Browse Topic: Center of gravity (CG)
This study investigates the use of machine learning (ML) models to estimate the gross weight (GW), the longitudinal position of the center of gravity (CGx), and 1/rev cyclic flapping angles (Δ1c and Δ1s) of a compound helicopter with three redundant controls - main rotor RPM, collective propeller thrust, and stabilator angle. Neural Network (NN), Gaussian Process for Regression (GPR), and Support Vector Machine (SVM) algorithms are employed to develop estimation models using supervised training. The airspeed, redundant controls, main rotor controls, aircraft attitudes, and main rotor torque are selected as input variables (predictors) to the models due to their accessibility through the aircraft Health and Usage Monitoring System (HUMS). The dataset is split into low-speed and high-speed regimes to compare the prediction accuracy and training cost of separate regime models against a combined full-regime model. Separate airspeed regime GPR models showed superior performance in GW
Weight and balance activities are widely recognized and understood as important steps in the operation and maintenance of an aircraft to ensure safe and efficient flight. From the pilot's perspective, the operational limits and maneuverability of the aircraft are directly linked to the weight and balance of the aircraft. From a structural perspective, fatigue damage can vary significantly with center of gravity position and gross weight. In-flight center of gravity and gross weight estimation has been pursued for many years with varying success. One of the major challenges is the lack of data to verify an estimation model, since these parameters cannot be easily measured using sensors in flight. This paper reviews in detail the requirement and challenges of accurately monitoring center of gravity and gross weight. In addition, a survey of published work on the estimation of these values is provided. These efforts are divided into four categories: helicopter dynamic models, performance
This SAE Aerospace Standard (AS) defines the minimum performance requirements and test parameters for air cargo unit load devices requiring approval of airworthiness for installation in an approved aircraft cargo compartment and restraint system that complies with the cargo restraint requirements of Title 14 CFR Part 25, except for the 9.0-g forward ultimate inertia force of § 25.561 (b)(3)(ii).
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