J. Saniie

Flaw-to-grain echo enhancement by split-spectrum processing

Abstract A split-spectrum processing technique for an ultrasonic flaw detection system has been developed which improves the flaw-to-grain echo ratio in large-grained materials. The enhancement is achieved by partitioning a wide-band received spectrum to obtain frequency shifted bands, which are then processed to suppress the grain echoes with respect to the flaw echo, using a novel signal minimization algorithm. Experimental data for titanium and stainless steel samples are presented which show superior flaw detection capabilities for the minimization algorithm with respect to frequency averaging techniques.

Quantitative grain size evaluation using ultrasonic backscattered echoes

Grain size characterization using ultrasonic backscattered signals is an important problem in nondestructive testing of materials. In this paper, a heuristic model which relates the statistical characteristics of the measured signal to the mean ultrasonic wavelet and attenuation coefficient in different regions of the sample is investigated. The losses in the backscattered signal are examined using temporal averaging, correlation, and probability distribution functions of the segmented data. Furthermore, homomorphic processing is used in a novel application to estimate the mean ultrasonic wavelet (as it propagates through the sample) and the frequency‐dependent attenuation. In the work presented, heat‐treated stainless steel samples with various grain sizes are examined. The processed experimental results support the feasibility of the grain size evaluation techniques presented here using the backscattered grain signal.

Digital phase detection based on in-phase and quadrature sampling

A simple and efficient algorithm of digital phase detection is presented. From data sampled at two instants of time separated by a quarter of the signal period an estimate of phase and magnitude can be obtained. The additional use of coherent averaging improves the accuracy of phase detection in signals with poor signal-to-noise ratio. A system implementation of the algorithm and error caused by the harmonics of the measured signal is discussed.

Modeling and moments of multibreath lung washout

Ventilation inhomogeneity, an important characteristic of abnormal lungs, is demonstrated in the dynamics of multibreath lung washout. Quantitative evaluation of the washout curve can be obtained from a model-free index, such as a moment ratio, or parameters of a model. Although a moment ratio is easier to compute and less dependent on noise, the parameters of an appropriate model have a direct physiological interpretation. In this study, we develop anN-alveolar-space model from dynamic mass balance equations, which account for breathing pattern variations. The general model takes the form of a set of time-varying, linear difference equations. Special cases of fewer alveolar spaces and time-invariance are examined in more detail. Properties of the time-invariant model are determined with the use of generating functions. In particular, from the generating function of the two-alveolar-space model, the ratio of the first-to-zero moments is expressed in terms of model parameters. If one of the spaces is poorly ventilated, the moment ratio approximately equals the relative volume-flow ratio of that space. As obtained from the model and found experimentally, the moment ratio gets larger as the ventilation inhomogeneity increases.

Spectral Evaluation of Ultrasonic Grain Signals

The ultrasonic wave traveling through solids is subject to energy losses due to scattering and absorption. In the Rayleigh scattering region, both scattering and absorption are functions of frequency and grain size distribution. Grain scattering results in an upward shift in the expected frequency of a broadband ultrasonic wave , while the attenuation effect influences the frequency shift in a downward direction. These opposing phenomena can be utilized for grain size evaluation. In this report, we present a spectralshift quantization technique using homomorphic processing and moment analysis. Computer simulation and experimental results obtained from steel samples with different grain sizes support the feasibility of using spectral quantization techniques for grain size characterization. I. INTRODUCTION Conventional ultrasonic microstructure evaluation techniques are based on a comparison of attenuation measurements of specimens with unknown grain sizes to specimens with known grain sizes. This is accomplished either by transmitting an ultrasonic wave through the specimen using two transducers, or by pulsing the transducer and measuring the amplitude of the echo as it returns from the far end of the specimen toward the transducer. An alternative method of estimating attenuation is by using frequency domain information of the backscattered grain signal. Since attenuation is a function of frequency and grain size distribution, a broad-band transducer can be used to measure the backscattered signal and to perform spectral analysis. In this paper we present an evaluation of two techniques for spectral analysis, moment estimation and homomorphic processing, the processes of which were presented in our earlier work [l]. These techniques are capable of estimating frequency shift resulting from grain scattering and attenuation in the power spectrum. Both computer simulated data and experimental measurements are used for evaluating the performance of these techniques. -4 model for the expected amplitude of the backscat

Lung washout during spontaneous breathing: Parameter estimation with a time-varying model

Abstract We use a time-varying model to analyze the multibreath washout of nitrogen from lungs of human subjects breathing spontaneously. Based on standard pulmonary function evaluation, the 39 subjects tested are classified in the following categories: nonsmoking normal, “smoking” normal, asthma, diffuse interstitial lung disease, and chronic obstructive lung disease. The degree of ventilation inhomogeneity among these subjects was indicated by two independent parameters of the model, which were estimated by nonlinear optimization. A Gauss-Newton algorithm with a Marquardt modification was applied to a least-squares objective function. Constraints were included in a penalty function. Values of the model parameters from repeated washouts of the same subjects showed wide variability. Also, model parameters did not appear to provide any better distinction among clinical groups than did a moment ratio whose computation is much less expensive and more reliable.

Ultrasound Imaging Through Highly Reverberant Thin Layers

Nondestructive testing of targets c onsisting of a finite number of thin layers using backscattered ultrasound echoes is highly desirable in material evaluation. These targets can be examined by an ultrasound pulse-echo system from uhich acoustical parameters sensitive to the inhomogeneity of the samples are extracted. In practice, extracting these parameters is difficult if nor impossible because of: l) limitation o f system spatial resolution, and 2) multiple reflection uithin the target. In this study the system resolution has been improved by using transducers uith the largest possible banduidth taking into account the increase in absorption and scattering, and applying a subtraction technique uhen the signal-to-noise ratio is high. In addition, the r everberation echoes are also identified and classified by decoupling the components of the backscattered echoes. These techniques have been adapted for measuring support

Evaluation of Heat Treated Stainless Steel Samples by Split-Spectrum Processing Technique

In ultrasonic examination where the grain size is much smaller than the sound wavelength (Rayleigh scattering) multiple scattering effects can be ignored. However, for a large grain environment in which the sound wavelength is on the order of the grain size (Stochastic scattering) multiple scattering can no longer be neglected and may reduce the effectiveness of the ultrasonic inspection. Here we present experimental data for heat treated stainless steel samples of various grain sizes. From the available experimental parameters, the stainless steel samples were determined to fall in the Rayleigh and Stochastic scattering regions. In these experiments a signal processing technique referred to as split-spectrum processing was used which improves detection of flaws in large grained materials. The examination of these samples showed the split-spectrum processing to achieve effective grain noise suppression. However, the performance of the algorithm indicates dependence on the grain size, which in general, deteroriates as the grain size increases.