Application of Phase-Sensitivity Detector in Air-Coupled Ultrasonic Testing

2012 ◽  
Vol 170-173 ◽  
pp. 3125-3129
Author(s):  
Wei Dong ◽  
Zi Wei Zhou ◽  
Zheng Gan Zhou
Keyword(s):  
Ultrasonic Testing ◽  
Testing Effect ◽  
Signal To Noise Ratio ◽  
Research Result ◽  
Phase Sensitivity ◽  
Signal To Noise ◽  
Detection Technology ◽  
Long Time ◽  
Phase Signal ◽  
Sensitivity Detection

The signal to noise ration of air-coupled ultrasonic testing is very poor and there is long time pulse residue, so it need adopt appropriate signal processing method to enhancing the SNR of received signal. Factors, which affect the received signal in ultrasonic testing process, is analyzed, phase sensitivity detection technology is presented to process the received signal, and ultrasonic testing information can be acquired by the calculation of phase signal. The principle of super-heterodyne receiver and phase sensitivity detector is introduced; some problem which should be pay attention in ultrasonic testing process is explained. Based on the research result, air-coupled ultrasonic testing system with phase sensitivity detector is constituted. Experiment results of image testing on carbon fiber reinforced plastic plate indicated that, phase sensitivity detection technology can improved signal to noise ratio of system and testing effect in evidence.

Micro-Size Damage Adaptive Detection Technology Based on Local Signal-to-Noise Ratio

2018 ◽  
Vol 45 (7) ◽  
pp. 0704001
Author(s):  
唐如欲 Tang Ruyu ◽  
刘德安 Liu Dean ◽  
朱健强 Zhu Jianqiang
Keyword(s):  
Signal To Noise Ratio ◽  
Adaptive Detection ◽  
Signal To Noise ◽  
Detection Technology ◽  
Noise Ratio

Improving signal-to-noise ratio in ultrasonic testing

2016 ◽  
Vol 52 (6) ◽  
pp. 310-314
Author(s):  
I. A. Krivosheev ◽  
M. I. Ignat’eva ◽  
A. I. Shamurina
Keyword(s):  
Ultrasonic Testing ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Receiver phase alignment using fitted SVD derived sensitivities from routine prescans

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256700
Author(s):  
Olivia W. Stanley ◽  
Ravi S. Menon ◽  
L. Martyn Klassen
Keyword(s):  
Singular Value Decomposition ◽  
Radio Frequency ◽  
Signal To Noise Ratio ◽  
Singular Value ◽  
7 Tesla ◽  
Signal To Noise ◽  
Phase Signal ◽  
Noise Ratio ◽  
Value Decomposition ◽  
Svd Method

Magnetic resonance imaging radio frequency arrays are composed of multiple receive coils that have their signals combined to form an image. Combination requires an estimate of the radio frequency coil sensitivities to align signal phases and prevent destructive interference. At lower fields this can be accomplished using a uniform physical reference coil. However, at higher fields, uniform volume coils are lacking and, when available, suffer from regions of low receive sensitivity that result in poor sensitivity estimation and combination. Several approaches exist that do not require a physical reference coil but require manual intervention, specific prescans, or must be completed post-acquisition. This makes these methods impractical for large multi-volume datasets such as those collected for novel types of functional MRI or quantitative susceptibility mapping, where magnitude and phase are important. This pilot study proposes a fitted SVD method which utilizes existing combination methods to create a phase sensitive combination method targeted at large multi-volume datasets. This method uses any multi-image prescan to calculate the relative receive sensitivities using voxel-wise singular value decomposition. These relative sensitivities are fitted to the solid harmonics using an iterative least squares fitting algorithm. Fits of the relative sensitivities are used to align the phases of the receive coils and improve combination in subsequent acquisitions during the imaging session. This method is compared against existing approaches in the human brain at 7 Tesla by examining the combined data for the presence of singularities and changes in phase signal-to-noise ratio. Two additional applications of the method are also explored, using the fitted SVD method in an asymmetrical coil and in a case with subject motion. The fitted SVD method produces singularity-free images and recovers between 95–100% of the phase signal-to-noise ratio depending on the prescan data resolution. Using solid harmonic fitting to interpolate singular value decomposition derived receive sensitivities from existing prescans allows the fitted SVD method to be used on all acquisitions within a session without increasing exam duration. Our fitted SVD method is able to combine imaging datasets accurately without supervision during online reconstruction.

A Novel Biometric Image Enhancement Approach With the Hybridization of Undecimated Wavelet Transform and Deep Autoencoder

2020 ◽  
pp. 245-269
Author(s):  
Sasirekha K. ◽  
Thangavel K.
Keyword(s):  
Wavelet Transform ◽  
Image Enhancement ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Mean Square ◽  
Signal To Noise ◽  
Undecimated Wavelet Transform ◽  
Long Time ◽  
Noise Ratio ◽  
Undecimated Wavelet

For a long time, image enhancement techniques have been widely used to improve the image quality in many image processing applications. Recently, deep learning models have been applied to image enhancement problems with great success. In the domain of biometric, fingerprint and face play a vital role to authenticate a person in the right way. Hence, the enhancement of these images significantly improves the recognition rate. In this chapter, undecimated wavelet transform (UDWT) and deep autoencoder are hydridized to enhance the quality of images. Initially, the images are decomposed with Daubechies wavelet filter. Then, deep autoencoder is trained to minimize the error between reconstructed and actual input. The experiments have been conducted on real-time fingerprint and face images collected from 150 subjects, each with 10 orientations. The signal to noise ratio (SNR), peak signal to noise ratio (PSNR), mean square error (MSE), and root mean square error (RMSE) have been computed and compared. It was observed that the proposed model produced a biometric image with high quality.

An Improved Algorithm for Estimating the Parameters of Polynomial-Phase Signals

2013 ◽  
Vol 380-384 ◽  
pp. 1350-1353
Author(s):  
Peng Fei Tang ◽  
Qian Qiang Lin ◽  
Bin Yuan ◽  
Zeng Ping Chen
Keyword(s):  
Radon Transform ◽  
Signal To Noise Ratio ◽  
Cubic Phase ◽  
Signal To Noise ◽  
Polynomial Phase ◽  
Polynomial Phase Signals ◽  
Phase Signal ◽  
Identifiability Problem ◽  
Cubic Phase Function ◽  
Theoretical Results

This paper presents an algorithm for estimating the parameters of polynomial-phase signals (PPSs). This algorithm combines the CPF-HAF method and Radon transform, and can be referred to as the Radon-CPF-HAF method. In the proposed algorithm, the HAF is first applied on the original PPS to produce a cubic phase signal, whose parameters are then estimated by the Radon transform of the cubic phase function for the derived cubic phase signal. As involving in lower order nonlinearity, the proposed algorithm outperforms the HAF in terms of the accuracy and signal-to-noise-ratio (SNR) threshold. When multicomponent PPSs are considered, the product version of the proposed algorithm removes the identifiability problem which the product version of the CPF-HAF (PCPF-HAF) suffers from. Computer simulations have been carried out to support the theoretical results.

scholarly journals Detection Spectrum Optimization of Stealth Aircraft Targets From a Space-based Infrared Platform

2021 ◽  
Author(s):  
Xinyue Ni ◽  
Shutian Yu ◽  
Xiaofeng Su ◽  
Fansheng Chen
Keyword(s):  
Detection System ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Central Wavelength ◽  
Detection Techniques ◽  
Detection Systems ◽  
Spectrum Detection ◽  
Detection Technology ◽  
Spectrum Optimization ◽  
Noise Ratio

Abstract Advances in infrared detection techniques require novel spectrum dynamic-modification strategies capable of sensing unprecedentedly low target radiant intensities. A conventional fixed-spectrum detection system cannot satisfy the effective detection of stealth aircraft targets due to complex Earth background clutter and atmospheric attenuation. Therefore, a detection method that can highlight aircraft targets is urgently needed to enhance stealth aircraft detectability. In this research, a spectrum set consisting of different bandwidths associated with a central wavelength is established. Furthermore, a signal-to-noise ratio of the stealth aircraft is computed using the established spectrum set. Finally, the optimal spectrum is selected according to the maximal signal-to-noise ratio from the spectrum set. Our numerical experiments and simulations further demonstrate that the proposed methodology can substantially strengthen the detection performance of stealth aircraft compared with traditional fixed-spectrum detection systems. This work on detection spectrum optimization paves the way to stealth aircraft detection and opens new vistas in the field of target detection technology.

Ultrasonic Testing Signal Denoising Based on Matching Pursuits

2013 ◽  
Vol 397-400 ◽  
pp. 2215-2218
Author(s):  
Xiu Li Du ◽  
Ying Hua Jiang
Keyword(s):  
White Noise ◽  
Ultrasonic Testing ◽  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Signal Denoising ◽  
Signal To Noise ◽  
Matching Pursuits ◽  
Testing Signal ◽  
Mp Method ◽  
The Relationship

When matching pursuits (MP) method was used for noise suppression of ultrasonic testing signals, the number of matched atoms affects the denoising performance. The relationship between the number of the matched atoms and denoising capability was analyzed, using the root mean square error (RMSE) and improvement of signal-to-noise ratio (SNR) to evaluate denoising performance. The simulated signals with white noise at different SNR and experimental signal with white noise and grain noise were analyzed respectively, and the results show that the MP method can remove the white noise and grain noise effectively. Moreover the best denoising performance can be arrived if the number of matched atoms is appropriate. At last, the selection principle of atoms number is given.

scholarly journals Research on Virtual Display of Wetsuit Based on CLO3D

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Haifeng Wang ◽  
Joung Hyung Cho
Keyword(s):  
Signal To Noise Ratio ◽  
Human Model ◽  
Signal To Noise ◽  
Synthesis Time ◽  
Information Synthesis ◽  
Dynamic Display ◽  
Long Time ◽  
Virtual Display ◽  
Noise Ratio ◽  
Output Interface

In order to overcome the problems of low signal-to-noise ratio in the information output interface and long time for information synthesis in the traditional virtual display method of clothing, a CLO3D-based virtual display method for wetsuit is designed in this study. The proposed method works as follows. Firstly, it analyzes the categories and functional characteristics of the wetsuit and the virtual display process of the CLO3D software. In the second step, the design of the proposed method for the process of data collection and fusion of the wetsuit design is made. In the subsequent steps, human model is established, designs are made for the style and modeling, simulation is made for the pattern and color of the wetsuit fabric, and dynamic display is made. Experimental results show that the signal-to-noise ratio (SNR) of the information output interface of the proposed method is above 75 dB, and the maximum SNR can reach 80.5 dB, and the information synthesis time varies between 32 min and 47 min, indicating that the proposed method is more efficient and effective.

scholarly journals Inductive Magnetic Nanoparticle Sensor Based on Microfluidic Chip Oil Detection Technology

Micromachines ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 183 ◽  
Author(s):  
Chenzhao Bai ◽  
Hongpeng Zhang ◽  
Lin Zeng ◽  
Xupeng Zhao ◽  
Laihao Ma
Keyword(s):  
Magnetic Field ◽  
Magnetic Nanoparticles ◽  
Fault Diagnosis ◽  
Wear Debris ◽  
Magnetic Nanoparticle ◽  
Signal To Noise Ratio ◽  
Solenoid Coil ◽  
Signal To Noise ◽  
Detection Technology ◽  
Ferromagnetic Particles

The wear debris in hydraulic oil or lubricating oil has a wealth of equipment operating information, which is an important basis for large mechanical equipment detection and fault diagnosis. Based on traditional inductive oil detection technology, magnetic nanoparticles are exploited in this paper. A new inductive oil detection sensor is designed based on the characteristics of magnetic nanoparticles. The sensor improves detection sensitivity based on distinguishing between ferromagnetic and non-ferromagnetic wear debris. Magnetic nanoparticles increase the internal magnetic field strength of the solenoid coil and the stability of the internal magnetic field of the solenoid coil. During the experiment, the optimal position of the sensor microchannel was first determined, then the effect of the magnetic nanoparticles on the sensor’s detection was confirmed, and finally the concentration ratio of the mixture was determined. The experimental results show that the inductive oil detection sensor made of magnetic nanoparticle material had a higher detection effect, and the signal-to-noise ratio (SNR) of 20–70 μm ferromagnetic particles was increased by 20%–25%. The detection signal-to-noise ratio (SNR) of 80–130 μm non-ferromagnetic particles was increased by 16%–20%. The application of magnetic nanoparticles is a new method in the field of oil detection, which is of great significance for fault diagnosis and the life prediction of hydraulic systems.

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