Split spectrum processing: optimizing the processing parameters using minimization

Karpur, Prasanna; Shankar, P.M.; Rose, Joseph L.; Newhouse, V.L.

doi:10.1016/0041-624x(87)90034-5

Cited by 50 publications

(32 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The methodology has been well documented in literature [4][5][6][7][8]. However, for the sake of completeness, abrief description of the technique follows.…”

Section: Background Information and Motivationmentioning

confidence: 99%

“…The 'N' frequency diverse signals so obtained are further processed using one of the algorithms of SSP. Further details of the method can be found in the literature [4,5].…”

Section: Background Information and Motivationmentioning

confidence: 99%

“…Split spectrum processing has been traditionally used only to improve SNR of the ultrasonic signals which in turn improves the detectability of anomalies [4][5][6][7][8]. The technique has not played a significant role in the characterization and sizing of anomalies.…”

Section: Background Information and Motivationmentioning

confidence: 99%

“…This paper deals with the effectiveness of split spectrum processing (SSP) [4][5][6][7][8] in improving the performance and reliability of signal analysis techniques such as deconvolutions and neural networks when used in tandem with such techniques.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Split Spectrum Technique as a Preprocessor for Ultrasonic Nondestructive Evaluation

Karpur

1992

Review of Progress in Quantitative Nondestructive Evaluation

View full text Add to dashboard Cite

“…The methodology has been well documented in literature [4][5][6][7][8]. However, for the sake of completeness, abrief description of the technique follows.…”

Section: Background Information and Motivationmentioning

confidence: 99%

“…The 'N' frequency diverse signals so obtained are further processed using one of the algorithms of SSP. Further details of the method can be found in the literature [4,5].…”

Section: Background Information and Motivationmentioning

confidence: 99%

Section: Background Information and Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Split Spectrum Technique as a Preprocessor for Ultrasonic Nondestructive Evaluation

Karpur

1992

Review of Progress in Quantitative Nondestructive Evaluation

View full text Add to dashboard Cite

“…The quality parameter, which measures performance, is the SNR defined like in [13,14,24,25]: trace whole in the deviation standard area t in targe e peak valu SNR =…”

Section: Spike With Additive White Gaussian Noisementioning

confidence: 99%

Noise reduction using wavelet cycle spinning: analysis of useful periodicities in the z-transform domain

Rodríguez-Hernández

Emeterio²

2015

SIViP

View full text Add to dashboard Cite

Robust Signal Processing for Material Noise Suppression in Ultrasonic Nondestructive Testing

Ericsson

Stepinski

1993

Review of Progress in Quantitative Nondestructive Evaluation

View full text Add to dashboard Cite

Ultrasonic nondestructive inspection of materials is often limited by the presence of backscattered echoes from the material structure, known as material or grain noise. The material noise can be difficult to distinguish from flaw echoes because their spectra overlap to a large extent. Due to the overlapping, application of conventional linear filters is generally not adequate for attenuating this type of noise. However, a suitable choice of the inspection frequency will cause the grain response to be considerable more noncoherent than the flaw response. This property arise from the fact that the material noise can be considered as an interference pattern made up of unresolved scatterers, while the flaw echoes will bear more resemblance to specular reflections. The implication of this difference is that the material noise can be suppressed by means of frequency diversity techniques which take advantage of its noncoherent nature. The desired frequency diverse signals may be obtained either by transmitting several pulses at slightly different frequencies or by using signal processing to create a set of signals from a single transmitted (broadband) pulse. The class of processing techniques used in the latter case will be referred to as Quasi Frequency Diversity (QFD) algorithms. The most renowned QFD algorithm is the Split Spectrum Processing (SSP) [1,2] which was developed about a decade ago. Through experimental verification the possibilities and limitations of the SSP have become evident. In order to avoid the drawbacks of the SSP we have developed a novel algorithm, which we refer to as Cut Spectrum Processing (CSP). In this paper the CSP algorithm is introduced and its operation is illustrated by an example.

show abstract

Split spectrum processing: optimizing the processing parameters using minimization

Cited by 50 publications

References 3 publications

Split Spectrum Technique as a Preprocessor for Ultrasonic Nondestructive Evaluation

Split Spectrum Technique as a Preprocessor for Ultrasonic Nondestructive Evaluation

Noise reduction using wavelet cycle spinning: analysis of useful periodicities in the z-transform domain

Robust Signal Processing for Material Noise Suppression in Ultrasonic Nondestructive Testing

Contact Info

Product

Resources

About