Abstract-In ultrasonic measurement situations, when dealing with media of multi-layered structures consisting of 1 or more thin layers, analysis of the measured ultrasonic waveform can be difficult because of overlapping and reverberant echoes. Information from the individual layers is then difficult to extract because the individual echoes cannot be detected. In this study, we use a parametric layer model to analyze the multi-layered material in a system identification approach. The parameters of the model are connected to physical properties of the investigated material, e.g., the reflection coefficients, the time-of-flight, and the attenuation. The main advantage using this model is that the complexity of the model is connected to the number of layers rather than the number of observable echoes in the received ultrasonic waveform. A system of linear equations is presented, giving the opportunity to find the model for both pulse-echo and through-transmission measurements. A thorough effort is made on the parameter estimation and optimization algorithm. The model is validated with practical measurements on a 3-layered structure using both pulse-echo and through-transmission techniques. The 3-layered material consists of a thin embedded middle layer with the time-of-flight in that layer shorter than the emitted signal's time support, giving rise to overlapping echoes. Finally the relation between the model parameters and physical properties of the material is established.
In some ultrasonic measurement situations, an adequate signal separation is difficult to achieve. A typical situation is material characterization of thin media using pulse-echo or through-transmission techniques, when the time-of-flight in the media is shorter than the emitted signal's time support. Separated signals are necessary to obtain accurate estimates of material properties and transit times. In this paper a new method is proposed that enables complete post-separation of measured coinciding signals. The method is based on a combination of hard physical and soft empirical models, which allows for a description of both known and unknown properties making a complete separation possible. The validity and limitations of the model and the separation results are thoroughly addressed. The proposed technique is verified using real measurements on thin dispersive samples and validated using residual analysis. The experimental results show a complete separation with uncorrelated and normally distributed residuals. The method enables characterization and/or flow analysis in difficult overlapping situations.
Abstract-In materials consisting of several thin layers, multiple reflections within the structure give rise to received ultrasonic signals composed of overlapping echoes. In this paper we present a parametric model that can be used to decompose such signals into the individual reflections. We derive a Maximum Likelihood Estimator for the the model parameters, which are then used in a Generalized Likelihood Ratio Test (GLRT) to detect flaws in multi-layered structures. We show with simulations how the presence of a thin bonding layer in a three-layer structure can be detected. The probability of detection is shown to be ≈ 96%, for a signal-to-noise ratio (SNR) of 15 dB and a probability of false alarm of 5%.
Methods for non-destructive inspection of layered materials are becoming more and more popular as a way of assuring product integrity and quality. In this paper, we present a model-based technique using ultrasonic measurements for classification of thin bonding layers within three-layered materials. This could be, for example, an adhesive bond between two thin plates, where the integrity of the bonding layer needs to be evaluated. The method is based on a model of the wave propagation of pulse-echo ultrasound that first reduces the measured data to a few parameters for each measured point. The model parameters are then fed into a statistical classifier that assigns the bonding layer to one of a set of predefined classes. In this paper, two glass plates are bonded together with construction silicone, and the classifiers are trained to determine if the bonding layer is intact or if it contains regions of air or water. Two different classification methods are evaluated: nominal logistic regression and discriminant analysis. The former is slightly more computationally demanding but, as the results show, it performs better when the model parameters cannot be assumed to belong to a multivariate Gaussian distribution. The performance of the classifiers is evaluated using both simulations and real measurements.
Measurements performed on a thin multilayered structure will imply a received signal waveform consisting of reverberant overlapping echoes. In this paper the multi-layered structure is modeled by a physical model and the Maximum Likelihood Estimator (MLE) is derived for the model parameters. A general recursive expression for the model is given. The model is evaluated using measurements on a thin three-layered structure, where two glass layers are bonded together. We show that measured signal waveforms can be reconstructed using the estimated parameters, and that physical properties can be extracted from the estimated model parameters. Simulations also show that physical parameters can be estimated for thicknesses of the bonding layer down to 50 μm for a wavelength of 200 μm of the ultrasonic pulse.Keywords: Material characterization, multi-layered structure, parametric model, pulse-echo ultrasound A. IntroductionNon-destructive testing of materials using ultrasound is considered a valuable tool to characterize thin layers in a multi-layered material. In this paper we propose a method to estimate material properties of the thin bonding layer in a multi-layered material using a physical model. The thinlayered material structure gives rise to overlapping ultrasonic echoes. The model structure is therefore chosen so that the variations in the received ultrasonic signal waveform are captured by a small number of model parameters.The material is modeled using a continuous autoregressive (AR) model with parameters connected to physical properties, related to the thickness of the layers, the reflection and the transmission coefficients given by the boundaries between the layers, and the attenuation inside the layers. The paper derives the Maximum Likelihood Estimator (MLE) for the model parameters.We show with simulations how accurate estimates of the model parameters we get when the thicknesses of the layers decrease. Material properties such as speed of sound, acoustic impedance, and density of the layers can be estimated from the parameters with corresponding confidence interval for varying signal-to-noise ratio and material layer properties.The model is evaluated with real measurements on two glass layers bonded together by a thin layer, where some properties of the layers are known. The measured signal waveform consists of reverberant overlapping echoes, and using the proposed parametric model we show that reliable estimates of the bonding layer properties can be deduced from the estimated parameters. B. TheoryIn this section, the signal model and the parameter estimation for the property extraction problem is stated in the frequency domain. The physical properties related to the estimated parameters are stated and the parameter estimation is explained. B.1. General Parametric ModelSending an ultrasonic echo through a multi-layered material will produce a received signal waveform consisting of several delayed and attenuated echoes. A structure consisting of thin layers will produce reverberating echoes d...
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