scholarly journals Casting Blanks Cleanliness Evaluation Based on Ultrasonic Microscopy and Morphological Filtering

Metals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 796
Author(s):  
Heng Ding ◽  
Qingting Qian ◽  
Xue Li ◽  
Zhu Wang ◽  
Min Li
Keyword(s):  
Signal To Noise Ratio ◽  
New Technology ◽  
Continuous Caster ◽  
Internal Quality ◽  
Ultrasound Images ◽  
Morphological Filtering ◽  
Ultrasound Technology ◽  
Metal Materials ◽  
Better Than

The cleanliness of the casting blanks could seriously affect the quality of downstream products. Recently, ultrasound technology has been introduced to detect the inclusions in metal materials. However, due to the anisotropy of the material crystal, the ultrasonic wave has the characteristics of multiple scattering and refraction in its propagation process. This makes it difficult to evaluate the casting blanks cleanliness effectively, for the inclusion echoes are submerged in the background noise. Therefore, the ultrasonic microscope is innovatively proposed to carry out efficient scanning on the casting blanks. In the meantime, the morphological filtering algorithm has the advantages of fewer parameters and faster calculation speed which can be used to increase the signal-to-noise ratio of ultrasound images and extract the defect features more efficiently. In order to verify the effectiveness of the proposed method, specimens were taken from three strands of continuous caster for detection and analysis. The experimental results show that the second strand has the best quality and the cleanliness is 2.2/mm3, which is obviously better than the other two strands. This method will provide a new technology for the quantitative evaluation of the internal quality of the casting blanks.

scholarly journals Deep Learning-Based Wavelet Threshold Function Optimization on Noise Reduction in Ultrasound Images

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Zhuxiang Shen ◽  
Wei Li ◽  
Hui Han
Keyword(s):  
Wavelet Transform ◽  
Image Denoising ◽  
Similarity Index ◽  
Speckle Noise ◽  
Disease Diagnosis ◽  
Function Optimization ◽  
Threshold Function ◽  
Ultrasound Images ◽  
Better Than

To explore the utilization of the convolutional neural network (CNN) and wavelet transform in ultrasonic image denoising and the influence of the optimized wavelet threshold function (WTF) algorithm on image denoising, in this exploration, first, the imaging principle of ultrasound images is studied. Due to the limitation of the principle of ultrasound imaging, the inherent speckle noise will seriously affect the quality of ultrasound images. The denoising principle of the WTF based on the wavelet transform is analyzed. Based on the traditional threshold function algorithm, the optimized WTF algorithm is proposed and applied to the simulation experiment of ultrasound images. By comparing quantitatively and qualitatively with the traditional threshold function algorithm, the advantages of the optimized WTF algorithm are analyzed. The results suggest that the image is denoised by the optimized WTF. The mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM) of the images are 20.796 dB, 34.294 dB, and 0.672 dB, respectively. The denoising effect is better than the traditional threshold function. It can denoise the image to the maximum extent without losing the image information. In addition, in this exploration, the optimized function is applied to the actual medical image processing, and the ultrasound images of arteries and kidneys are denoised separately. It is found that the quality of the denoised image is better than that of the original image, and the extraction of effective information is more accurate. In summary, the optimized WTF algorithm can not only remove a lot of noise but also obtain better visual effect. It has important value in assisting doctors in disease diagnosis, so it can be widely applied in clinics.

scholarly journals ANALYSIS OF SPOT-6 DATA FUSION USING GRAM-SCHMIDT SPECTRAL SHARPENING ON RURAL AREAS

2014 ◽  
Vol 10 (2) ◽  
Author(s):  
Danang Surya Candra
Keyword(s):  
Data Fusion ◽  
Spatial Resolution ◽  
Rural Areas ◽  
Signal To Noise Ratio ◽  
Test Site ◽  
Multispectral Images ◽  
Fused Image ◽  
Pc Method ◽  
Better Than

Image fusion is a process to generate higher spatial resolution multispectral images by fusion of lower resolution multispectral images and higher resolution panchromatic images. It is used to generate not only visually appealing images but also provide detailed images to support applications in remote sensing field, including rural area. The aim of this study was to evaluate the performance of SPOT-6 data fusion using Gram-Schmidt Spectral Sharpening (GS) method on rural areas. GS method was compared with Principle Component Spectral Sharpening (PC) method to evaluate the reliability of GS method. In this study, the performance of GS was presented based on multispectral and panchromatic of SPOT-6 images. The spatial resolution of the multispectral (MS) image was enhanced by merging the high resolution Panchromatic (Pan) image in GS method. The fused image of GS and PC were assessed visually and statistically. Relative Mean Difference (RMD), Relative Variation Difference (RVD), and Peak Signal to Noise Ratio (PSNR) Index were used to assess the fused image statistically. The test sites of rural areas were devided into four main areas i.e., whole area, rice field area, forest area, and settlement. Based on the results, the visual quality of the fused image using GS method was better than using PC method. The color of the fused image using GS was better and more natural than using PC. In the statistical assessment, the RMD results of both methods were similar. In the RVD results, GS method was better then PC method especially in band 1 and band 3. GS method was better than PC method in PSNR result for each test site. It was observed that the Gram-Schmidt method provides the best performance for each band and test site. Thus, GS was a robust method for SPOT-6 data fusion especially on rural areas.

scholarly journals Electrocardiogram Baseline Wander Suppression Based on the Combination of Morphological and Wavelet Transformation Based Filtering

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Xiang-kui Wan ◽  
Haibo Wu ◽  
Fei Qiao ◽  
Feng-cong Li ◽  
Yan Li ◽  
...  
Keyword(s):  
Realistic Model ◽  
Suppression Effect ◽  
Ecg Signals ◽  
Morphological Filtering ◽  
Baseline Wander ◽  
Waveform Distortions ◽  
Electrocardiogram Ecg ◽  
Morphology Filter ◽  
Better Than

One of the major noise components in electrocardiogram (ECG) is the baseline wander (BW). Effective methods for suppressing BW include the wavelet-based (WT) and the mathematical morphological filtering-based (MMF) algorithms. However, the T waveform distortions introduced by the WT and the rectangular/trapezoidal distortions introduced by MMF degrade the quality of the output signal. Hence, in this study, we introduce a method by combining the MMF and WT to overcome the shortcomings of both existing methods. To demonstrate the effectiveness of the proposed method, artificial ECG signals containing a clinical BW are used for numerical simulation, and we also create a realistic model of baseline wander to compare the proposed method with other state-of-the-art methods commonly used in the literature. The results show that the BW suppression effect of the proposed method is better than that of the others. Also, the new method is capable of preserving the outline of the BW and avoiding waveform distortions caused by the morphology filter, thereby obtaining an enhanced quality of ECG.

scholarly journals Selective Route Based on SNR with Cross-Layer Scheme in Wireless Ad Hoc Network

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Istikmal ◽  
Adit Kurniawan ◽  
Hendrawan
Keyword(s):  
Routing Protocol ◽  
Ad Hoc ◽  
Signal To Noise Ratio ◽  
Cross Layer ◽  
Hop Count ◽  
Routing Overhead ◽  
Fifth Generation ◽  
Distance Vector ◽  
Better Than

In this study, we developed network and throughput formulation models and proposed new method of the routing protocol algorithm with a cross-layer scheme based on signal-to-noise ratio (SNR). This method is an enhancement of routing protocol ad hoc on-demand distance vector (AODV). This proposed scheme uses selective route based on the SNR threshold in the reverse route mechanism. We developed AODV SNR-selective route (AODV SNR-SR) for a mechanism better than AODV SNR, that is, the routing protocol that used average or sum of path SNR, and also better than AODV which is hop-count-based. We also used selective reverse route based on SNR mechanism, replacing the earlier method to avoid routing overhead. The simulation results show that AODV SNR-SR outperforms AODV SNR and AODV in terms of throughput, end-to-end delay, and routing overhead. This proposed method is expected to support Device-to-Device (D2D) communications that are concerned with the quality of the channel awareness in the development of the future Fifth Generation (5G).

scholarly journals HD SCAN – ULTRASOUND TECHNOLOGY FOR QUANTITATIVE EVALUATION OF THE INTERNAL QUALITY OF AS-CAST STEEL PRODUCTS

2017 ◽  
Author(s):  
Ernst Lindemann ◽  
Jochen Wans ◽  
Martin Klein ◽  
Tamara Gusarova ◽  
Oliver Hofmann
Keyword(s):  
Quantitative Evaluation ◽  
Cast Steel ◽  
Internal Quality ◽  
Ultrasound Technology

scholarly journals Image Denoising Using Multiwavelet Transform with Different Filters and Rules

2021 ◽  
Vol 15 (15) ◽  
pp. 140
Author(s):  
Muna Majeed Laftah
Keyword(s):  
Image Denoising ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Original Signal ◽  
Result Section ◽  
Switching Median Filter ◽  
Multiwavelet Transform ◽  
Denoised Image ◽  
Better Than

<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt&amp; pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by using Peak Signal to Noise Ratio (PSNR). Depend on the value of PSNR that explained in the result section; we conclude that the (Tri-State Median filter) is better than (Switching Median filter) in denoising image quality, according to the results of applying rules the result of the Shrinking rule for each filter shows that the best result using first the Bivariate Shrink.</p>

scholarly journals Validation of stratospheric and mesospheric ozone observed by SMILES from International Space Station

2013 ◽  
Vol 6 (9) ◽  
pp. 2311-2338 ◽  
Author(s):  
Y. Kasai ◽  
H. Sagawa ◽  
D. Kreyling ◽  
E. Dupuy ◽  
P. Baron ◽  
...  
Keyword(s):  
International Space Station ◽  
Signal To Noise Ratio ◽  
Space Station ◽  
Local Times ◽  
International Space ◽  
Order Of Magnitude ◽  
Mesospheric Ozone ◽  
Synchronous Orbit ◽  
Better Than

Abstract. We observed ozone (O3) in the vertical region between 250 and 0.0005 hPa (~ 12–96 km) using the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on the Japanese Experiment Module (JEM) of the International Space Station (ISS) between 12 October 2009 and 21 April 2010. The new 4 K superconducting heterodyne receiver technology of SMILES allowed us to obtain a one order of magnitude better signal-to-noise ratio for the O3 line observation compared to past spaceborne microwave instruments. The non-sun-synchronous orbit of the ISS allowed us to observe O3 at various local times. We assessed the quality of the vertical profiles of O3 in the 100–0.001 hPa (~ 16–90 km) region for the SMILES NICT Level 2 product version 2.1.5. The evaluation is based on four components: error analysis; internal comparisons of observations targeting three different instrumental setups for the same O3 625.371 GHz transition; internal comparisons of two different retrieval algorithms; and external comparisons for various local times with ozonesonde, satellite and balloon observations (ENVISAT/MIPAS, SCISAT/ACE-FTS, Odin/OSIRIS, Odin/SMR, Aura/MLS, TELIS). SMILES O3 data have an estimated absolute accuracy of better than 0.3 ppmv (3%) with a vertical resolution of 3–4 km over the 60 to 8 hPa range. The random error for a single measurement is better than the estimated systematic error, being less than 1, 2, and 7%, in the 40–1, 80–0.1, and 100–0.004 hPa pressure regions, respectively. SMILES O3 abundance was 10–20% lower than all other satellite measurements at 8–0.1 hPa due to an error arising from uncertainties of the tangent point information and the gain calibration for the intensity of the spectrum. SMILES O3 from observation frequency Band-B had better accuracy than that from Band-A. A two month period is required to accumulate measurements covering 24 h in local time of O3 profile. However such a dataset can also contain variation due to dynamical, seasonal, and latitudinal effects.

scholarly journals Validation of stratospheric and mesospheric ozone observed by SMILES from International Space Station

2013 ◽  
Vol 6 (2) ◽  
pp. 2643-2720 ◽  
Author(s):  
Y. Kasai ◽  
H. Sagawa ◽  
D. Kreyling ◽  
K. Suzuki ◽  
E. Dupuy ◽  
...  
Keyword(s):  
International Space Station ◽  
Signal To Noise Ratio ◽  
Space Station ◽  
Local Times ◽  
International Space ◽  
Calibration Problem ◽  
Order Of Magnitude ◽  
Synchronous Orbit ◽  
Better Than

Abstract. We observed the diurnal variation of ozone (O3) in the vertical region between 250 and 0.0005 hPa (~12–96 km) using the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on the Japanese Experiment Module (JEM) of the International Space Station (ISS) between 12 October 2009 and 21 April 2010. The new 4 K superconducting heterodyne receiver technology of SMILES allowed us to obtain a one order of magnitude better signal-to-noise ratio for the O3 line observation compared to past spaceborne microwave instruments. We assessed the quality of the vertical profiles of O3 in the 100–0.001 hP (~16–90 km) region for the SMILES NICT Level 2 product version 2.1.5. The evaluation is based on four components; error analysis; internal comparisons of observations targeting three different instrumental setups for the same O3 625.371 GHz transition; internal comparisons of two different retrieval algorithms; and external comparisons for various local times with ozonesonde, satellite and balloon observations (ENVISAT/MIPAS, SCISAT/ACE-FTS, Odin/OSIRIS, Odin/SMR, Aura/MLS, TELIS). SMILES O3 data have an estimated absolute accuracy of better than 0.3 ppmv (3%) with a vertical resolution of 3–4 km over the 60 to 8 hPa range. The random error for a single measurement is better than the estimated systematic error, being less than 1, 2, and 7%, in the 40–1, 80–0.1, and 100–0.004 hPa pressure region, respectively. SMILES O3 abundance was 10–20% lower than all other satellite measurements at 8–0.1 hPa due to an error arising from uncertainties of the tangent point information and the calibration problem for the intensity of the spectrum. The non sun-synchronous orbit of the ISS allowed us to observe O3 at various local times. A two month period is required to accumulate measurements covering 24 h in local time. However such a dataset can also contain variation due to dynamical, seasonal, and latitudinal effects.

scholarly journals Adaptive Noise Reduction of Scintigrams with a Wavelet Transform

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Koichi Ogawa ◽  
Masahiko Sakata ◽  
Yu Li
Keyword(s):  
Wavelet Transform ◽  
Noise Reduction ◽  
Signal To Noise Ratio ◽  
Poisson Noise ◽  
Denoising Method ◽  
Translation Invariant ◽  
Conventional Methods ◽  
Adaptive Noise ◽  
Better Than

The aim of this study was to eliminate the effect of Poisson noise in scintigrams with a wavelet thresholding method. We developed a new noise reduction method with a wavelet transform. The proposed method was a combination of the translation-invariant denoising method and our newly introduced denoising filter which was applicable for Poisson noise. To evaluate the validity of our proposed method, phantom images and scintigrams were used. The results with the phantom images showed that our method was better than conventional methods in terms of the peak signal-to-noise ratio by 3 dB. Quality of the scintigrams processed with our method was better than that with the conventional methods in terms of reducing Poisson noise while preserving edge components. The results demonstrated that the proposed method was effective for the reduction of Poisson noise in scintigrams.

Experimental Research on Technological Parameters of Magneto-Rheological Finishing for Metal Materials

2011 ◽  
Vol 411 ◽  
pp. 327-330
Author(s):  
Jia Hong Gao ◽  
Yan Yang ◽  
Zu Wen Ren
Keyword(s):  
Surface Roughness ◽  
Processing Time ◽  
New Technology ◽  
Technological Parameters ◽  
Workpiece Surface ◽  
Mr Fluids ◽  
Metal Materials ◽  
Magneto Rheological ◽  
Magnetic Filed

MRF (Magneto-rheological Finishing) is a kind of new technology which carries on fine polishing to the workpiece surface by using rheological property of MR fluids. A set of simple experimental equipment has been designed in this paper and magnet was selected for device forming magnetic filed. The main parameters of MRF which influence the surface quality of the metal material has been analyzed. The rule of the influence on surface roughness varying with several parameters has been summed up. The experiment results show that with the increase of magnetic field intensity, the value of surface roughness of workpiece decreases; the value increases with the increase of rotational velocity.The value of surface roughness of workpiece is in inverse proportion to the processing time. With the increase of time, the value of surface roughness of workpiece has been decreasing to basically stable after a certain amount of processing time.

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