Key Engineering Materials Vols. 569-570

Abstract: The use of cointegration has been proposed recently as a potentially powerful means of removing confounding influences from structural health monitoring (SHM) data. On the other hand the Empirical Mode Decomposition method is a recent multi-scale decomposition technique with the ability to decompose a signal into meaningful signal components. In this paper the EMD method will be used to highlight the dominant time-scales that have been affected by varying environmental and operational conditions and the time-scales that are related to damage. Then cointegration will be used to remove the nonstationary effects not associated with damage at the time-scales of interest in the data. The final step of the damage detection approach proposed, will be the use of two different amplitude-frequency separation methods, the Hilbert Transform and the more recent Teager Kaiser energy operator approach in order to compare the merits of both, concerning the estimation of the instantaneous characteristics of the signals.

Abstract: The translational restraints associated to pin and rocker bearings are typically idealized in the form of fixed and free conditions. However, elastomeric bearings need to be represented with springs to reasonably predict the time- and frequency-domain response of bridges under traffic-induced vibrations. Therefore, changes in the response of these bearings are common as a result of aging, deterioration, variation in loading levels and/or environmental changes. The latter makes difficult to discern if changes in the frequency content of the structural response to ambient vibration are due to changes in temperature, changes in normal operational loads or the occurrence of damage. In this paper, the bridge is idealized by a beam model supported on a hysteretic translational sprung support. The purpose is twofold: (a) to gather a better understanding of the variations of the bridge response with bearing performance; and (b) to be able to quickly identify an anomaly in the bearing. Empirical Mode Decomposition and the Hilbert-Huang Transform are employed to capture changes in the bearing stiffness from the bridge response.

Abstract: It is a common practice in the automotive industry to expose products to accelerated vibration tests, that simulate the load, predicted to occur during the products service time. To avoid long testing times, higher amplitudes are used. Usually such tests come late in the development process, and can result in unexpected costs. A common tool for predicting time-to-failure or expected fatigue-life of the product is the time-domain method, using the rainflow counting algorithm and the Palmgren-Miner summation method. However, if one chooses to apply this method inside a FEM environment on a large amount of nodes with different time histories dependent on the structure excitation, the time-domain method becomes computationally complex. This has led to more effective methods, that estimate the time-to-failure in frequency-domain but are less accurate, compared to the time-domain approach. In this research, a group of such methods is presented and compared using real signals, namely: Tovo-Benasciutti, Wirsching-Light, Petrucci-Zuccarello, empirical α_0.75, Dirlik and Gao-Moan method. Separately, only some of those methods were already compared side by side. Usually the comparison was made on simulated random signals, while this research compares them based on a real signal, collected by measuring different groups of spectra (e.g. typical vibration test profiles, different background noise levels, spectral width, number of modes etc.). In existing studies, Dirlik is usually identified as most accurate but in this research, conclusions show, that the Tovo-Benasciutti and Zhao-Baker methods can be more accurate than the Dirlik method and should therefore also be considered for vibration fatigue analysis.

Abstract: This paper presents an application of Lamb-wave-based damage detection under varying temperature conditions. The method used is based on the cointegration technique and wavelet analysis that are partially built on the analysis of non-stationary behaviour and multi-resolution decomposition of time series, respectively. Instead of directly using Lamb wave data for damage detection, two approaches are used: (1) analysis of cointegrating residuals obtained from the cointegration process of Lamb wave responses and (2) analysis of stationary characteristics of the multi-level wavelet decomposed cointegrating residuals. These two approaches are tested on undamaged and damaged aluminium plates exposed to temperature variations. The experimental results show that the method can isolate damage-sensitive features from the temperature effect and reliably detect damage.

Abstract: Principal Component Analysis (PCA) and Wavelet Transform (WT) aretwo well-known signal processing tools that are widely used indifferent fields. PCA playsa vital role in statistical analysis as a dimensional reduction tool. Besides, WT has proven its abilityto overcome many of the limitation of the others among various time-frequencyanalyzers. The present work attempts to use the properties and advantagesof both methodologies together in damage detection. To achieve thisaim, PCA is applied on ridges of wavelet transform of measured signalsfrom the structure. The results show that the proposed combination improvesthe accuracy of detection comparing with PCA damage detection basedon original data captured from sensors. According to the result, when PCA uses the ridges of transformed data, theidentifications of damages are more clear and accurate. This work involvesexperiments with an aluminum beam using piezoelectrictransducers as sensors and actuators. Damages are introduced intothe structure as a cut in several steps enlarging the depthof cut.

Abstract: Signal processing method based on wavelet transform used in non-linear acoustic test is presented in the paper. The method is applied for sidebands identification in response signal acquired during vibro-acoustic modulation test of impacted carbon fiber reinforced plate (CFRP). The plate was impacted with known energy using drop-weight testing machine. The modulation effect in investigated specimen results from the interaction of low and high frequency excitation with damage. The paper investigates different than mono-harmonic low-frequency excitation usually used in non-linear acoustics tests. Application of aperiodic low-frequency excitation signal allows to omit the modal test, where natural frequency of the structure are estimated. However, this requires the use of dedicated signal processing methods.

Abstract: Photogrammetric techniques have demonstrated their suitability for monitoring static structural tests. Advantages include scalability, reduced cost, and three dimensional monitoring of very high numbers of points without direct contact with the test element. Commercial measuring instruments now exist which use this approach. Dynamic testing is becoming a convenient approach for long-term structural health monitoring. If image based methods could be applied to the dynamic case, then the above advantages could prove beneficial. Past work has been successful where the vibration has either large amplitude or low frequency, as even specialist imaging sensors are limited by an inherent compromise between image resolution and imaging frequency. Judgement in sensor selection is therefore critical. Monitoring of structures in real-time is possible only at a reduced resolution, and although imaging and computer processing hardware continuously improves, so the accuracy demands of researchers and engineers increase. A new approach to measuring vibration is introduced here, whereby a long-exposure photograph is used to capture a blurred image of the vibrating structure. The high resolution blurred image showing the whole vibration interval is measured with no need for high-speed imaging. Results are presented for a series of small-scale laboratory models, as well as a larger scale test, which demonstrate the flexibility of the proposed technique. Different image processing strategies are presented and compared, as well as the effects of exposure, aperture and sensitivity selection. Image processing time appears much faster, increasing suitability for real-time monitoring.

Abstract: In this work a signal processing algorithm for Lamb waves based defect detection/localization procedures is proposed. In particular, the proposed signal processing allows active-passive networks of piezosensors to use chirp shaped pulses in actuation, instead of classically applied spiky pulses. Thus, defect detection/localization can be achieved by using low power voltages in actuation. Basically, the proposed processing is capable to compensate the acquired time-waveforms from the dispersion due to the traveled distance as well as to compress the additional pulse spreading due to the chirp actuation. A processed time-waveform is thus directly transformed into a distance of propagation. Next, the compensated and compressed signals are exploited to feed an imaging algorithm aimed at providing the position of the defect on the plate. As a result, an automatic detection procedure to locate defect-induced reflections is demonstrated and successfully tested by analyzing experimental Lamb waves propagating in an aluminum plate. The proposed method is suitable for defect detection and can be easily implemented in real applications for structural health monitoring.

Abstract: Several nonlinear system identification methods have been presented in the past, such as the Extended Kalman Filter, the H filter and the Sequential Monte Carlo methods. One of the most promising ones is the Unscented Kalman Filter (UKF) recently proposed for the on-line identification of structural parameters. In the present study the UKF is proposed to the purpose of the nonlinear identification of a new prototype of rolling-pendulum tuned vibration absorber which, relying on an optimal three-dimensional guiding receptacle, can simultaneously control the response of the supporting structure along two orthogonal horizontal directions. Unlike existing ball vibration absorbers, mounted on spherical recesses and used in axial-symmetrical structures, the new device can be bidirectionally tuned to both fundamental structural modes even when the corresponding natural frequencies are different, by virtue of the optimum shape of the rolling cavity. Based on preliminary numerical simulations, the UKF is shown to be effective in identifying the structural parameters of the new device and particularly the nonlinear rolling friction dissipation mechanism at the interface between the ball bearing and the rolling surface.

Abstract: We describe a method to effectively image and characterize structural features and defects using local estimates of wavenumber for propagating guided Lamb waves at a fine grid of spatial sampling points. The guided waves are rapidly excited at each grid point using a scanning Q-switched laser system and sensed by a single fixed ultrasonic transducer. Through reciprocity, this produces a full-wave-field time history of a virtual wave being excited from the transducer.We first demonstrate the unique capability of the measurement system by showing frequency-wavenumber intensity diagrams that resolve up to 5^th order guided Lamb wave modes. Well then show how, using frequency-wavenumber processing, localized wavelength estimates can be obtained by isolating each guided Lamb wave mode, extracting a specific frequency bin, and identifying the center-wavelength of a sliding wavenumber band-pass filter that maximizes the energy at each grid point. This procedure is repeated across all frequency bins in order generate estimates of the local dispersion curves at each spatial sample point on the structure. The approach was capable of producing detailed images of hidden wall-thinning in an aluminum plate and local impact delamination in a complicated composite component.