Signal processing for the detection of multiple imperfection echoes drowned in the structural noise

Drai, Redouane; Benammar, Abdessalem; Benchaala, A.

doi:10.1016/j.ultras.2004.01.060

Cited by 8 publications

(4 citation statements)

References 6 publications

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“…Widely used methods at the present time are split spectrum processing [3][4][5][6][7], wavelet method [8][9][10][11][12][13][14][15][16], the high resolution pursuit (HRP) [17][18], and the chirplet transform [19][20]. The results are presented in various forms, so a direct comparison is very difficult.…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic Flaw Detection in Composite Materials Using SSP-MPSD Algorithm

Benammar¹,

Drai²

2014

Journal of Electrical Engineering and Technology

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-Due to the inherent inhomogeneous and anisotropy nature of the composite materials, the detection of internal defects in these materials with non-destructive techniques is an important requirement both for quality checks during the production phase and in service inspection during maintenance operations. The estimation of the time-of-arrival (TOA) and/or time-of-flight (TOF) of the ultrasonic echoes is essential in ultrasonic non-destructive testing (NDT). In this paper, we used split-spectrum processing (SSP) combined with matching pursuit signal decomposition (MPSD) to develop a dedicated ultrasonic detection system. SSP algorithm is used for Signal-to-Noise Ratio (SNR) enhancement, and the MPSD algorithm is used to decompose backscattered signals into a linear expansion of chirplet echoes and estimate the chirplet parameters. Therefore, the combination of SSP and MPSD (SSP-MPSD) presents a powerful technique for ultrasonic NDT. The SSP algorithm is achieved by using Gaussian band pass filters. Then, MPSD algorithm uses the Maximum Likelihood Estimation. The good performance of the proposed method is experimentally verified using ultrasonic traces acquired from three specimens of carbon fibre reinforced polymer multi-layered composite materials (CFRP).

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Section: Introductionmentioning

confidence: 99%

Ultrasonic Flaw Detection in Composite Materials Using SSP-MPSD Algorithm

Benammar¹,

Drai²

2014

Journal of Electrical Engineering and Technology

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“…In general, many signal/image processing algorithms have been developed for NDT and medical diagnosis in flaws, anomalies detection such as split spectrum processing (Drai, Benammar, & Benchaala, 2004;Gronningsaeter, Angelsen, Heimdal, & Torp, 1996;Tian, Li, & Bilgutay, 1995), wavelet denoising (Zhang, Zhang, & Wang, 2000), adaptive filtering (Zhu & Weight, 1994), time-shift compensation and spatial compounding (Laceld, Pilkington, & Wang, 2004). These algorithms are designed to increase the signalto-noise ratio (SNR), in which the noise due to coarse grains and blood red cells is assumed non-correlated with the signals.…”

Section: Introductionmentioning

confidence: 99%

Detection of occluded small objects in glass bottles filled with beverages via ultrasound center frequency tracing

Zhao

Basir

Mittal

2009

LWT - Food Science and Technology

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“…Such field covers the split spectrum technique (3,4) , adaptive time-frequency decomposition (5) , neural networks (6) , WignerVille distribution (7,8) , wavelet transform (9,10) and HilbertHuang (11,12) transform. Development of novel NDT methods and optimisation of signal processing algorithms may be simplified using adequate numerical models of the testing medium.…”

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confidence: 99%