• Journal of the Korean Society for Nondestructive Testing
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• v.7 no.2
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• pp.8-15
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• 1988

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. A technique for suppression of grain echoes has also been devised which takes advantage of the fact that the grain echo amplitude changes with the frequency of the incident ultrasound whereas the flaw echo amplitude does not. The combination of this technique and the new flaw detection system greatly improve the capabilities of ultrasonic evaluation of large grain materials.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.113-118
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• 2010

The split spectrum processing algorithm of an ultrasonic wave on the tire was studied for the damage detection of a driving vehicle's tire. The processing results of normal and damaged tire was compared using the split spectrum algorithm to estimate the maximum value. The result that used Auto-correlation in case of damaged tire, the damage feature point is detected during 81ms intervals at a speed of 100km/h and during 162ms periodicity at a speed of 50km/h. This results was meaned the possibility for the tire's damage decision by damaging material with using periodicity feature point of tire damage according to vehicle speed.

• The Journal of the Acoustical Society of Korea
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• v.14 no.6
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• pp.27-31
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• 1995

In this paper, the determination method of available bandwidth for automation of the split-spectrum processing(SSP) has been studied. The SSP is used for the visibility enhancement of the ultrasonic signal with grain noise. Even though the SSP has proved useful in signal-to-noise ratio enhancement, its application and automation have been limited due to ambiguity in the determination of available bandwidth. Until recently, it is the usual practice to optimize the available bandwidth by trial and error. The spectral histogram is the statistical distribution of the spectral windows that is selected by the minimization algorithm with the whole band of the spectrum of the received ultrasonic signal. Since the available bandwidth can be determined adaptively using spectral histogram, this method can be used for automation of the SSP. In order to evaluate the determination technique of the available bandwidth using spectral histogram, this method is applied to experimental ultrasonic data. The experimental results show that the spectral histogram is an efficient method for determination of the available bandwidth and automation of the SSP.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.2
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• pp.32-40
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• 1994

In this study by using EMAT(electro magnetic acoustic transducer)the artificial slit is installed on 12B-SUS pipe test piece. By making 4 cycle SH-burst (EMA) incidence to 45 .deg. angle, the signal data of pulse, received from EMAT are translated into digital-signal-processing- method SSP(Split Spectrum Processing) and Deconvolution method. The main conclusions obtained are as follows; (1) the signal data received from EMAT are translated with digital signal proc- essing of SSP-method and Deconvolution-method and this method shows exellent results more than Ultrasonic testing method does; (2) noise can well be removed by SSP with signal data, and resolution and S/N ratio are advanced; (3) when used with Ultrasonic wave general stainless steel has proporties of multiscattering and reflection phenomena, but resolution is progressed by using Deconvolution method;and (4) as addition-averaging-processing mumber is increasing, the resolution and S/N ratio are improved and the satisfactory signal is obtained.

• Smart Structures and Systems
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• v.10 no.3
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• pp.253-269
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• 2012

A split spectrum processing (SSP) method is proposed to accurately determine the time-of-flight (ToF) of damage-scattered waves by comparing the instantaneous amplitude variation degree (IAVD) of a wave signal captured from a damage case with that from the benchmark. The fundamental symmetrical ($S_0$) mode in aluminum plates without and with a notch is assessed. The efficiency of the proposed SSP method and Hilbert transform in determining the ToF of damage-scattered $S_0$ mode is evaluated for damage identification when the wave signals are severely contaminated by noise. Broadband noise can overwhelm damage-scattered wave signals in the time domain, and the Hilbert transform is only competent for determining the ToF of damage-scattered $S_0$ mode in a noise-free condition. However, the calibrated IAVD of the captured wave signal is minimally affected by noise, and the proposed SSP method is capable of determining the ToF of damage-scattered $S_0$ mode accurately even though the captured wave signal is severely contaminated by broadband noise, leading to the successful identification of damage (within an error on the order of the damage size) using a triangulation algorithm.

• Journal of the Korean Society for Nondestructive Testing
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• v.16 no.1
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• pp.1-9
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• 1996

Many signal-processing techniques have been found to be useful in ultrasonic and nondestructive evaluation. Among the most popular techniques are signal averaging, spatial compounding, matched filters and homomorphic processing. One of the significant new process is split-spectrum processing(SSP), which can be equally useful in signal-to-noise ratio(SNR) improvement and grain characterization in several specimens. The purpose of this paper is to explore the utility of SSP in ultrasonic NDE. A wide variety of engineering problems are reviewed, and suggestions for implementation of the technique are provided. SSP uses the frequency-dependent response of the interfering coherent noise produced by unresolvable scatters in the resolution range cell of a transducer. It is implemented by splitting the frequency spectrum of the received signal by using gaussian bandpass filter. The theoretical basis for the potential of SSP for grain characterization in SUS 304 material is discussed, and some experimental evidence for the feasibility of the approach is presented. Results of SNR enhancement in signals obtained from real four samples of SUS 304. The influence of various processing parameters on the performance of the processing technique is also discussed. The minimization algorithm, which provides an excellent SNR enhancement when used either in conjunction with other SSP algorithms like polarity-check or by itself, is also presented.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.11a
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• pp.359-364
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• 2004

This paper deals with the comparison of signal processing techniques of ultrasonic data. The goal of signal processing is the ultrasonic speckle suppression and the visibility enhancement of flaw-reflected ultrasonic echo. The performance of conventional SSP(split spectrum processing) method and the wavelet denoising method are compared and discussed for tested ultrasonic data. Tested ultrasonic data obtained from the weld area of centrifugal-casted stainless steel material and safe-ending material with holes and notch of variable depths are presented. In experimental results, the outputs of wavelet-based denoising method show the clear and sharp peaks at the positions of flaw-reflected echos comparing with those of SSP method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.50-57
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• 1994

In the non-destructive evaluation techniques using ultrasonic signal, backscattering noise from grain interface decreases the SNR of received signal. In this paper, SSP(split-spectrum processing) based on the constant FBR decomposition method has been applied to enhance the SNR. This algorithm helps to find optimal parameters of filter bank through a simple theory and has an advantage that reduce the signal processing time compared with the conventional constant bandwidth decomposition method. In this experiment, the 304 stainless steel sample is heat-treated and received ultrasonic signal is processed by SSP using the constand bandwidth decomposition method and the constand FBR decomposition method enhanced the SNR by 1.4 dB and reduced the required number of filters by 4 compared with the constant bandwidth decomposition method.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.81-89
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• 1996

It is very important for ultrasonic test method to evaluate the integrity of the class I components in nuclear power plants. However, as the rltrasonic test is affected by internal structures and configurations of test materials, backscattering, that is, time invariant noise is generated in large grain size materials. Due to the above reason, the received signal results in low signal to noise(S/N) ratio. Split spectrum processing(SSP) technique is effective to suppress the grain noise. The conventional SSP technique. however, has been applied to unique algorithm. This paper shows that MPO(minimization and polarity threshold) algorithm which two algorithms are applied simulatancously, was utilized, the signal processing time was shorten by using the new constant-Q SSP with the FIR filter which frequency to bandwidth ratio is constant and the optimum parameters were analysed for the signal processing to longitudinal wave and shear wave with the same requirements of inspection on nuclear power plant site. Moreover, the new ultrasonic test instrument, the reference block of the same product form and material specification, stainless stell test specimens and copper test specimens block of the same fabricated for the application of new SSP technique. As the result of experimental test with new ultrasonic test instrument and test specimens, the signal to noise ratio was improved by appying the new SSP technique.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1753-1761
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• 2014

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).