Nihat M. Bilgutay

Analysis of homomorphic processing for ultrasonic grain signal characterization

A model for the grain signal is presented, which includes the effect of frequency-dependent scattering and attenuation. This model predicts that the expected frequency increases with scattering and decreases with attenuation. Homomorphic processing was used for spectral smoothing, and the selection of parameters for optimal performance was examined. Experimental results are presented that show both the upward shift in the expected frequency with grain boundary scattering and the downward shift with attenuation. Furthermore, it is shown that the expected frequency shift can be correlated with the grain size of the material. It is important to point out that the quantitative relationship between the average grain size and the expected frequency shift (either upward or downward) is dependent on the type of material, the quality of grain boundaries, and the characteristics of the measuring instruments.<<ETX>>

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.

Spectral histogram using the minimization algorithm-theory and applications to flaw detection

In ultrasonic flaw detection in large grained materials, backscattered grain noise often masks the flaw signal. To enhance the flaw visibility, a frequency diverse statistical filtering technique known as split-spectrum processing has been developed. This technique splits the received wideband signal into an ensemble of narrowband signals exhibiting different signal-to-noise ratios (SNR). Using a minimization algorithm, SNR enhancement can be obtained at the output. The nonlinear properties of the frequency diverse statistic filter are characterized based on the spectral histogram, which is the statistical distribution of the spectral windows selected by the minimization algorithm. The theoretical analysis indicates that the spectral histogram is similar in nature to the Wiener filter transfer function. Therefore, the optimal filter frequency region can be determined adaptively based on the spectral histogram without prior knowledge of the signal and noise spectra.<<ETX>>

Enhanced ultrasonic imaging with split-spectrum processing and polarity thresholding

The polarity thresholding algorithm, which utilizes the frequency decorrelation principle based on the split-spectrum processing technique, is examined. Split-spectrum processing obtains an ensemble of frequency diverse signals from a wideband received signal by using a set of parallel bandpass filters with different center frequencies. Polarity thresholding acts as an on-off switch on the resulting data by setting the output to zero at time instants where the split-spectrum ensemble exhibits polarity reversal. Since the target echo exhibits significantly smaller variation with frequency compared to cluster echoes, polarity thresholding maintains the target echo while suppressing a significant portion of the clutter echos. Theoretical derivations are provided to determine the signal-to-noise ratio enhancement capabilities of the algorithm. Ultrasonic data obtained from large-grained stainless steel samples with flat-bottom holes are used to verify the theoretical results and demonstrate the grain echo suppression capability of the algorithm in imaging applications. >

Statistical evaluation of backscattered ultrasonic grain signals

Insonification of the microstructure of materials results in a backscattered signal consisting of multiple interfering echoes with random amplitudes and phases. Information pertaining to grain scattering cross section and grain size distribution is an inherent property of the backscattered signal. A statistical model of grain signals is developed that describes the spatial and time averaged data, and their relationship to signal attenuation caused by scattering and absorption. Both spatial and temporal averaging permits the estimation of the attenuation coefficient, which has been found to be position dependent. Furthermore, it has been shown experimentally and theoretically that the performance of spatial and time averaging is governed by correlation properties of the grain signal.

Spectral correlation in ultrasonic pulse echo signal processing

The effects of using spectral correlation in a maximum-likelihood estimator (MLE) for backscattered energy corresponding to coherent reflectors embedded in media of microstructure scatterers is considered. The spectral autocorrelation (SAC) function is analyzed for various scatterer configurations based on the regularity of the interspacing distance between scatterers. It is shown that increased regularity gives rise to significant spectral correlation, whereas uniform distribution of scatters throughout a resolution cell results in no significant correlation between spectral components. This implies that when a true uniform distribution for the effective scatterers exists, the power spectral density (PSD) is sufficient to characterize their echoes. However, as the microstructure scatterer distribution becomes more regular, SAC terms become more significant. MLE results for 15 A-scans from stainless steel specimens with three different grain sizes indicate an average 6-dB signal-to-noise ratio (SNR) improvement in the coherent scatterer (flat-bottom hole) echo intensities for estimators using the SAC characterization as opposed to the PSD characterization.<<ETX>>

Order statistic filters as postdetection processors

The performance of radar detection systems can be improved through postdetection processing. The performance of the binary integrator from the viewpoint of order statistics is examined, and the binary integrator as an order statistic (OS) filter is described. A general analysis for OS filters in detection systems is developed and it is used to show the OS filter is a consistent and biased estimator of the quantities of the received signal distributions. The features of the OS filter and n-pulse integrator that are critical to detection performance are compared to determine the proper application of each processor. It is shown that the OS filter can be used to emphasize selective regions of the input distributions where good statistical separability between the class of input signals exist. A computer simulation is performed to illustrate the performance of binary and n-pulse integration for the detection of a white chi distributed target in white Weibull clutter and a white Rayleigh distributed target in white Rayleigh clutter. >

First-year integrated curricula across engineering education coalitions

The National Science Foundation has supported creation of eight engineering education coalitions: Ecsel, Synthesis, Gateway, SUCCEED, Foundation, Greenfield, Academy and Scceme. One common area of work among these coalitions has been restructuring first-year engineering curricula. Within some of the Coalitions, schools have designed and implemented integrated first-year curricula. The purpose of this paper is to survey the different pilots that have been developed, abstract some design alternatives which can be explored by schools interested in developing an integrated first-year curriculum, indicated some logistical challenges, and present brief descriptions of various curricula along with highlights of the assessment results which have been obtained.

High-Frequency Ultrasound Technique for Testing Concrete

This paper offers the split spectrum processing (SSP) protocol, a data processing method, to make the use of ultrasound of MHz-frequency possible for improved nondestructive defect detection and layer thickness determination of concrete. Reflected ultrasonic signals can be obtained from both defects within and the boundaries of concrete; but when the frequency is high, they are corrupted, typically, by echoes from randomly distributed scatterers in the form of (coherent) noise. This results in low signal-to-noise ratio; that is, it is difficult, if not impossible, to distinguish defect signals from scatterer noise that cannot be reduced by time averaging. This paper shows that defect visibility in concrete can be enhanced by combining the high-frequency pulse-echo test with SSP. The basis of SSP is that the scatterer noise is highly sensitive to shifts in the operating frequency, whereas the echoes from targets of interest are not. Thus, if an ultrasonic signal with broad frequency content is captured after passing through concrete, and its Fourier spectrum is led through a Gaussian filter bank that splits the signal into different frequency bands, then the computerized reassembly of these bands enhances the signal-to-noise ratio because the scatterer noise contents obtained at different frequencies cancel out. SSP has been successful with metals and polymers. These test results demonstrate the SSPs noise reduction potential also for improved nondestructive testing of concrete with ultrasound of frequencies up to 1 MHz. It is also shown, however, that further research is needed for field application.

Analysis of a non-linear frequency diverse clutter suppression algorithm

Abstract The target signal is often received in the presence of coherent noise resulting from a large number of complex and randomly distributed scatterers known as clutter, whose echoes can suppress or mask the actual target echo. This is a fundamental limitation which exists in all imaging and detection applications and cannot be removed by conventional techniques, such as time averaging. This paper examines a non-linear signal processing algorithm (polarity thresholding) used in conjunction with a frequency diversity technique (split-spectrum processing), which decorrelates clutter. Since the target echo exhibits significantly smaller amplitude variations with frequency compared to clutter, the polarity thresholding algorithm can achieve flaw enhancement by setting the output to zero at time instants where phase reversal occurs. Theoretical derivations are provided to determine the signal to noise ratio enhancement capabilities of the algorithm. Ultrasonic data obtained from large grained stainless-steel samples with flat-bottom holes are used to verify the theoretical results and demonstrate the grain echo suppression capability of the algorithm in imaging applications.