Analysis of homomorphic processing for ultrasonic grain signal characterization

Saniie, Jafar; Wang, T.; Bilgutay, N.M.

doi:10.1109/58.19177

Cited by 77 publications

(33 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Elsley et al [10] have reported that the flaw spectrum peaks at a frequency lower than that of the trans duc er spectrum. The frequency dependence of the scattering coefficient in the Rayleigh scattering region has been studied by Saniie et al [11]. The results show that the intensity of the backscattered components Is targer at high frequencies, which indicates that grain noise due to scattering will be greater at higher frequencies.…”

Section: Theoretical Analysismentioning

confidence: 85%

Application of Bandpass Filtering in Ultrasonic Non-Destructive Testing

Murthy

Bilgutay

Saniie

1989

Review of Progress in Quantitative Nondestructive Evaluation

View full text Add to dashboard Cite

LNTRODUCTIONUltrasonie nondestructive testing oflarge grained materials is limited by the ability of the detection process to distinguish the flaw signals from the backscattered grain boundary echoes. This coherent grain noise often masks the echo from inhomogeneities and defects in the material. Absorption and scattering effects further reduce the ultrasound energy leading to poor signal-to-noise ratio in the received signal. It is not possible to reduce the grain clutter by conventional time averaging techniques due to its coherent nature. Different algorithms utilizing the principles of frequency diversity and spatial diversity have been used in the past for signal-to-noise ratio enhancement. In NDE applications where the noise is primarily due to Rayleigh scattering, it can be shown that flaw detection can be improved significantly by merely bandpass filtering the lower part of the received wideband echo spectrum. Both theoretical and experimental results are presented to support this conclusion. The filtering technique is successfully tested on materials with different grain sizes. The main advantage of this method is its relative simplicity, which eliminates the need for sophisticated and computationally intensive signal processing algorithms. Furthermore, this technique allows simple hardware implementation for real-time applications. The optimal parameters, i.e., the center frequency and bandwidth of the bandpass filter are experimentally determined.

show abstract

Section: Theoretical Analysismentioning

confidence: 85%

Application of Bandpass Filtering in Ultrasonic Non-Destructive Testing

Murthy

Bilgutay

Saniie

1989

Review of Progress in Quantitative Nondestructive Evaluation

View full text Add to dashboard Cite

show abstract

“…Using the mercury intrusion method, we verified that, at 10 MHz, E[D]/ varied between 0.026 and 0.071 for the di↵erent types of cement paste considered, where is the wavelength and D is the mean grain size. Therefore, we are working in the Rayleigh region [23], and we have a moderate, but su cient, amount of grain noise. When the frequency increases, it produces an attenuation that is too large; when the frequency decreases, it reduces the level of GN (the ultrasound pulse propagated better, but there were no echoes from the inner microstructure).…”

Section: Application To the Characterization Of Cement Pastesmentioning

confidence: 99%

Measuring predictability in ultrasonic signals: An application to scattering material characterization

2014

View full text Add to dashboard Cite

In this paper, we present a novel and completely di↵erent approach to the problem of scattering material characterization: measuring the degree of predictability of the time series. Measuring predictability can provide information of the signal strength of the deterministic component of the time series in relation to the whole time series acquired. This relationship can provide information about coherent reflections in material grains with respect to the rest of incoherent noises that typically appear in non-destructive testing using ultrasonics. This is a non-parametric technique commonly used in chaos theory that does not require making any kind of assumptions about attenuation profiles. In highly scattering media (low SNR), it has been shown theoretically that the degree of predictability allows material characterization. The experimental results obtained in this work with 32 cement probes of 4 di↵erent porosities demonstrate the ability of this technique to do classification. It has also been shown that, in this particular application, the measurement of predictability can be used as an indicator of the percentages of porosity of the test samples with great accuracy.Keywords: Ultrasonic Signal Modality, Ultrasonic NDT, Multiple scattering, Noise, Determinism, Chaos Theory, Higher order statistics IntroductionWhen scattering materials are subject to ultrasonic non-destructive testing (NDT), the ultrasonic pulse undergoes some variations that are related to the internal grain microstructure of the specimen. Each grain behaves like a scattering center, producing an echo that when superimposed on other echoes coming from other grains can even hide the echoes produced by a possible defect. Similar situations are found in other related fields such as ultrasound B-mode scans (where the grain noise is called speckle) and in radar with clutter [1].In the literature, a wide range of solutions has been proposed to enhance the detection of small cracks or defects and to reduce (or even eliminate) the e↵ect discussed in each of the above situations. Some of these solutions are signal averaging, auto-and cross-correlation, matched filtering, frequency spectrum analysis [2], spectral correlation [3], and wavelet transformations [4]. The aforementioned analyses discard the information encoded in the grain noise; however, this information can be used to recognize potential di↵erences among materials, tissues, or surfaces. This approach has been employed to characterize materials by extracting temporal signal statistics [1], the resonance frequency [5], and even the penetration depth [6]. Our work continues with this line of thought and proposes a new approach that attempts to extract information about the nature of the signal, thereby characterizing the signal modality. Signal modality characterization is a key concept of a multidisciplinary research topic that includes di↵erent concepts such as signal linearity, stationarity, and stochasticity [7]. The applications of signal modality characterization are becoming mo...

show abstract

“…(c) (dashed line) using a 28ps (approximately equivalent to the duration of a single echo governed by the characteristic of the transducer) shortpass lifter. Note that this duration for the shortpass lifter is chosen to provide sufficient smoothing [2]. The scattering function, S(f), can be found by the ratios of the spectrums of the grain echoes ((5)) and the back surface echo ( ( 4 ) ) , Rg(j)/Rb(f), which is displayed in Fig.…”

Section: Iw)i X I a (~) I I W ) I (4)mentioning

confidence: 99%

Analysis of order-statistic CFAR threshold estimators for improved ultrasonic flaw detection

Saniie

Nagle

1992

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

Self Cite

View full text Add to dashboard Cite

In the pulse-echo method using broadband transducers, flaw detection can be improved by using optimal bandpass filtering to resolve flaw echoes surrounded by grain scatterers. Optimal bandpass filtering is achieved by examining spectral information of the flaw and grain echoes where frequency differences have been experimentally shown to be predictable in the Rayleigh scattering region. Using optimal frequency band information, flaw echoes can then be discriminated by applying adaptive thresholding techniques based on surrounding range cells. The authors present order-statistic (OS) processors, ranked and trimmed mean (TM), to robustly estimate the threshold while censoring outliers. The design of these OS processors is accomplished analytically based on constant false-alarm rate (CFAR) detection. It is shown that OS-CFAR and TM-CFAR processors can detect flaw echoes robustly with the CFAR of 10 (-4) where the range cell used for the threshold estimate contains outliers.

show abstract

Analysis of homomorphic processing for ultrasonic grain signal characterization

Cited by 77 publications

References 19 publications

Application of Bandpass Filtering in Ultrasonic Non-Destructive Testing

Application of Bandpass Filtering in Ultrasonic Non-Destructive Testing

Measuring predictability in ultrasonic signals: An application to scattering material characterization

Analysis of order-statistic CFAR threshold estimators for improved ultrasonic flaw detection

Contact Info

Product

Resources

About