EXPERIMENTAL VALIDATION OF A STRUCTURAL HEALTH MONITORING METHODOLOGY: PART II. NOVELTY DETECTION ON A GNAT AIRCRAFT

This paper concerns the second phase of an experimental validation programme for a structural health monitoring methodology based on novelty detection. This phase seeks to apply one of the methods considered in the first stage of the work on a more realistic structure, namely the wing of a Gnat aircraft, as opposed to the previously investigated laboratory structure. The novelty detection algorithm used is that of outlier analysis and damage is introduced by making several copies of an inspection panel, each with a different controlled fault. All of these faults were detectable, a single feature was highlighted which proved capable of separating all the fault conditions from the unfaulted.     

NOVELTY DETECTION IN A CHANGING ENVIRONMENT: REGRESSION AND INTERPOLATION APPROACHES

The technique of novelty detection is now established as a means of performing the lowest level of damage identification. Data are accumulated while the system or structure is operating in normal condition and used to construct a reference model. During subsequent operation of the system, data are compared to the reference and any significant deviations are taken to indicate damage. This approach has potential problems if the system or structure is embedded in a changing environment. If the reference data are only characteristic of a limited range of the environmental parameters, measurements from the system in an undamaged condition but from a different environmental state, may cause the diagnostic to register novelty and thus falsely infer damage. This paper demonstrates a potential solution to the problem via the construction of a reference set parametrized by an environmental variable. Two approaches are considered: regression and interpolation.     

The use of pseudo-faults for novelty detection in SHM

The main problem associated with pattern recognition based approaches to Structural Health Monitoring (SHM) is that damage localisation and quantification almost always require supervised learning. In the case of high-value engineering structures like aircraft, it is simply not possible to generate the training data associated with damage by experiment. It is also unlikely that data can always be generated by simulation as the models required would often need to be of such high fidelity that the costs of development and the run-times would again be prohibitive. The object of this paper is to explore the potential of a simple experimental strategy, which involves adding masses to the structure, in the attempt to extract features for novelty detection. The idea itself is not presented as revolutionary based on the fact that adding masses has been considered as a case of damage before, however, an in-depth investigation of its suitability for guiding feature selection is presented here. The approach is illustrated first on a simple structure by using data generated from a finite-element (FE) simulation and then validated experimentally on a more complicated laboratory structure. Simulated damage, in the form of a loss in the stiffness in the case of the numerical model and of a saw-cut in the case of the structure is used for comparison. The results show similar patterns in both cases which suggests a potential use of the method for higher level damage detection.     

Cetacean population density estimation from single fixed sensors using passive acoustics

Passive acoustic methods are increasingly being used to estimate animal population density. Most density estimation methods are based on estimates of the probability of detecting calls as functions of distance. Typically these are obtained using receivers capable of localizing calls or from studies of tagged animals. However, both approaches are expensive to implement. The approach described here uses a MonteCarlo model to estimate the probability of detecting calls from single sensors. The passive sonar equation is used to predict signal-to-noise ratios (SNRs) of received clicks, which are then combined with a detector characterization that predicts probability of detection as a function of SNR. Input distributions for source level, beam pattern, and whale depth are obtained from the literature. Acoustic propagation modeling is used to estimate transmission loss. Other inputs for density estimation are call rate, obtained from the literature, and false positive rate, obtained from manual analysis of a data sample. The method is applied to estimate density of Blainville's beaked whales over a 6-day period around a single hydrophone located in the Tongue of the Ocean, Bahamas. Results are consistent with those from previous analyses, which use additional tag data.     

Impact localization and energy quantification based on the power flow: A low-power requirement approach

The increasing use of composite materials has led to a dramatic change in the definition of safety standards. In particular, composite structures may be subjected to internal damages caused by external impacts that may not be detected by classical inspection methods. Additional constraints related to energy requirements may also be considered in order to make the system autonomous and possibly self-powered. The purpose of this paper is to present a low-cost impact detection and quantification scheme for thin plates or shells giving the whole history of the structure solicitation. Based on the analysis of the energy that has flown over a monitored area through the use of the elastic Poynting vector (that relates the mechanical power density of travelling waves), it is shown that this global energy balance may be linked in a simple way to the voltage output of piezoelectric elements in open-circuit condition. From this estimation, it is therefore possible to detect if an impact occurred inside the monitored area (in this case, the global energy balance would be positive) as well as its associated energy. If the impact occurs out of the frame, the global energy (and thus the obtained estimator) would be negative because of energy dissipation caused by internal losses and almost null. Thanks to this energy flow approach, the system is also independent from the boundary conditions of the structure. Experimental measurements aiming at validating the theoretical predictions showed that the technique permits detecting the impact area (inside/outside the frame) as well as an accurate estimation of the impact energy if the latter occurred inside the frame, both on a steel plate (with different boundary conditions) and an anisotropic composite structure.     

Optimally discriminant moments for speckle detection in real B-scan images

The paper presents and evaluates a speckle detection method for B-scan images. This is a fully automatic method and does not require information about the sensor parameters, which is often missing in retrospective studies.The characterization and posterior detection of speckle noise in ultrasound (US) has been regarded as an important research topic in US imaging, for improving signal-to-noise ratio by removing speckle noise and for exploiting speckle correlation information. Most of the existing methods require either manual intervention, the need to know sensor parameters or are based on statistical models which often do not generalize well to B-scans of different imaging areas. The proposed method aims to overcome those limitations.The main novelty of this work is to show that speckle detection can be improved based on finding optimally discriminant low order speckle statistics. In addition, and in contrast with other approaches the presented method is fully automatic and can be efficiently implemented to B-scan images.The method detects speckle patches using an ellipsoid discriminant function which classifies patches based on features extracted from optimally discriminant low order moments of the uncompressed intensity B-scan information. In addition, if the uncompressed signal is not available, we propose and evaluate a method for the estimation of this factor.The computation of low order moments using an optimality criteria, the decompression factor estimation and other key aspects of the method are quantitatively evaluated using both simulated and real (phantom and in vivo) data. Speckle detection results are obtained using again phantom and in vivo studies which show the validity of our approach. In addition, speckle probability images (SPI) are presented which provide valuable information about the distribution of speckle and non-speckle areas in an image.The presented evaluation and results show the effectiveness of our approach. In particular, the need for using discriminant analysis to determine the optimal discriminant power of the statistical moments and that this optimal value strongly depends on the characteristics and imaged tissues in the B-scan data.     

声学回波统计的鱼群密度评估方法*

与传统的回波积分法相比，回波统计鱼群数量密度评估方法具有无需回波信号绝对量和鱼群中个体鱼的平均目标强度先验知识的优点。对该方法在鱼群数量密度评估上的应用问题进行了实验研究，并针对其中鱼群密度分布的不均匀性及统计样本量偏少导致评估结果偏差的问题，提出了一种基于能量阈值的鱼群回波数据预处理方法和统计样本的改进抽样方法，有效提高了该方法鱼群密度评估的精确度。与传统的回波积分法评估结果的对比分析表明，该评估方法适用于低密度鱼群的评估。     

OFDM symbol detection integrated with channel multipath gains estimation for doubly-selective fading channels

Orthogonal Frequency Division Multiplexing (OFDM) is a technique for wideband transmission that is commonly used in modern wireless communication systems because of its good performance over frequency selective channels. However OFDM systems are sensitive to channel time variations resulting in Inter-Carrier Interference (ICI), that without suitable detection methods can degrade performance significantly. Channel State Information (CSI) is essential to various OFDM detection schemes, and its acquisition is a critical factor over time varying channels. This work considers a Kalman filter channel multipath gains estimation technique for time varying environments, integrated with a novel detection scheme for OFDM based on a Sphere Decoding (SD) algorithm derived to exploit the banded structure of the channel matrix. This combined scheme employs decision–feedback from the SD requiring only a low pilot symbol density, and hence improves bandwidth efficiency. Three techniques for integrating the Kalman filter operating in decision–feedback mode, with SD data detection that produces these decisions, are considered in this paper. When compared with other competing schemes, this integrated symbol detection and channel multipath gains estimation approach for OFDM provides performance advantages over time varying channels. Furthermore, it is shown that for moderate Doppler shifts the degradation that carrier phase noise induces in this scheme is small.     

Attenuation coefficient estimation using experimental diffraction corrections with multiple interface reflections

The ultrasonic attenuation coefficient of a fluid or solid is an acoustic parameter routinely estimated for the purpose of materials characterization and defect/disease detection. This paper describes a broadband attenuation coefficient estimation technique that combines two established estimation approaches. The key elements of these two approaches are: (1) the use of magnitude spectrum ratios of front surface, first back surface, and second back surface reflections from interfaces of materials with plate-like geometries, and (2) the use of an experimental diffraction correction approach to avoid diffraction losses. The combined estimation approach simplifies the attenuation coefficient estimation process by eliminating the need to explicitly make diffraction corrections or calculate reflection/transmission coefficients. The approach yields estimates of the attenuation coefficient, reflection coefficient, and material density. Models, experimental procedures, and signal analysis procedures, which support implementation of the approach, are presented. Attenuation coefficient and reflection coefficient estimates are presented for water and solid samples with estimates based on measurements made with multiple transducers.     

Locating the position of objects in non-line-of-sight based on time delay estimation

Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface(diffuser).It has very important significance in indirect access to an object or dangerous object detection, such as medical treatment and rescue. An approach to locating the positions of hidden objects is proposed based on time delay estimation. The time delays between the received signals and the source signal can be obtained by correlation analysis, and then the positions of hidden objects will be located. Compared with earlier systems and methods, the proposed approach has some modifications and provides significant improvements, such as quick data acquisition, simple system structure and low cost, and can locate the positions of hidden objects as well: this technology lays a good foundation for developing a practical system that can be used in real applications.     

Theoretical study of the decaying convective turbulence in a shear-buoyancy PBL

The derivation of a theoretical model for the decaying convective turbulence in a shear-buoyancy planetary boundary layer is considered. The model is based on the dynamical equation for the energy density spectrum in which the buoyancy, mechanical and inertial transfer terms are retained. The parameterization for the buoyancy and mechanical terms is provided by the flux Richardson number. Regarding the inertial term an approach employing Heisenberg’s spectral transfer theory is used to describe the turbulence friction, caused by small eddies, responsible for the energy dissipation of the large eddies. Therefore, a novelty in this study is to utilize the Adomian decomposition method to solve directly without linearization the energy density spectrum equation, with this the nonlinear nature of the problem is preserved. Therefore, the errors found are only due to the parameterization used. Comparison of the theoretical model is performed against large-eddy simulation data for a decaying convective turbulence in a shear-buoyancy planetary boundary layer. The results show that the existence of a mechanical turbulent driving mechanism reduces in an accentuated way the energy density spectrum and turbulent kinetic energy decay generated by the decaying convective production in a shear-buoyancy planetary boundary layer.     

EXPERIMENTAL VALIDATION OF A STRUCTURAL HEALTH MONITORING METHODOLOGY: PART III. DAMAGE LOCATION ON AN AIRCRAFT WING

This paper documents the third phase of a programme of experimental work which validates a structural health monitoring methodology based on novelty detection. In this paper, an extension of the detection method for damage location is proposed and demonstrated. The structure of interest is a Gnat aircraft wing. Although it was not possible to damage the aircraft, the method was demonstrated by determining which of a set of inspection panels had been removed.     

The influence of the stray-light component in determining coronal temperature structures

We use a few solar partial eclipse observations made by XRT/Hinode to estimate the influence of stray-light component in determining coronal temperature structures. Our analysis shows that the stray light will largely affect the estimation of coronal temperature and change the estimated temperature structure in one coronal hole region. The stray lights mildly influence the estimated temperatures in one quiet Sun region and do not change the estimated temperature structure. This implies that the influence of stray lights differs from one region to another, and definitely needs to be considered in some regions. Whereas a carefully estimated point-spread-function is needed to remove the stray light component, our study shows that by a simple approach such as subtracting the average intensity of distant (e.g. >1.4 solar radius) points from the data values, the influence of stray light can be largely removed, at least for the two regions we study here.     

A short range many-body potential for modelling bcc metals

The problem considered is the fitting of a many-body interaction potential to bulk crystal data. A parameterisation of the potential is assumed which is based on physical considerations. The free parameters are determined by using global optimization to perform a least squares fit, to a large number of crystal properties. This has been achieved for body centered cubic (bcc) materials. The approach adopted here fits the bcc crystal structure, as the preferred minimum energy configuration for tungsten, and also fits the dimer energetics and the elastic properties of crystalline tungsten.     

A new adaptive subband decomposition approach for automatic analysis of NMR data

This paper presents a non-iterative, fast, and almost automated time-data analysis method for NMR spectroscopy, based on a new adaptive implementation of high resolution methods used in spectral subbands. It is intended to avoid the choice of the decimation factor (or the width of the spectral windows) which, in the case of a uniform decomposition, strongly conditions the estimation results, and to diminish the computational burden. It is achieved through successive decimation/estimation stages each followed by a test procedure in order to decide whether or not the process should continue. The proposed test is based on a local spectral flatness measure of the estimation residuals. This stop-criterion involves an a posteriori validation of the estimation, thus the method proposed allows one to obtain a better detection rate at a lower complexity comparatively to other stopping rules, while preserving a reasonable estimation variance. Moreover, the reliability of the fitting algorithms considered is improved, by decreasing the influence of the model order and the number of false detections. Finally, the method is more efficient than Fourier transform (FT) at low signal-to-noise ratio (SNR). The effectiveness of the method is demonstrated by analyzing a simulation signal and raw carbon-13 experimental data.     

Simultaneous estimation of unwrapped phase and phase derivative from a closed fringe pattern

We propose a new approach for the direct estimation of the unwrapped phase from a single closed fringe pattern. The fringe analysis is performed along a given row/column at a time by approximating the phase with a weighted linear combination of linearly independent basis functions. Gaussian radial basis functions with equally distributed centers and a fixed variance are considered for the phase approximation. A state space model is defined with the weights of the basis functions as the state vector elements. Extended Kalman filter is effectively utilized for the accurate state estimation. A fringe density estimation based criteria is established to select whether the phase estimation is performed in a row by row or column by column manner. In the seed row/column decided based on this criteria, the optimal basis dimension is computed. The proposed method effectively renders itself in the simultaneous estimation of the phase and the phase derivative. The proposed phase modeling approach also allows us to successfully demodulate the low density fringe patterns. Simulation and experimental results validate the practical applicability of the proposed method.     

A path integral method for data assimilation

Described here is a path integral, sampling-based approach for data assimilation, of sequential data and evolutionary models. Since it makes no assumptions on linearity in the dynamics, or on Gaussianity in the statistics, it permits consideration of very general estimation problems. The method can be used for such tasks as computing a smoother solution, parameter estimation, and data/model initialization.Speedup in the Monte Carlo sampling process is essential if the path integral method has any chance of being a viable estimator on moderately large problems. Here a variety of strategies are proposed and compared for their relative ability to improve the sampling efficiency of the resulting estimator. Provided as well are details useful for its implementation and testing.The method is applied to a problem in which standard methods are known to fail, an idealized flow/drifter problem, which has been used as a testbed for assimilation strategies involving Lagrangian data. It is in this kind of context that the method may prove to be a useful assimilation tool in oceanic studies.     

A time-domain approach for damage detection in beam structures using vibration data with a moving oscillator as an excitation source

The problem of detecting local/distributed change of stiffness in bridge structures using ambient vibration data is considered. The vibration induced by a vehicle moving on the bridge is taken to be the excitation source. A validated finite element model for the bridge structure in its undamaged state is assumed to be available. Alterations to be made to this initial model, to reflect the changes in bridge behaviour due to occurrence of damage, are determined using a time-domain approach. The study takes into account complicating features arising out of dynamic interactions between vehicle and the bridge, bridge deck unevenness, spatial incompleteness of measured data and presence of measurement noise. The inclusion of vehicle inertia, stiffness and damping characteristics into the analysis makes the system time variant, which, in turn, necessitates treatment of the damage detection problem in time domain. The efficacy of the procedures developed is demonstrated by considering detection of localized/distributed damages in a beam-moving oscillator model using synthetically generated vibration data.