55 research outputs found
Probability density evolution for time-varying reliability assessment of wing structures
Get PDFReliability evaluation is a key factor in serviceability and safety analysis of air vehicles. Structural health monitoring methods have grown to a degree of maturity in many industries. However, there is a challenging interest to tie in SHM with reliability assessment. In this respect, consideration of stochastic structural dynamics with SHM data and random loadings opens a new chapter in failure prevention. The current study focuses on the stochastic behavior of structures as a way to relate SHM data with reliability. In this respect, uncertain factors such as atmospheric turbulence, structural parameters, and sensor outputs are considered in the process of reliability assessment. Firstly, an experimental evaluation is conducted using a simple cantilevered beam. Subsequently, system identification is weaved in with a probability density evolution equation for calculating the reliability of a wing structural component. Numerical simulations demonstrate that structural reliability of a typical WSC can be effectively evaluated. The proposed scheme paves the way for new SHM research topics such as online life prediction and reliability based failure prevention
Unscented Kalman Filtering for Single Camera Based Motion and Shape Estimation
Get PDFAccurate estimation of the motion and shape of a moving object is a challenging task due to great variety of noises present from sources such as electronic components and the influence of the external environment, etc. To alleviate the noise, the filtering/estimation approach can be used to reduce it in streaming video to obtain better estimation accuracy in feature points on the moving objects. To deal with the filtering problem in the appropriate nonlinear system, the extended Kalman filter (EKF), which neglects higher-order derivatives in the linearization process, has been very popular. The unscented Kalman filter (UKF), which uses a deterministic sampling approach to capture the mean and covariance estimates with a minimal set of sample points, is able to achieve at least the second order accuracy without Jacobians’ computation involved. In this paper, the UKF is applied to the rigid body motion and shape dynamics to estimate feature points on moving objects. The performance evaluation is carried out through the numerical study. The results show that UKF demonstrates substantial improvement in accuracy estimation for implementing the estimation of motion and planar surface parameters of a single camera
Analysis of two-stage endo-atmospheric separation using statistical methods
No full textIn this paper, selection and analysis of an atmospheric two stage separation system is di-
scussed. The main purpose of this system is to test a supersonic parachute projectile, where
a stage separation occurs after the burn out. Subsequently, the parachute is ejected from the
payload after a minimum elapsed time. The separation times, for the supersonic parachute
ejection, as well as the time needed for a safe clearing distance between the two stages are
two critical issues in the separation process. In this respect, the knowledge of the relative
position between the two stages is necessary to assure a safe distance and in order to ad-
just the required system parameters. In addition, as the nature of the parameters involved
in the separation process is not deterministic, it would be useful to utilize the concept of
random variables in the dynamic modeling of the separation process. In this paper, the mo-
deling and simulation of the separation process is initially performed and partially verified.
Subsequently, an approximate statistical method is utilized to acquire some probabilistic in-
formation about the relative distances at the two critical times. According to the simulation
results, the relative distance between the two stages falls in a safe region. Finally, Monte
Carlo simulation is also performed for comparison and verification of the statistical results
that indicated a small and acceptable deviation between the two approaches. Thus, it can
be concluded that the simpler approximate statistical approach is also valid for uncertainty
analysis and can provide valuable knowledge needed in the preliminary design phase of the
separation system
EXPERIMENTAL INVESTIGATION OF VERTICAL CG POSITION CHANGES ON QUADROTOR'S PERFORMANCE VIA FREQUENCY-DOMAIN IDENTIFICATION TECHNIQUES
No full textPayload placement on quad-rotor (QR) is a subject of considerable importance
during its flight and maneuvering phases. In this sense, any changes in the
payload position, especially along the vertical axis, could significantly affect the QR center of gravity (CG) position and, in turn, its performance, dramatically. The current experimental study investigates the effect of payload vertical positioning on the performance and stability characteristics of a typical QR. The QR is test flown for more than eighty times with different payload positions, whose recorded flight data (RFD) are filtered using extended Kalman filter and subsequently utilized for QR frequency domain analysis. The RFDs are used to identify the QR longitudinal and lateral modes. In addition, the mode changes trend against the center of gravity location has led to the determination of the CG position at which instability occurs. The experimental results show that as the QR CG moves up along its vertical axis, its dynamics modes move towards the origin on the real axis taking the QR closer to borderline dynamic instability. Moreover, the damping behavior of the longitudinal and lateral modes with respect to CG has been extracted that in turn can lead to CG based techniques for QR damping control. In addition, in order to generalize the present results to be useful for other QRs, the QR parameters have been nondimensionalized, and an effective nondimensional
parameter through which results can be extended to other QRs is determined. The newly introduced nondimensional parameter is used against another set of data, extracted from a different QR for verification and comparative purposes.
Finally, to account for uncertainties and stochastic noise in the RFD measures,
each experimental stage is repeated four times; and the results of the mean
behavior are reported, too
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