scholarly journals Digital Filtering Techniques for Performance Improvement of Golay Coded TDM-FBG Sensor

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4299
Author(s):  
Mohamed M. Elgaud ◽  
Mohd Saiful Dzulkefly Zan ◽  
Abdulfatah A. G. Abushagur ◽  
Abdulwahhab E. Hamzah ◽  
Mohd Hadri Hafiz Mokhtar ◽  
...  
Keyword(s):  
High Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Digital Filtering ◽  
Signal Shape ◽  
Fbg Sensor ◽  
Filtering Technique ◽  
Fbg Sensors ◽  
Golay Codes ◽  
The Individual ◽  
Filtering Techniques

For almost a half-decade, the unique autocorrelation properties of Golay complementary pairs (GCP) have added a significant value to the key performance of conventional time-domain multiplexed fiber Bragg grating sensors (TDM-FBGs). However, the employment of the unipolar form of Golay coded TDM-FBG has suffered from several performance flaws, such as limited improvement of the signal-to-noise ratio (SNIR), noisy backgrounds, and distorted signals. Therefore, we propose and experimentally implement several digital filtering techniques to mitigate such limitations. Moving averages (MA), Savitzky–Golay (SG), and moving median (MM) filters were deployed to process the signals from two low reflectance FBG sensors located after around 16 km of fiber. The first part of the experiment discussed the sole deployment of Golay codes from 4 bits to 256 bits in the TDM-FBG sensor. As a result, the total SNIR of around 8.8 dB was experimentally confirmed for the longest 256-bit code. Furthermore, the individual deployment of MA, MM, and SG filters within the mentioned decoded sequences secured a further significant increase in SNIR of around 4, 3.5, and 3 dB, respectively. Thus, the deployment of the filtering technique alone resulted in at least four times faster measurement time (equivalent to 3 dB SNIR). Overall, the experimental analysis confirmed that MM outperformed the other two techniques in better signal shape, fastest signal transition time, comparable SNIR, and capability to maintain high spatial resolution.

Optimization of the proposed hybrid denoising technique to overcome over-filtering issue

2019 ◽  
Vol 64 (5) ◽  
pp. 601-618 ◽  
Author(s):  
Sumit Kushwaha ◽  
Rabindra Kumar Singh
Keyword(s):  
Signal To Noise Ratio ◽  
Design Parameters ◽  
Band Pass Filter ◽  
Hybrid Filter ◽  
Signal To Noise ◽  
Pass Filter ◽  
Adaptive Wavelet ◽  
Filtering Technique ◽  
Noise Ratio ◽  
Filtering Techniques

Abstract Image denoising has become a crucial task in medical ultrasound (US) imaging due to the presence of speckle or multiplicative noise and additive Gaussian noise. Recently, several denoising techniques such as adaptive wavelet thresholding & joint bilateral (AWT + JB) filter, adaptive fuzzy switching weighted mean (AFSWM) filter and median patch-based locally optimal Wiener (MPBLOW) filter have been proposed to remove the speckle noise. However, these denoising techniques were found to remove noise along with the essential parts of the actual image data which is known as over-filtering. Thereby, it reduces the accuracy of the recognition process. In this paper, a new hybrid filter technique is proposed by combining anisotropic diffusion (AD) with Butterworth band pass filter to overcome over-filtering of the image. In addition, the performance of the proposed hybrid filter and its design parameters are enhanced using the particle swarm optimization (PSO) algorithm. The simulation results show that the proposed filtering technique achieves a better denoising performance when compared with other filtering techniques in terms of peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), structural similarity index (SSIM) and edge preservation index (EPI). Moreover, the results validated that the proposed filtering technique using PSO achieves effective performance than using the harmony search algorithm (HSA) and other filtering techniques.

A Comparative Study of Digital Filtering Techniques in Ultrasound and Carotid Bifurcation Atherosclerosis

2018 ◽  
Vol 1 (1) ◽  
pp. 5-12
Author(s):  
Adriana Milășan ◽  
◽  
Cristian Molder ◽  
Silviu Dumitrescu ◽  
◽  
...  
Keyword(s):  
Comparative Study ◽  
Digital Filtering ◽  
Carotid Bifurcation ◽  
Filtering Techniques

scholarly journals A Blended Sea Ice Concentration Product from AMSR2 and VIIRS

2021 ◽  
Vol 13 (15) ◽  
pp. 2982
Author(s):  
Richard Dworak ◽  
Yinghui Liu ◽  
Jeffrey Key ◽  
Walter N. Meier
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Infrared Imaging ◽  
High Spatial Resolution ◽  
Sea Ice Concentration ◽  
Clear Sky ◽  
Ice Concentration ◽  
Best Linear Unbiased ◽  
The Individual ◽  
Sky Conditions

An effective blended Sea-Ice Concentration (SIC) product has been developed that utilizes ice concentrations from passive microwave and visible/infrared satellite instruments, specifically the Advanced Microwave Scanning Radiometer-2 (AMSR2) and the Visible Infrared Imaging Radiometer Suite (VIIRS). The blending takes advantage of the all-sky capability of the AMSR2 sensor and the high spatial resolution of VIIRS, though it utilizes only the clear sky characteristics of VIIRS. After both VIIRS and AMSR2 images are remapped to a 1 km EASE-Grid version 2, a Best Linear Unbiased Estimator (BLUE) method is used to combine the AMSR2 and VIIRS SIC for a blended product at 1 km resolution under clear-sky conditions. Under cloudy-sky conditions the AMSR2 SIC with bias correction is used. For validation, high spatial resolution Landsat data are collocated with VIIRS and AMSR2 from 1 February 2017 to 31 October 2019. Bias, standard deviation, and root mean squared errors are calculated for the SICs of VIIRS, AMSR2, and the blended field. The blended SIC outperforms the individual VIIRS and AMSR2 SICs. The higher spatial resolution VIIRS data provide beneficial information to improve upon AMSR2 SIC under clear-sky conditions, especially during the summer melt season, as the AMSR2 SIC has a consistent negative bias near and above the melting point.

scholarly journals Intensity and Wavelength Division Multiplexing FBG Sensor System Using a Raman Amplifier and Extreme Learning Machine

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yibeltal Chanie Manie ◽  
Run-Kai Shiu ◽  
Peng-Chun Peng ◽  
Bao-Yi Guo ◽  
Mekuanint Agegnehu Bitew ◽  
...  
Keyword(s):  
Extreme Learning Machine ◽  
Wavelength Division Multiplexing ◽  
Sensor System ◽  
Bragg Wavelength ◽  
Wavelength Division ◽  
Raman Amplifier ◽  
Fbg Sensor ◽  
Transmission Distance ◽  
Fbg Sensors ◽  
Learning Machine

A fiber Bragg grating (FBG) sensor is a favorable sensor in measuring strain, pressure, vibration, and temperature in different applications, such as in smart structures, wind turbines, aerospace, industry, military, medical centers, and civil engineering. FBG sensors have the following advantages: immune to electromagnetic interference, light weight, small size, flexible, stretchable, highly accurate, longer stability, and capable in measuring ultra-high-speed events. In this paper, we propose and demonstrate an intensity and wavelength division multiplexing (IWDM) FBG sensor system using a Raman amplifier and extreme learning machine (ELM). We use an IWDM technique to increase the number of FBG sensors. As the number of FBG sensors increases and the spectra of two or more FBGs are overlapped, a conventional peak detection (CPD) method is unappropriate to detect the central Bragg wavelength of each FBG sensor. To solve this problem, we use ELM techniques. An ELM is used to accurately detect the central Bragg wavelength of each FBG sensor even when the spectra of FBGs are partially or fully overlapped. Moreover, a Raman amplifier is added to a fiber span to generate a gain medium within the transmission fiber, which amplifies the signal and compensates for the signal losses. The transmission distance and the sensing signal quality increase when the Raman pump power increases. The experimental results revealed that a Raman amplifier compensates for the signal losses and provides a stable sensing output even beyond a 45 km transmission distance. We achieve a remote sensing of strain measurement using a 45 km single-mode fiber (SMF). Furthermore, the well-trained ELM wavelength detection methods accurately detect the central Bragg wavelengths of FBG sensors when the two FBG spectra are fully overlapped.

Investigation on Temperature Compensation of Fiber Bragg Grating Sensors for Hull Monitoring

2018 ◽  
Author(s):  
Ruiqi Ma ◽  
Guoqing Feng ◽  
Huilong Ren ◽  
Peng Fu ◽  
Shuang Wu ◽  
...  
Keyword(s):  
Thermal Expansion ◽  
Fiber Bragg Grating ◽  
Temperature Compensation ◽  
Compensation Method ◽  
Bragg Grating ◽  
Theoretical Derivation ◽  
Temperature Changes ◽  
Hull Girder ◽  
Fbg Sensor ◽  
Fbg Sensors

Hull monitoring system with Fiber Bragg Grating (FBG) sensors increasingly receives people’s attentions. However, for the ship hull monitoring, the deformation of hull girder changes a lot as is subjected to a huge temperature variation. Therefore, the compensation method with only FBG temperature self-correction is not suitable for the hull monitoring sensors because no material thermal expansion effects are reasonably included. In this paper, the new compensation method of hull monitoring FBG sensor based on the sensor theory with both FBG temperature self-correction and steel thermal expansion effects correction is studied. The coupled compensation method suitable for hull monitoring sensor is obtained by theoretical derivation. As the comparison, the coupled compensation experiment was carried out. The results show that the relative error under the temperature compensation method is large in the case of drastic strain and temperature changes, and the correction results of the tested method will be closer to the true level.

scholarly journals Disentangling age-dependent DNA methylation: deterministic, stochastic, and nonlinear

2020 ◽  
Author(s):  
O. Vershinina ◽  
M. Ivanchenko ◽  
M.G. Bacalini ◽  
A. Zaikin ◽  
C. Franceschi
Keyword(s):  
Dna Methylation ◽  
Environmental Factors ◽  
Methylation Level ◽  
Signal To Noise Ratio ◽  
Cross Sectional ◽  
Ample Evidence ◽  
Systematic Assessment ◽  
Relative Contribution ◽  
Age Dependent ◽  
The Individual

ABSTRACTDNA methylation variability arises due to concurrent genetic and environmental influences. Each of them is a mixture of regular and noisy sources, whose relative contribution has not been satisfactorily understood yet. We conduct a systematic assessment of the age-dependent methylation by the signal-to-noise ratio and identify a wealth of “deterministic” CpG probes (about 90%), whose methylation variability likely originates due to genetic and general environmental factors. The remaining 10% of “stochastic” CpG probes are arguably governed by the biological noise or incidental environmental factors. Investigating the mathematical functional relationship between methylation levels and variability, we find that in about 90% of the age-associated differentially methylated positions, the variability changes as the square of the methylation level, whereas in the most of the remaining cases the dependence is linear. Furthermore, we demonstrate that the methylation level itself in more than 15% cases varies nonlinearly with age (according to the power law), in contrast to the previously assumed linear changes. Our findings present ample evidence of the ubiquity of strong DNA methylation regulation, resulting in the individual age-dependent and nonlinear methylation trajectories, whose divergence explains the cross-sectional variability. It may also serve a basis for constructing novel nonlinear epigenetic clocks.

scholarly journals Methods for mutual time delay estimation of wideband signals based on nonlinear digital filtering

2019 ◽  
Vol 30 ◽  
pp. 03008
Author(s):  
Roman Ershov ◽  
Oleg Morozov
Keyword(s):  
Time Delay ◽  
Communication Systems ◽  
Satellite Communication ◽  
Signal To Noise Ratio ◽  
Digital Filtering ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Wideband Signals ◽  
Correlation Processing

Methods for mutual time delay estimation of wideband signals propagating in satellite communication systems are proposed. The signals are propagated in different channels and received with low signal-to-noise ratio. A characteristic feature of satellite channel is the presence of the Doppler Effect, which leads to a shift and scaling the signal spectrums. The proposed approaches are based on the separation of narrow-band channels from the studied signals, using non-linear digital filtering algorithms in each channel, and subsequent optimal (correlation) processing. The accuracy of the proposed methods and the reliability of the determination of time delay are investigated.

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