Error analysis and assessment of unsteady forces acting on a flapping wing micro air vehicle: free flight versus wind-tunnel experimental methods

Abstract

An accurate knowledge of the unsteady aerodynamic forces acting on a bio-inspired, flapping-wing micro air vehicle (FWMAV) is crucial in the design development and optimization cycle. Two different types of experimental approaches are often used: determination of forces from position data obtained from external optical tracking during free flight, or direct measurements of forces by attaching the FWMAV to a force transducer in a wind-tunnel. This study compares the quality of the forces obtained from both methods as applied to a 17.4 gram FWMAV capable of controlled flight. A comprehensive analysis of various error sources is performed. The effects of different factors, e.g., measurement errors, error propagation, numerical differentiation, filtering frequency selection, and structural eigenmode interference, are assessed. For the forces obtained from free flight experiments it is shown that a data acquisition frequency below 200 Hz and an accuracy in the position measurements lower than ± 0.2 mm may considerably hinder determination of the unsteady forces. In general, the force component parallel to the fuselage determined by the two methods compares well for identical flight conditions; however, a significant difference was observed for the forces along the stroke plane of the wings. This was found to originate from the restrictions applied by the clamp to the dynamic oscillations observed in free flight and from the structural resonance of the clamped FWMAV structure, which generates loads that cannot be distinguished from the external forces. Furthermore, the clamping position was found to have a pronounced influence on the eigenmodes of the structure, and this effect should be taken into account for accurate force measurements.

Onboard/Offboard Sensor Fusion for High-Fidelity Flapping-Wing Robot Flight Data

“…approximately 70Hz. As a comparison, previous work on a similar test platform showed that 200Hz-sampled optical tracking data only resulted in reliable information up to 32Hz in the accelerations obtained from double differentiation [16]. The high resolution attained is relevant not only for the forces and moments, but also for the states themselves, and especially the body velocities, which cannot be estimated as effectively by either IMU or optical tracking alone.…”

“…While sampling up to 1024Hz is possible, internal low-pass filtering at 256Hz implies that such sampling frequencies would not yield accurate additional information, and it was also found that at higher rates, significant numbers of frames were being lost, presumably as a result of CPU overloading. Moreover, previous work with similar ornithopters showed that very high-frequency content becomes increasingly difficult to distinguish from noise [16].…”

“…here 120Hz; (ii) presence of glitches and occasionally untracked or misattributed markers, e.g. due to light disturbance; and (iii) exclusive measurement of position and attitude, meaning rates must be computed via numerical differentiation, which amplifies the noise by a factor of 1 (∆t) n , with n the order of differentiation and ∆t the time step [16]. The low acquisition frequency, in particular, means that even for the relatively low flapping frequency of the studied ornithopter (10-15Hz), only approximately 8-12 measurements are made during each flap cycle.…”

“…Additionally, it is still considerably difficult to obtain realistic experimental data, particularly in free flight and in different flight regimes. Studies have found discrepancies between free-flight and wind tunnel data [16,17,18], suggesting that wind tunnel measurements approximate free-flight data only for specific clamping positions and in some flight conditions, so that realistic insight for free flight ideally should be obtained in free-flight conditions.…”

“…Additionally, linear and angular velocities and accelerations have to be computed via numerical differentiation, which introduces considerable noise [16]. It can also be expected that as platforms become increasingly small, attitude data obtained from tracking alone will decrease in quality due to the limited resolution.…”