Adriana Hera

A System Identification Technique Using Pseudo-Wavelets

Sensitivity of regular wavelets to singularity has been used to detect a suddenly occurred structural damage and estimate its location in a large-scale structure. The usage of the approach is sometimes limited by a demand to the signal that the measurement data need to include the time period when the damage occurred. In this paper a concept of pseudo-wavelet is proposed based on shifting and scaling of conventional wavelets and a related pseudo-wavelet transform (PWT) is defined. A class of pseudo-wavelets is defined based on the frequency response function of the single degree of freedom mass-spring-dashpot system. A PWT-based system identification technique is developed to estimate the system parameters, mainly the natural frequencies and the damping ratios of the structure using vibration data. The approach can be applied for structural health monitoring. Change in system parameters using any two segments of response data may suggest occurrence of structural damages. The proposed approach is illustrated for single- and multiple-degree-of-freedom mass-spring-dashpot systems using simulated vibration response data. In all the case studies, the structural parameters are successfully estimated.

Evolutionary task assignment in distributed multi-agent networks with local interactions

In distributed multi-agent networks with local interactions, effective resource allocation to attain multiple tasks is a key system performance. In this paper, a dynamic evolutionary task assignment approach for such networks is introduced. According to this novel approach, every agent will allocate resources according to its individuallyassigned task prioritization as well as local interactions with neighboring agents. The effects of different parameters used in the approach are studied and tested by simulations. Relevant applications to robot networks are discussed. A comprehensive simulation-based study is provided to demonstrate the performance of the proposed approach.

System identification technique using truncated pseudowavelet transform

Pseudo-wavelets were proposed for system identification of linear systems to determine their natural frequencies and modal damping ratios. The approach provides excellent results for single-degree-of-freedom (SDOF) oscillators but significant errors might be observed for multiple-degree-of- freedom (MDOF) systems due to interference between different modes if the pseudo-wavelet transform (PWT) is directly applied. IN this paper a truncated pseudo-wavelet transform was employed to improve the accuracy for MDOF systems. A peak of the Fourier amplitude spectrum of the response was located and truncated in its neighborhood to isolate the peak. The frequency amplitude response function of a linear SDOF system was selected as the pseudo-wavelet. A truncated pseudo-wavelet transform was performed and its maximum value was located on a contour map of the PWT coefficients. The associated frequency and bandwidth of the MDOF system may be identified by the matching values of the scale and shift parameters. The methodology is illustrated for linear MDOF systems to identify their system parameters and good estimates were obtained. Noise effects were discussed. The approach can be applied for structural health monitoring. Change in system parameters using any two segments of response data may suggest occurrence of structural damages.

A Comparative Study of the Empirical Mode Decomposition and Wavelet Analysis on Their Application for Structural Health Monitoring

The paper presents a comparative study of the effectiveness of three novel damage detection techniques namely Continuous Wavelet Transform (CWT), Empirical Mode Decomposition (EMD) and Wavelet Packet Sifting (WPS). The health condition of a mechanical or civil engineering structure can be assessed by monitoring a change in natural frequencies and mode shapes. CWT method can be used to identify the instantaneous values of these modal parameters by the wavelet ridges. Using the EMD method, intrinsic mode functions (IMF) can be sifted from a vibration signal, whereas a newly-developed WPS technique can decompose a signal into its dominant mono-frequency components. Instantaneous modal information can be extracted by incorporating the EMD and WPS with the Hilbert Transform. These techniques are illustrated for simulated vibration data from a three-degree-of-freedom system subjected to (i) sudden damage and (ii) progressive damage. The aspects related to the implementation algorithms, sensitivity to damage type and the robustness issues in case of noisy data are discussed. In case of progressive damage, all methods performed well. WPS technique performed better in case of sudden damage whereas CWT demonstrated robustness in case of noisy data.Copyright

Marginal Instability and Intermittency in Stochastic Systems

Dynamic systems with lumped parameters which experience random temporal variations are considered. The variations may “smear” boundary between the system’s states which are dynamically stable and unstable in the classical sense. The system’s response within such a “twilight zone” of marginal instability is found to be of an intermittent nature, with alternating periods of zero or almost zero response and rare short outbreaks. As long as it may be impractical to preclude completely such outbreaks for a designed system, the corresponding response should be analyzed to evaluate the system’s reliability.

Short-Term Instability in Stochastic Aeroelasticity

Dynamic systems with lumped parameters are considered which interact with fluid flow with random temporal variations of speed. The variations may lead to “short-term” dynamic instability of a system — which is nominally stable in the classical sense — whereby occasional random excursions beyond neutral stability boundary result in rare short outbreaks in response. As long as it may be impractical to preclude completely such outbreaks for a designed system, subject to highly uncertain dynamic loads, the corresponding system’s response should be analyzed to evaluate its reliability. Linear models of the systems are studied to this end for the case of slow variations in the flow speed using parabolic approximation for the variations during the excursions together with Krylov-Bogoliubov (KB) averaging for the transient response. This results in a solution for probability density function (PDF) of the response in terms of PDF of the flow speed; the results may be of importance for predicting fatigue life. First-passage problem for the random response is also reduced to that for the flow speed. The analysis is used also to derive on-line identification procedure for the system from its observed intermittent response with set of rare outbreaks. Specific examples for analytical and numerical solutions for systems with random temporal variations of flow speed include: 1D and 2D galloping of elastically suspended rigid bodies in cross-flow; classical two-degrees-of-freedom flutter; bundles of heat exchanger tubes in cross-flow with potential for flutter-type instability.Copyright