers. Results obtained using the LTI/LQE model revealed an interesting finding. It was found that the N/rev (where N is the number of blades) fixed system load measurements have information that can be leveraged to make an inference about the N/rev
dynamic loads in the rotating system.
Publisher
AHS International dba Vertical Flight Society