scholarly journals Detection of radio signals against the background of strong electromagnetic noise in transport

2021 ◽  
Vol 2131 (5) ◽  
pp. 052046
Author(s):  
E Myasnikov ◽  
T Zaboronkova ◽  
L Kogan
Keyword(s):  
Background Noise ◽  
Nonlinear Function ◽  
High Sensitivity ◽  
Measured Signal ◽  
Mathematical Algorithm ◽  
Useful Signal ◽  
Random Components ◽  
Radio Signals ◽  
The Fourier Transform ◽  
Stochastic Phenomena

Abstract The problem of detecting a useful signal in the presence of a strong background noise is considered. To solve it, a statistical approach is used, based on a change in the level of chaos in the system when an additional random or deterministic process occurs, which is probabilistically independent from a set of stochastic phenomena that form background noise. It is shown that the occurrence of this process changes the level of entropy of the measured signal; this fact is the basis of the applied mathematical algorithm. It is based on the elements of the Fourier transform apparatus for the probability density with an appropriate choice of a nonlinear function of the random process under study. The proposed approach, based on variations in the randomness in the system in the presence of a useful signal, makes it possible to record its presence against the background of noise components even at low signal-to-noise ratios. The effectiveness of the method is confirmed both by theoretical justification and by the calculations presented in this work. The condition for the implementation of the technique described in the article, which does not impose restrictions on the studied physical fields and frequency ranges, is the comparability of the width of the probabilistic distribution of the desired useful signal with several intervals of discreteness of the measuring equipment. One of the results of this work is a high sensitivity to the emergence of independent random components.

Half division two-dimensional method for simple sinusoidal quantities parameters accurate measurement

2021 ◽  
pp. 16-21
Author(s):  
Kirill Yu. Solomentsev ◽  
Vyacheslav I. Lachin ◽  
Aleksandr E. Pasenchuk
Keyword(s):  
Measuring Instruments ◽  
Measured Signal ◽  
Two Dimensional ◽  
Measuring Device ◽  
New Approach ◽  
Precision Measuring ◽  
Useful Signal ◽  
Midpoint Method ◽  
Order Of Magnitude ◽  
Current Measuring

Several variants of half division two-dimensional method are proposed, which is the basis of a fundamentally new approach for constructing measuring instruments for sinusoidal or periodic electrical quantities. These measuring instruments are used in the diagnosis of electric power facilities. The most general variant, called midpoint method, is considered. The proposed midpoint method allows you to measure much smaller than using widespread methods, alternating currents or voltages, especially when changing the amplitude of the measured signal in very wide ranges, by 1–2 orders of magnitude. It is shown that using the midpoint method it is possible to suppress sinusoidal or periodic interference in the measuring path, in particular, to measure small alternating current when sinusoidal or periodic interference is 1–2 orders of magnitude higher than the useful signal. Based on the results of comparative tests, it was found that the current measuring device implementing the midpoint method is an order of magnitude more sensitive than the currently used high-precision measuring instruments.

scholarly journals Investigation of Infrasound Background Noise at Mátra Gravitational and Geophysical Laboratory (MGGL)

Universe ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 10
Author(s):  
Edit Fenyvesi ◽  
József Molnár ◽  
Sándor Czellár
Keyword(s):  
Background Noise ◽  
Seismic Waves ◽  
Ventilation System ◽  
Gravity Gradient ◽  
Measured Signal ◽  
Einstein Telescope ◽  
Continuous Background ◽  
Continuous Noise ◽  
Infrasound Signal ◽  
Noise Spectra

Infrasound and seismic waves are supposed to be the main contributors to the gravity-gradient noise (Newtonian noise) of the third-generation subterranean gravitational wave detectors. This noise will limit the sensitivity of the instrument at frequencies below 20 Hz. Investigation of its origin and the possible methods of mitigation have top priority during the designing period of the detectors. Therefore, long-term site characterizing measurements are needed at several subterranean sites. However, at some sites, mining activities can occur. These activities can cause sudden changes (transients) in the measured signal, and increase the continuous background noise, too. We have developed an algorithm based on discrete Haar transform to find these transients in the infrasound signal. We found that eliminating the transients decreases the variation of the noise spectra, and therefore results a more accurate characterization of the continuous background noise. We carried out experiments for controlling the continuous noise. Machines operating at the mine were turned on and off systematically in order to see their effect on the noise spectra. These experiments showed that the main contributor of the continuous noise is the ventilation system of the mine. We also estimated the contribution of infrasound Newtonian noise at MGGL to the strain noise of a subterranean GW detector similar to Einstein Telescope.

scholarly journals How can the Fourier Transform be Used in Radio Astronomy to Perform Spectral Analysis of Pulsars

2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Pranesh Kumar ◽  
Arthur Western
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Low Frequency ◽  
Radio Frequency Interference ◽  
Radio Waves ◽  
Folding Algorithm ◽  
Radio Signals ◽  
Multiple Characteristics ◽  
The Fourier Transform

The analysis of pulsars is a complicated procedure due to the influence of background radio waves. Special radio telescopes designed to detect pulsar signals have to employ many techniques to reconstruct interstellar signals and determine if they originated from a pulsating radio source. The Discrete Fourier Transform on its own has allowed astronomers to perform basic spectral analysis of potential pulsar signals. However, Radio Frequency Interference (RFI) makes the process of detecting and analyzing pulsars extremely difficult. This has forced astronomers to be creative in identifying and determining the specific characteristics of these unique rotating neutron stars. Astrophysicists have utilized algorithms such as the Fast Fourier Transform (FFT) to predict the spin period and harmonic frequencies of pulsars. However, FFT-based searches cannot be utilized alone because low-frequency pulsar signals go undetected in the presence of background radio noise. Astrophysicists must stack up pulses using the Fast Folding Algorithm (FFA) and utilize the coherent dedispersion technique to improve FFT sensitivity. The following research paper will discuss how the Discrete Fourier Transform is a useful technique for detecting radio signals and determining the pulsar frequency. It will also discuss how dedispersion and the pulsar frequency are critical for predicting multiple characteristics of pulsars and correcting the influence of the Interstellar Medium (ISM).

Label-Free and Immobilization-Free Immunoassay

2007 ◽  
Author(s):  
Island Pinnick ◽  
Kieseok Oh ◽  
Chen-Ling Chang ◽  
Kyong-Hoon Lee ◽  
Jae-Hyun Chung
Keyword(s):  
Analytical Model ◽  
High Sensitivity ◽  
Positive Control ◽  
Negative Control ◽  
Measured Signal ◽  
Label Free ◽  
Particle Counter ◽  
Fluid Resistance

This paper presents an immunoassay capable of detecting an antigen without labeling or immobilization. By measuring a change in fluid resistance, the immunoassay successfully differentiates a positive control from a negative control. The same device can also act as a particle counter due to its high sensitivity. It is capable of detecting differences in concentrations as low as 104 particles per milliliter. An analytical model is developed to analyze the measured signal.

De-Noising Algorithm for Magnetotelluric Signal Based on Mathematical Morphology Filtering

2011 ◽  
Vol 42 (11) ◽  
pp. 65-72 ◽  
Author(s):  
Jin Li ◽  
Jing-tian Tang ◽  
Xiao Xiao
Keyword(s):  
Mathematical Morphology ◽  
Magnetotelluric Sounding ◽  
Measured Signal ◽  
Spectrum Estimation ◽  
Basic Principles ◽  
Baseline Drift ◽  
Type Selection ◽  
The Fourier Transform ◽  
Non Stationary Signal ◽  
Signal Analysis Method

In this paper, an effective de-noising algorithm based on mathematical morphology filtering for magnetotelluric sounding data is presented. Magnetotelluric signals are nonlinear, non-stationary, non-minimum phase, they do not meet the basic requirements of the Fourier transform based on the traditional power spectrum estimation. Mathematical morphology filtering is a new signal analysis method developed in recent years for dealing with non-linear, non-stationary signal. This paper briefly introduce the mathematical morphology filtering basic principles and algorithms. According to the properties of structuring elements, the mathematical morphology filtering is designed. Analysis structuring elements type selection program by filtering performance. Based on the measured signal processing, we discussed its application in magnetotelluric sounding data processing and strong interference separation. Experimental results indicate that the proposed method is feasible and can effectively eliminate larger scale disturbance and baseline drift of magnetotelluric sounding data. In addition, the method is efficient to keep the main characteristics of the original signals, and is helpful to improve signal quality and information interpretability for magnetotelluric sounding data.

scholarly journals Fast radio bursts to be detected with the Square Kilometre Array

2020 ◽  
Vol 497 (4) ◽  
pp. 4107-4116 ◽  
Author(s):  
Tetsuya Hashimoto ◽  
Tomotsugu Goto ◽  
Alvina Y L On ◽  
Ting-Yi Lu ◽  
Daryl Joe D Santos ◽  
...  
Keyword(s):  
Luminosity Function ◽  
Mass Density ◽  
Formation Rate ◽  
High Sensitivity ◽  
High Angular Resolution ◽  
Radio Bursts ◽  
Square Kilometre Array ◽  
Luminosity Functions ◽  
Radio Signals ◽  
Order Of Magnitude

ABSTRACT Fast radio bursts (FRBs) are mysterious extragalactic radio signals. Revealing their origin is one of the central foci in modern astronomy. Previous studies suggest that occurrence rates of non-repeating and repeating FRBs could be controlled by the cosmic stellar-mass density (CSMD) and cosmic star formation-rate density (CSFRD), respectively. The Square Kilometre Array (SKA) is one of the best future instruments to address this subject due to its high sensitivity and high-angular resolution. Here, we predict the number of FRBs to be detected with the SKA. In contrast to previous predictions, we estimate the detections of non-repeating and repeating FRBs separately, based on latest observational constraints on their physical properties including the spectral indices, FRB luminosity functions, and their redshift evolutions. We consider two cases of redshift evolution of FRB luminosity functions following either the CSMD or CSFRD. At $z$ ≳ 2, $z$ ≳ 6, and $z$ ≳ 10, non-repeating FRBs will be detected with the SKA at a rate of ∼104, ∼102, and ∼10 (sky−1 d−1), respectively, if their luminosity function follows the CSMD evolution. At $z$ ≳ 1, $z$ ≳ 2, and $z$ ≳ 4, sources of repeating FRBs will be detected at a rate of ∼103, ∼102, and ≲10 (sky−1 d−1), respectively, assuming that the redshift evolution of their luminosity function is scaled with the CSFRD. These numbers could change by about one order of magnitude depending on the assumptions on the CSMD and CSFRD. In all cases, abundant FRBs will be detected by the SKA, which will further constrain the luminosity functions and number density evolutions.

Research of Defect Detection Method Noise for Bevel Gear

2014 ◽  
Vol 889-890 ◽  
pp. 722-725 ◽  
Author(s):  
Feng Yan Dai ◽  
Zhao Yao Shi ◽  
Jia Chun Lin
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Background Noise ◽  
Back Propagation ◽  
Noise Signal ◽  
Ensemble Empirical Mode Decomposition ◽  
Bevel Gear ◽  
Noise Characteristics ◽  
Useful Signal ◽  
Gear Fault

Noise signal analysis method is widely available for gearbox bevel gear fault detection. However, the noise from the gearbox is usually concealed by background noise, which leads to poor efficiency analysis. This paper reports an ensemble empirical mode decomposition (EEMD) and neural network method for bevel gear fault detection. To extract useful signal, EEMD algorithm was firstly applied to get rid of the background noise. Characteristics from a group of discriminating defect status were then chosen to build the eigenvector. Finally, the eigenvector was imported into a back propagation (BP) neural network classifier for defect diagnosis automatically. Experimental results show that the proposed approach is capable for signal denoising and providing distinguishing characteristics of founded fault. The developed method is an accurate approach to detect fault for tested bevel gear.

scholarly journals Structural Health Monitoring of Walking Dragline Excavator Using Acoustic Emission

2021 ◽  
Vol 11 (8) ◽  
pp. 3420
Author(s):  
Vera Barat ◽  
Artem Marchenkov ◽  
Dmitry Kritskiy ◽  
Vladimir Bardakov ◽  
Marina Karpova ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Weld Joint ◽  
Background Noise ◽  
Effective Control ◽  
Industrial Facility ◽  
Structural Health ◽  
Useful Signal ◽  
Parameters Analysis

The article is devoted to the organization of the structural health monitoring of a walking dragline excavator using the acoustic emission (AE) method. Since the dragline excavator under study is a large and noisy industrial facility, preliminary prospecting researches were carried out to conduct effective control by the AE method, including the study of AE sources, AE waveguide, and noise parameters analysis. In addition, AE filtering methods were improved. It is shown that application of the developed filtering algorithms allows to detect AE impulses from cracks and defects against a background noise exceeding the useful signal in amplitude and intensity. Using the proposed solutions in the monitoring of a real dragline excavator during its operation made it possible to identify a crack in one of its elements (weld joint in a dragline back leg).

ECG Signal Processing

2013 ◽  
Vol 749 ◽  
pp. 394-400
Author(s):  
Lukas Smolarik ◽  
Dusan Mudroncik ◽  
Lubos Ondriga
Keyword(s):  
Notch Filter ◽  
Electric Activity ◽  
Infinite Impulse Response ◽  
Measured Signal ◽  
Point System ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Ecg Signals ◽  
Useful Signal ◽  
Contact Sensing

Electrocardiography (ECG) is a diagnostic method that allows sensing and record the electric activity of heart [. The measurement of electrical activity is used as a standard twelve-point system. At each of these leads to measure the useful signal and interference was measured. The intensity of interference depends on the artefacts (electrical lines, brum, motion artefacts, muscle, interference from the environment, etc.). For correct evaluation of measured signal there is a need to processing the measured signal to suitable form. At present, the use of electrocardiograms with sensors with contact scanning are difficult to set a time so we decided to use the principle of non-contact sensing. Such a device to measure the ECG was constructed under the project. The disadvantage of such devices is a problem with a high level of noise, which degrades a useful signal. The aim of this article is to pre-process the signals obtained from non-contact sensing. The contactless devices are powered from the network and battery. The electrodes were connected by way of Eithoven bipolar leads. Signals were pre-treated with suitable filters so that they are also appropriate for their subsequent analysis. In the filtration ECG signals was used as a method of linear (low pass filter, high pass, IIR (Infinite Impulse Response) peak, notch filter. The results of many signals clearly demonstrate removing noise in the ECG signals to the point that is also suitable for their analysis.

Enzymatically generated long polyT-templated copper nanoparticles for versatile biosensing assay of DNA-related enzyme activity

2015 ◽  
Vol 7 (10) ◽  
pp. 4355-4361 ◽  
Author(s):  
Feifei Peng ◽  
Zhuoliang Liu ◽  
Wang Li ◽  
Yan Huang ◽  
Zhou Nie ◽  
...  
Keyword(s):  
Enzyme Activity ◽  
Copper Nanoparticles ◽  
Background Noise ◽  
High Sensitivity ◽  
Terminal Deoxynucleotidyl Transferase ◽  
Low Background ◽  
Related Enzyme

Terminal deoxynucleotidyl transferase-generated long poly(thymine) DNA can be used as an efficient template to synthesize fluorescent copper nanoparticles, providing a versatile method for detecting various enzymes with low background noise and high sensitivity.

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