The Simulation of Transient Electromagnetic Based on Time-domain IP Model

2019 ◽  
Vol 24 (1) ◽  
pp. 159-162
Author(s):  
Lei Zhou ◽  
LiangJun Yan ◽  
Osborne Kachaje ◽  
Xingbing Xie ◽  
Yurong Mao ◽  
...  
Keyword(s):  
Electromagnetic Field ◽  
Frequency Domain ◽  
Time Domain ◽  
Electromagnetic Response ◽  
Computation Method ◽  
Time Frequency ◽  
Transient Electromagnetic ◽  
Investigation Methods ◽  
Modeling Calculation ◽  
Cole Model

When transient electromagnetic investigation methods are carried out in the field, the measured data often contain both the induced polarization (IP) effect and the electromagnetic effect. In order to study the IP effect in the transient electromagnetic response, many researchers first calculate the electromagnetic field which considers the IP effect by replacing traditional resistivity with complex resistivity of the Cole-Cole model in the frequency domain. After the forward modeling calculation of the electromagnetic field in the frequency domain that considers the IP effect, the transient electromagnetic field in time-domain is obtained by a time-frequency transform algorithm. In this paper, the resistivity is directly replaced by the time-variant resistivity expression of the Cole-Cole model by using digital filter algorithms when we simulate the transient electromagnetic fields in time- domain. The calculated result of the Cole-Cole model in time-domain and in frequency-domain are consistent with each other, as observed in the horizontal electric field and the vertical magnetic field comparisons, which indicates the correctness of the numerical computation method adopted in this paper. The research presented herein allows us to observe the influence of the IP effect on transient electromagnetic field as well as study the mechanisms of IP directly.

scholarly journals A research on fiber-optic vibration pattern recognition based on time-frequency characteristics

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881346 ◽  
Author(s):  
Tabi Fouda Bernard Marie ◽  
Dezhi Han ◽  
Bowen An ◽  
Jingyun Li
Keyword(s):  
Pattern Recognition ◽  
Frequency Domain ◽  
Time Domain ◽  
Fiber Optic ◽  
Pattern Recognition Method ◽  
Recognition Method ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Vibration Pattern ◽  
The Time Domain

To detect and recognize any type of events over the perimeter security system, this article proposes a fiber-optic vibration pattern recognition method based on the combination of time-domain features and time-frequency domain features. The performance parameters (event recognition, event location, and event classification) are very important and describe the validity of this article. The pattern recognition method is precisely based on the empirical mode decomposition of time-frequency entropy and center-of-gravity frequency. It implements the function of identifying and classifying the event (intrusions or non-intrusion) over the perimeter to secure. To achieve this method, the first-level prejudgment is performed according to the time-domain features of the vibration signal, and the second-level prediction is carried out through time-frequency analysis. The time-frequency distribution of the signal is obtained by empirical mode decomposition and Hilbert transform and then the time-frequency entropy and center-of-gravity frequency are used to form the time-frequency domain features, that is, combined with the time-domain features to form feature vectors. Multiple types of probabilistic neural networks are identified to determine whether there are intrusions and the intrusion types. The experimental results demonstrate that the proposed method is effective and reliable in identifying and classifying the type of event.

Spectrum analysis of moving average operator and construction of time-frequency hybrid sequence operator

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Changhai Lin ◽  
Sifeng Liu ◽  
Zhigeng Fang ◽  
Yingjie Yang
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Moving Average ◽  
Spectral Characteristics ◽  
Complex Data ◽  
Time Data ◽  
Average Operator ◽  
Content Type ◽  
Time Frequency ◽  
Hybrid Sequence

PurposeThe purpose of this paper is to analyze the spectral characteristics of moving average operator and to propose a novel time-frequency hybrid sequence operator.Design/methodology/approachFirstly, the complex data is converted into frequency domain data by Fourier transform. An appropriate frequency domain operator is constructed to eliminate the impact of disturbance. Then, the inverse Fourier transform transforms the frequency domain data in which the disturbance is removed, into time domain data. Finally, an appropriate moving average operator of N items is selected based on spectral characteristics to eliminate the influence of periodic factors and noise.FindingsThrough the spectrum analysis of the real-time data sensed and recorded by microwave sensors, the spectral characteristics and the ranges of information, noise and shock disturbance factors in the data can be clarified.Practical implicationsThe real-time data analysis results for a drug component monitoring show that the hybrid sequence operator has a good effect on suppressing disturbances, periodic factors and noise implied in the data.Originality/valueFirstly, the spectral analysis of moving average operator and the novel time-frequency hybrid sequence operator were presented in this paper. For complex data, the ideal effect is difficult to achieve by applying the frequency domain operator or time domain operator alone. The more satisfactory results can be obtained by time-frequency hybrid sequence operator.

scholarly journals Numerical Simulation of Transient Electromagnetic Response of Unfavorable Geological Body in Tunnel

2011 ◽  
Vol 90-93 ◽  
pp. 37-40 ◽  
Author(s):  
Lu Bo Meng ◽  
Tian Bin Li ◽  
Zheng Duan
Keyword(s):  
Numerical Simulation ◽  
Finite Element ◽  
Electromagnetic Field ◽  
Electromagnetic Response ◽  
Detection Distance ◽  
Geological Body ◽  
Response Characteristics ◽  
Finite Element Software ◽  
Transient Electromagnetic ◽  
Field Decay

To investigate the transient electromagnetic method of response characteristics in the tunnel geological prediction, the finite element numerical simulation of unfavorable geological body of different location, different resistivity sizes, different shapes, and different volume size were carried out by ANSYS finite element software. The results show that secondary electromagnetic field of different location of unfavorable geological body have same decay rate, when detection distance from 30m to 70m, transient electromagnetic responses are strongest, followed distance from 10m to 30m and from 70m to 90m. The shape, volume and resistivity of unfavorable geological body have strong influence on transient electromagnetic response, unfavorable geological body more sleek, the greater the volume and the smaller the resistivity of unfavorable geological body, the secondary electromagnetic field decay slower.

scholarly journals Recognition of Emotions Using Multichannel EEG Data and DBN-GC-Based Ensemble Deep Learning Framework

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Hao Chao ◽  
Huilai Zhi ◽  
Liang Dong ◽  
Yongli Liu
Keyword(s):  
Deep Learning ◽  
Frequency Domain ◽  
Time Domain ◽  
Recognition Task ◽  
Frequency Characteristics ◽  
Time Frequency ◽  
Learning Framework ◽  
Valence States ◽  
Correlation Information ◽  
Multiple Domains

Fusing multichannel neurophysiological signals to recognize human emotion states becomes increasingly attractive. The conventional methods ignore the complementarity between time domain characteristics, frequency domain characteristics, and time-frequency characteristics of electroencephalogram (EEG) signals and cannot fully capture the correlation information between different channels. In this paper, an integrated deep learning framework based on improved deep belief networks with glia chains (DBN-GCs) is proposed. In the framework, the member DBN-GCs are employed for extracting intermediate representations of EEG raw features from multiple domains separately, as well as mining interchannel correlation information by glia chains. Then, the higher level features describing time domain characteristics, frequency domain characteristics, and time-frequency characteristics are fused by a discriminative restricted Boltzmann machine (RBM) to implement emotion recognition task. Experiments conducted on the DEAP benchmarking dataset achieve averaged accuracy of 75.92% and 76.83% for arousal and valence states classification, respectively. The results show that the proposed framework outperforms most of the above deep classifiers. Thus, potential of the proposed framework is demonstrated.

A Computationally Efficient Multichannel Active Road Noise Control System

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Jie Duan ◽  
Mingfeng Li ◽  
Teik C. Lim ◽  
Ming-Ran Lee ◽  
Ming-Te Cheng ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Noise Control ◽  
Acoustic Noise ◽  
Reference Signal ◽  
Active Noise Control ◽  
Computational Cost ◽  
Road Noise ◽  
Time Frequency ◽  
Fxlms Algorithm

A multichannel active noise control (ANC) system has been developed for a vehicle application, which employs loudspeakers to reduce the low-frequency road noise. Six accelerometers were attached to the vehicle structure to provide the reference signal for the feedforward control strategy, and two loudspeakers and two microphones were applied to attenuate acoustic noise near the headrest of the driver's seat. To avoid large computational burden caused by the conventional time-domain filtered-x least mean square (FXLMS) algorithm, a time-frequency domain FXLMS (TF-FXLMS) algorithm is proposed. The proposed algorithm calculates the gradient estimate and filtered reference signal in the frequency domain to reduce the computational requirement, while also updates the control signals in the time domain to avoid delay. A comprehensive computational complexity analysis is conducted to demonstrate that the proposed algorithm requires significantly lower computational cost as compared to the conventional FXLMS algorithm.

The influence of currents induced in the host rock on electromagnetic response of a spheroid directly beneath a loop

Geophysics ◽  
1981 ◽  
Vol 46 (8) ◽  
pp. 1121-1136 ◽  
Author(s):  
Alexander A. Kaufman
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Asymptotic Expression ◽  
Surrounding Medium ◽  
Electromagnetic Response ◽  
Ore Body ◽  
Ore Bodies ◽  
Integral Equation Approach ◽  
Em Field ◽  
Special Case

A variety of time‐domain and frequency‐domain electromagnetic (EM) methods has come into use in minerals exploration for detection of conductive ore bodies. Because the responses of these various systems differ markedly from one another, the question arises as to which is the most effective for use in discovering a buried, conductive ore body. The question can be posed as follows: What type of exploration system provides the best signal‐to‐noise (S/N) ratio, when signal is defined as the anomalous EM field caused by the presence of a target body and noise is defined as EM responses from the surrounding medium? Analytic solution of the problem is tedious and has not yet been reported in the literature. I describe some results for a special case which reduces the complexity of the problem somewhat. The case treated is that of a conducting spheroid situated directly beneath a source loop. The EM responses caused by currents in the spheroid and in the surrounding medium were computed in both the frequency domain and time domain, using the integral equation approach, supplemented with evaluations of asymptotic expression for various field components. Results show that the transient method provides the best S/N ratio of the methods considered.

Extracting of Micro Doppler Parameter of Helicopter Rotor Based on Time-Frequency Analysis

2011 ◽  
Vol 130-134 ◽  
pp. 2696-2700 ◽  
Author(s):  
Lei Zhang ◽  
Guo Qing Huang
Keyword(s):  
Frequency Domain ◽  
Frequency Analysis ◽  
Time Domain ◽  
Good Method ◽  
Helicopter Rotor ◽  
Echo Signal ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Radar Echo ◽  
Doppler Parameter

The micro Doppler effect of the radar echo signal of helicopter rotor is studied, and the formula of helicopter rotor echo is obtained. Then the received echo signal of helicopter rotor simulated is analyzed in time domain, frequency domain and time-frequency domain respectively, the analysis results show that it is a good method to extract micro Doppler of helicopter rotor echo by time-frequency analysis. According to analysis results, obtained a method to determine parity of blades and velocity of helicopter rotor, these methods can be used to identify helicopter.

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