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Showing 4 results for Hilbert Transform
Abolfazl Mokhtari, Mehdi Sabzehparvar,
Volume 17, Issue 1 (3-2017)
Abstract
Identification of spin maneuver flight characteristics focused in this paper. To analyses an airplane flying quality, identification of the dynamic modes and extracting their characteristics is essential for assessment of the airplane dynamic stability and response-to-control. The paper aims to present a new method for identification of some flight modes, including natural and nonstandard modes, and extraction of their characteristics the same as instantaneous frequency and instantaneous damping ratio, directly from measurements of flight parameters in the time domain in nonlinear flight regime. Firstly, a conceptual method based on the Empirical Mode Decomposition (EMD) algorithm is proposed. The key issue of the EMD algorithm is to represent the signal as the summation of the pattern and detail parts, besides separating them from each other. by utilize the Empirical Mode Decomposition (EMD) capabilities in real-time, a local-online algorithm is introduced which estimates the signal intrinsic mode functions Secondly, by applying Hilbert- Huang transformation to IMFs obtained by EMD algorithm the flight characteristics the same as instantaneous frequency and instantaneous damping ratio for flight mode has been estimated from spin measured flight data. The results indicate the appropriate performance of the identification method in nonlinear flight regime.
Farzaneh Sabbaghian Bidgoli, Javad Poshtan,
Volume 17, Issue 5 (7-2017)
Abstract
Signal processing has a key role in signal based fault diagnosis in rotating machinery for finding beneficial discriminating features. Task of Signal processing is conversion of the raw data into beneficial features to facilitate the diagnostic operations. the features should be robust regarding noise and working condition of the machine and simultaneously sensitive to the machine defects. Therefore, assignment of more efficient analyzing techniques in order to achieve more beneficial features of the signal and faster and more accurate fault detection is taken into consideration by researchers. In order to finding such features, the current research applies at first wavelet packet denoising and then applies wavelet packet based Hilbert transform as well as improved Hilbert-Huang transform separately to decompose vibration signal into narrow frequency bands in order to extracting instantaneous frequencies. The findings show that the wavelet packet based Hilbert transform generates better results in comparison to the improved Hilbert-Huang transform in detecting frequencies of the broken rotor bar fault.
M. Rezaee , V. Shaterian_alghalandis,
Volume 19, Issue 9 (9-2019)
Abstract
The equations of nonlinear motion of clamped-hinged beam with an open crack were extracted and through solving them, the internal resonance in the cracked beam was studied. To this end, the crack was modeled as a torsional spring and the cracked beam was considered as two beam segments connected by a torsional spring. The equations of motion of the cracked beam were extracted considering the geometrical nonlinearity. Then, using the Galerkin’s method, these equations were changed to a set of nonlinear differential equations for vibration modes which were solved by the perturbation method. Since the mechanical energy of the beam in each mode depends on the instantaneous amplitude of vibration of the beam at the corresponding mode, so to analyze the influence of the crack on the energy exchange between the modes, the instantaneous amplitudes of the vibration modes were obtained. The results show that in the cracked beam the magnitude of the energy exchanged between the modes is less and the frequency is more than that in the intact beam. Also, by increasing the crack depth the frequency of energy exchange between the modes increases. The Vibration response obtained for the cracked beam with various amounts of the damping ratios shows that the frequency and the amplitude of energy exchange between the modes are independent of the system damping. To validate the results by the perturbation method, the equations of motions are also solved by a numerical method and the obtained results are in agreement with the results of the analytical method.
Volume 21, Issue 6 (12-2021)
Abstract
Occurrence of the nonlinear behavior can be a sign of changes in structural parameters and the presence of damage in systems. This paper presents a method for detecting and quantifying of nonlinearity, as an indication of damage, using the indicators that are extracted from the frequency response functions (FRFs) and Hilbert transform of FRFs, for steel moment frame structural systems. Using time history analysis under selected harmonic ground motions, the results of FRFs for the studied 4-story system are illustrated and discussed.
Nonlinear behavior is a result of formation plastic hinges under earthquake loading. FRFs and Hilbert transform of FRFs are extracted from both the linear and nonlinear behavior of 4, 8, and 12-stories steel moment frames under fifteen different earthquake records with different characteristics in their time histories. Some near and far field well-known earthquakes records have been selected for the present study as the ground motions input in time history analysis. Different levels of nonlinearity are determined based on the maximum rotation of hinges in column members of structures equal to 2θy, 4θy and 6θy, in which θy is yield limit rotation. The indicators of the studied systems are calculated and evaluated for linear and different levels of nonlinearity based on the mathematical power of changes for FRFs and Hilbert transform of FRFs. The presented indicators are extracted based on the frequency response functions (FRFs) and Hilbert transform of FRFs for the responses of absolute acceleration and relative displacement of stories. The indicators are calculated at the location of acceleration sensors (accelerometer) in four levels of the structural systems, while the formation of plastic hinges in the columns of the structures will occur only at the level of the distance between the adjacent sensors.It is shown that the proposed method and calculated indicators have enough accuracy and sensitivity in detecting the “existence”, “location” and “extent” of damage.
