Wavelet Analysis to Characterise Non-Linearities and Predict Limit Cycles of an Aeroelastic System

Lind, Rick; Snyder, Kyle; Brenner, Marty

doi:10.1006/mssp.2000.1346

Cited by 25 publications

(13 citation statements)

References 19 publications

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“…The parameter a is the scale, and is the temporal propagation parameter. [22] Three periods of the fluctuating oscillations of Figure 2a(a 1 ) are very prominent from the three rows of contours of Figure 2b(a 2 ) for B = 23 G. The dark and light colours present in the contours represent high and low coefficient values. So it can be concluded that a signal can be decomposed in the time-scale plane or time-frequency plane using above scale-frequency relation.…”

Section: Cwt-based Analysis Of the Fluctuationsmentioning

confidence: 87%

“…The scale shift with time signifies the presence of non-linearity in the system. [22] Three periods of the fluctuating oscillations of Figure 2a(a 1 ) are very prominent from the three rows of contours of Figure 2b(a 2 ) for B = 23 G. The dark and light colours present in the contours represent high and low coefficient values. Further, it is seen that three contour rows merge into two rows, with high coefficients values representing the observed four peaks, as shown in Figure 2b(b 2 ).…”

Section: Cwt-based Analysis Of the Fluctuationsmentioning

confidence: 87%

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Characteristic behaviour of plasma fluctuations inside a plasma bubble in presence of a magnetic field due to the formation of a potential well

Megalingam

Sarma

2019

Contributions to Plasma Physics

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Experiments were carried out to observe the effect of a magnetic field and grid biasing voltage in presence of a plasma bubble in a magnetized, filamentary discharge plasma system. A spherical mesh grid of 80% optical transparency was negatively biased and introduced into the plasma for creating a plasma bubble. Diagnostics via an electrical Langmuir probe and a hot emissive probe were extensively used for scanning the plasma bubble. Plasma floating potential fluctuations were measured at three different positions of the plasma bubble. The instability in the pattern showed the dynamic transition from periodic to chaotic for increasing magnetic fields. Time scale analysis using continuous wavelet transform was carried out to identify the presence of non-linearity from the contour plots. The mechanisms of the low-frequency instabilities along with the transition to chaos could be qualitatively explained. Non-linear techniques such as fast Fourier transform, phase space plot, and recurrence plot were used to explore the dynamics of the system appearing during plasma fluctuations. In order to demonstrate the observed chaotic phenomena in this study, characteristics of chaos such as the Lyapunov exponent were obtained from experimental time series data. The experimentally observed potential structure is confirmed with numerical analysis based on fluid hydrodynamics. KEYWORDS chaos, floating potential fluctuations, plasma bubble, potential well, spherical mesh grid 1

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Section: Cwt-based Analysis Of the Fluctuationsmentioning

confidence: 87%

Section: Cwt-based Analysis Of the Fluctuationsmentioning

confidence: 87%

Characteristic behaviour of plasma fluctuations inside a plasma bubble in presence of a magnetic field due to the formation of a potential well

Megalingam

Sarma

2019

Contributions to Plasma Physics

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“…An accurate wavelet transform is achieved by using a basis function that is the same as the input function. 8,10 The wavelet transform is:…”

Section: Wave Attenuationmentioning

confidence: 99%

Development of an integrated software solution for piezoelectric active-sensing in structural health monitoring

Jacobs

Park

Farrar

2007

Sensor Systems and Networks: Phenomena, Technology, and Applications for NDE and Health Monitoring 2007

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In this study, a novel approach of integrating data interrogation algorithms of active sensing methods for structural health monitoring (SHM) applications, including Lamb wave propagation, impedance method, and sensor-diagnostics, is presented. Contrary to most active-sensing SHM techniques, which utilize only a single signal processing method for damage identification, a suite of signal processing algorithms are employed and grouped into one package to improve the damage detection capability. A MatLab-based user interface called H.O.P.S. (Health Of Plate Structures) was created, which allows the analyst to configure the data acquisition system and display the results from each damage identification algorithm for side-by-side comparison. This side-by-side comparison of results simplifies the task of identifying the relative effectiveness and sensitivity of each algorithm. By grouping a suite of algorithms into one package, this study contributes to and enhances the visibility and interpretation of the active-sensing methods related to damage identification in a structure.

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“…Subsequently, in the wavelet toolbox a DB3 wavelet, which was selected due to its similarity to the input signal, was used to decompose the data into its frequency components. By plotting the magnitude of the wavelet coefficient at the peak driving frequency, the energy remaining from the inputted signal could be compared [22]. This procedure was carried out for two of each specimen type at the optimal driving frequency of 15 kHz.…”

Section: Experimental Procedures Thin Coupon Testingmentioning

confidence: 99%

Structural health monitoring in composite materials using frequency response methods

et al. 2001

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1Cost-effective and reliable damage detection is critical for the utilization of composite materials. This paper presents part of an experimental and analytical survey of candidate m ethods for in-situ damage detection of composite materials. Experimental results are presented for the application of Lamb wave techniques to quasi-isotropic graphite/epoxy thin coupons and sandwich beams containing representative damage modes, including delamination, transverse ply cracks and through-holes. Optimization experiments provided a procedure capable of easily and accurately determining the presence of damage by monitoring the transmitted waves with piezoceramic sensors (PZT). Lamb wave techniques have been proven to provide more information about damage type, severity and location than previously tested methods, and may prove suitable for structural health monitoring applications since they travel long distances and can be applied with conformable piezoelectric actuators and sensors that require little power.

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Wavelet Analysis to Characterise Non-Linearities and Predict Limit Cycles of an Aeroelastic System

Cited by 25 publications

References 19 publications

Characteristic behaviour of plasma fluctuations inside a plasma bubble in presence of a magnetic field due to the formation of a potential well

Characteristic behaviour of plasma fluctuations inside a plasma bubble in presence of a magnetic field due to the formation of a potential well

Development of an integrated software solution for piezoelectric active-sensing in structural health monitoring

Structural health monitoring in composite materials using frequency response methods

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