scholarly journals Analysis of the Borehole Effect in Borehole Radar Detection

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5812
Author(s):  
Wentian Wang ◽  
Sixin Liu ◽  
Xuzhang Shen ◽  
Wenjun Zheng
Keyword(s):  
Relative Permittivity ◽  
Mutual Coupling ◽  
Propagation Speed ◽  
Wave Pattern ◽  
Radar System ◽  
Circular Array ◽  
Multiple Reflections ◽  
Borehole Radar ◽  
The One ◽  
Transmitting Antenna

The directional borehole radar can accurately locate and image the geological target around the borehole, which overcomes the shortcomings that the conventional borehole radar can only detect the depth of the target and the distance from the borehole. The directional borehole radar under consideration consists of a transmitting antenna and four receiving antennas equally distributed on the ring in the borehole. The nonuniformity caused by the borehole and sonde, as well as the mutual coupling among the four receiving antennas, will have a serious impact on the received signal and then cause interference to the azimuth recognition for the targets. In this paper, Finite difference time domain (FDTD), including the subgrid, is applied to study these effects and interferences, and the influence of borehole, sonde, and mutual coupling among the receiving antennas is found. The results show that, without considering the sonde and the fluid in the borehole, the one transmitting and one receiving borehole radar system does not have resonance, but the wave pattern of the reflected wave will have obvious distortion. For the four receiving antennas of the borehole radar system, there is obvious resonance, which is caused by the multiple reflections between the receiving antennas. However, when the fluid in the borehole is water and the relative permittivity of the sonde is low to a certain extent, the resonance disappears; that is, the generation of resonance requires a large relative permittivity material between the receiving antennas. When the influence of the sonde is considered, the resonance disappears because the relative permittivity of the sonde is low, which makes the propagation speed of the electromagnetic wave between the antennas accelerate and lose the conditions for resonance. In addition, the diameters of the sonde and the circular array of the receiving antennas can affect the received signal: the higher the diameter of the sonde and the higher the diameter of the circular array are, the better the differentiation of the received signal. The development of the research provides scientific guidance for the design and application of borehole radar in the future.

Inversion of normal incidence seismograms

Geophysics ◽  
1982 ◽  
Vol 47 (5) ◽  
pp. 757-770 ◽  
Author(s):  
A. Bamberger ◽  
G. Chavent ◽  
Ch. Hemon ◽  
P. Lailly
Keyword(s):  
Simulated Data ◽  
Normal Incidence ◽  
State Equation ◽  
Inversion Algorithm ◽  
Multiple Reflections ◽  
Common Depth Point ◽  
Adjoint State ◽  
Nmo Correction ◽  
The One ◽  
Practical Feasibility

The well‐known instability of Kunetz’s (1963) inversion algorithm can be explained by the progressive manner in which the calculations are done (descending from the surface) and by the fact that completely different impedances can yield indistinguishable synthetic seismograms. Those difficulties can be overcome by using an iterative algorithm for the inversion of the one‐dimensional (1-D) wave equation, together with a stabilizing constraint on the sums of the jumps of the desired impedance. For computational efficiency, the synthetic seismogram is computed by the method of characteristics, and the gradient of the error criterion is computed by optimal control techniques (adjoint state equation). The numerical results on simulated data confirm the expected stability of the algorithm in the presence of measurement noise (tests include noise levels of 50 percent). The inversion of two field sections demonstrates the practical feasibility of the method and the importance of taking into account all internal as well as external multiple reflections. Reflection coefficients obtained by this method show an excellent agreement with well‐log data in a case where standard estimation techniques [deconvolution of common‐depth‐point (CDP) stacked and normal‐moveout (NMO) correction section] failed.

scholarly journals Accurate and Efficient Representation of Obstacles Using Radar Visualizer

2021 ◽  
Vol 9 (VI) ◽  
pp. 4429-4431
Author(s):  
K. Akanksha
Keyword(s):  
Detection System ◽  
Target Position ◽  
Radar System ◽  
Motor Vehicles ◽  
Radio Waves ◽  
Receiving Antenna ◽  
Efficient Representation ◽  
Transmitting Antenna ◽  
Analyze Data

Radar is a detection system that uses radio waves to determine the range, angle or velocity of objects. It can be used to detect aircraft, ships, spacecraft, guided missiles, motor vehicles, weather formations, and terrain. A radar system consist of a transmitting antenna, a receiving antenna (often same antenna is used for transmitting and receiving) and a receiver and process to determine properties of the objects. In our project we are detecting the target position of the obstacles that come in our way be it in military, aircrafts, ships, clouds, etc. using MATLAB. Using MATLAB, you can: analyze data, develop algorithms, create models and applications. The language, apps, and build in math functions enable you to quickly explore multiple approaches to arrive at a solution. Using MATLAB and Simulink we are doing radar visualizer.

scholarly journals Pulse-Wave-Pattern Classification with a Convolutional Neural Network

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Gaoyang Li ◽  
Kazuhiro Watanabe ◽  
Hitomi Anzai ◽  
Xiaorui Song ◽  
Aike Qiao ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Pattern Classification ◽  
Pulse Wave ◽  
Wave Pattern ◽  
Classification Criteria ◽  
Physiological Parameters ◽  
Physiological Parameter ◽  
Data Set ◽  
The One

Abstract Owing to the diversity of pulse-wave morphology, pulse-based diagnosis is difficult, especially pulse-wave-pattern classification (PWPC). A powerful method for PWPC is a convolutional neural network (CNN). It outperforms conventional methods in pattern classification due to extracting informative abstraction and features. For previous PWPC criteria, the relationship between pulse and disease types is not clear. In order to improve the clinical practicability, there is a need for a CNN model to find the one-to-one correspondence between pulse pattern and disease categories. In this study, five cardiovascular diseases (CVD) and complications were extracted from medical records as classification criteria to build pulse data set 1. Four physiological parameters closely related to the selected diseases were also extracted as classification criteria to build data set 2. An optimized CNN model with stronger feature extraction capability for pulse signals was proposed, which achieved PWPC with 95% accuracy in data set 1 and 89% accuracy in data set 2. It demonstrated that pulse waves are the result of multiple physiological parameters. There are limitations when using a single physiological parameter to characterise the overall pulse pattern. The proposed CNN model can achieve high accuracy of PWPC while using CVD and complication categories as classification criteria.

Delta-Shock Solution to the Eulerian Droplet Model by Variable Substitution Method

2020 ◽  
Vol 75 (3) ◽  
pp. 201-210 ◽  
Author(s):  
Yanyan Zhang ◽  
Yu Zhang
Keyword(s):  
Special Kind ◽  
Propagation Speed ◽  
Euler System ◽  
Droplet Model ◽  
Delta Shock Wave ◽  
Delta Shock ◽  
System Solution ◽  
Variable Substitution ◽  
The One ◽  
Vacuum Solutions

AbstractBy introducing a special kind of variable substitution, we skillfully solve the delta-shock and vacuum solutions to the one-dimensional Eulerian droplet model. The position, propagation speed, and strength of the delta shock wave are derived under the generalised Rankine–Hugoniot relation and entropy condition. Moreover, we show that the Riemann solution of the Eulerian droplet model converges to the corresponding the pressureless Euler system solution as the drag coefficient goes to zero.

scholarly journals Transmission compensated primary reflection retrieval in the data domain and consequences for imaging

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. Q27-Q36 ◽  
Author(s):  
Lele Zhang ◽  
Jan Thorbecke ◽  
Kees Wapenaar ◽  
Evert Slob
Keyword(s):  
Thin Layer ◽  
Time Domain ◽  
Velocity Model ◽  
Original Data ◽  
Transmission Losses ◽  
Multiple Reflections ◽  
Data Set ◽  
Numerical Examples ◽  
The One ◽  
The Time Domain

We have developed a scheme that retrieves primary reflections in the two-way traveltime domain by filtering the data. The data have their own filter that removes internal multiple reflections, whereas the amplitudes of the retrieved primary reflections are compensated for two-way transmission losses. Application of the filter does not require any model information. It consists of convolutions and correlations of the data with itself. A truncation in the time domain is applied after each convolution or correlation. The retrieved data set can be used as the input to construct a better velocity model than the one that would be obtained by working directly with the original data and to construct an enhanced subsurface image. Two 2D numerical examples indicate the effectiveness of the method. We have studied bandwidth limitations by analyzing the effects of a thin layer. The presence of refracted and scattered waves is a known limitation of the method, and we studied it as well. Our analysis indicates that a thin layer is treated as a more complicated reflector, and internal multiple reflections related to the thin layer are properly removed. We found that the presence of refracted and scattered waves generates artifacts in the retrieved data.

Oscillating flames: multiple-scale analysis

2009 ◽  
Vol 465 (2107) ◽  
pp. 2089-2110 ◽  
Author(s):  
Luc Bauwens ◽  
C. Regis L. Bauwens ◽  
Ida Wierzba
Keyword(s):  
Approximate Solution ◽  
Reaction Front ◽  
Burning Velocity ◽  
Propagation Speed ◽  
Multiple Scale ◽  
Expansion Ratio ◽  
Scale Analysis ◽  
Dimensional Problem ◽  
One Dimensional ◽  
The One

A complete multiple-scale solution is constructed for the one-dimensional problem of an oscillating flame in a tube, ignited at a closed end, with the second end open. The flame front moves into the unburnt mixture at a constant burning velocity relative to the mixture ahead, and the heat release is constant. The solution is based upon the assumption that the propagation speed multiplied by the expansion ratio is small compared with the speed of sound. This approximate solution is compared with a numerical solution for the same physical model, assuming a propagation speed of arbitrary magnitude, and the results are close enough to confirm the validity of the approximate solution. Because ignition takes place at the closed end, the effect of thermal expansion is to push the column of fluid in the tube towards the open end. Acoustics set in motion by the impulsive start of the column of fluid play a crucial role in the oscillation. The analytical solution also captures the subsequent interaction between acoustics and the reaction front, the effect of which does not appear to be as significant as that of the impulsive start, however.

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