Predicting microseismic,acoustic emission and electromagnetic radiation data using neural networks

Microseism,acoustic emission and electromagnetic radiation(M-A-E)data are usually used for predicting rockburst hazards.However,it is a great challenge to realize the prediction of M-A-E data.In this study,with the aid of a deep learning algorithm,a new method for the prediction of M-A-E data is proposed.In this method,an M-A-E data prediction model is built based on a variety of neural networks after analyzing numerous M-A-E data,and then the M-A-E data can be predicted.The predicted results are highly correlated with the real data collected in the field.Through field verification,the deep learning-based prediction method of M-A-E data provides quantitative prediction data for rockburst monitoring.

Fast measurement and prediction method for electromagnetic susceptibility of receiver

Aiming at evaluating and predicting rapidly and accurately a high sensitivity receiver’s adaptability in complex electromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone test.Firstly,two signal generators are used to generate signals at the radio frequency(RF)by frequency scanning,and then a rapid measurement at the intermediate frequency(IF)output port is carried out to obtain a huge amount of sample data for the subsequent analysis.Secondly,the IF output response data are modeled and analyzed to construct the linear and nonlinear response constraint equations in the frequency domain and prediction models in the power domain,which provide the theoretical criteria for interpreting and predicting electromagnetic susceptibility(EMS)of the receiver.An experiment performed on a radar receiver confirms the reliability of the method proposed in this paper.It shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity model.Based on this,fast and comprehensive evaluation and prediction of the receiver’s EMS in complex environment can be efficiently realized.

Research on Electromagnetic Acoustic Emission Signal Recognition Based on Local Mean Decomposition and Least Squares Support Vector Machine

Electromagnetic acoustic emission technology is one of nondestructive testing, which can be used for defect detection of metal specimens. In this study, round and cracked metal specimens, round metal specimens, and intact metal specimens were prepared. And the electromagnetic acoustic emission signals of the three specimens were collected. In addition, the local mean decomposition(LMD), Autoregressive model(AR model) and least squares support vector machine (LSSVM) algorithms were combined to identify the eletromagnetic acoustic emission signals of round and cracked, round, and intact specimens. According to the algorithm recognition results, the recognition accuracy of can reach above 97.5%, which has a higher recognition rate compared with SVM and BP neural network. The results of the study show that the algorithm is able to identify quickly and accurately crack defect in metal specimens.

Study of electromagnetic and acoustic emission in creep experiments of water-containing rock samples

Based on biaxial shear creep tests conducted on rock samples with different water contents, we present the results of our study on the regularities of electromagnetic and acoustic emission during the process of creep experiments in which we have analyzed the contribution of water to the occurrence of electromagnetic radiation. The result shows that in the creep-fracturing course of rock samples, when the water content increases, the initial frequency and amplitude of electromagnetic and acoustic emission also increases, but at a decreasing growth rate caused by loading stress. This can be used as a criterion for the long-term stability of rock masses under conditions of repeated inundation and discharge of water.

Chaotic characteristics of electromagnetic emission signals during deformation and fracture of coal

Electromagnetic emission(EME) is a kind of physical phenomenon accompanying the process of deformation and fracture of loaded coal and rock and it is of importance in quantitatively analyzing its characteristics.This will reveal the process of deformation and fracture of coal and predicting dynamic disasters in coal mines.In this study,the G-P(Grassberger and Procaccia) algorithm,calculation steps of the(if only 1 dimension) correlation dimension of time series and the identification standards of chaotic signals are introduced.Furthermore,the correlation dimensions of EME and the acoustic emission(AE) signals of time series during deformation and fracture of coal bodies are calculated and analyzed.The results show that the time series of pulses number of EME and the time series of AE count rate are chaotic and that the saturation embedding dimensions of a K3 coal sample are,respectively,5 and 6.The results can be used to provide basic parameters for predicting of EME and AE time series.

Stimulated electromagnetic emissions spectrum observed during an X-mode heating experiment at the European Incoherent Scatter Scientific Association

An extraordinary(X-mode)electromagnetic wave,injected into the ionosphere by the ground-based heating facility at Tromsφ,Norway,was utilized to modify the ionosphere on November 6,2017.The high-power high-frequency transmitter facility located at Tromsφ belongs to the European Incoherent Scatter Scientific Association.In the experiment,stimulated electromagnetic emission(SEE)spectra were observed.A narrow continuum occurred under cold-start conditions and showed an overshoot effect lasting several seconds.Cascading peaks occurred on both sides of the heating frequency only in the preconditioned ionosphere and also showed an overshoot effect.These SEE features are probably related to the ponderomotive process in the X-mode heating experiment and are helpful for understanding the physical mechanism that generated them during the X-mode heating experiment.The features observed in the X-mode heating experiments are novel and require further investigation.

Electromagnetic Emissions Recorded by a Borehole TOA Installment before Four Huge Destructive <i>M</i>_S≥ 8.0 Earthquakes in Asia

In this paper, electromagnetic emissions recorded by a borehole TOA installment with three observing channels of CH1 (0.01 - 0.1 Hz), CH2 (0.1 - 1.0 Hz) and CH3 (1 - 9 kHz) before four large earthquakes with magnitudes more than 8.0 have been depicted. These abnormities present different fluctuating processes from one another. For the Wenchuan MS 8.0 earthquake on 12 May 2008, the nearest one among these four events and only 660 km from the TOA station, electromagnetic information appeared at least 5 months ago in two low frequency bands of CH1 and CH2 and it was subjected to an obvious fluctuating process with several developing stages: initial information, intensive anomaly and large amplitude signals. The typical pulse-like emissions in CH2 happened group by group with large various magnitudes, which can be of 10 mV in the climax period. While during this period, compatible wave-like information with little magnitudes also happened in CH1 channel and a few pulses in CH3. Anomalous emissions occurred about 4 months prior to the 25 April 2015 Nepal MS 8.1 event, 1560 km away from the TOA station. The abnormal information in CH2 also appeared group by group but with small various magnitudes, more than 2 mV during their climax. This process is also effective for the Sumatra MS 8.9 earthquake on 26 December 2004, 2500 km from the borehole TOA, only with a different duration of 2 months and less magnitudes of 0.1 mV in CH1 and 1 mV in CH2 in this case. However, there is no obvious fluctuation and only small constant amplitude signals being ~0.15 mV appeared during 2 weeks before the Japan MS 9.0 earthquake on 11 March 2011. It is the farthest one among these four events and beyond 4000 km from the observing station. So, we can make a conclusion that there is a near relationship between the properties of the abnormities associated with these four earthquakes, such as amplitudes, duration and signal types, and the distances from TOA station: on one hand, the amplitude and duration decreases as the distance increases;on the other hand, there is an evolution for emission properties from complex various magnitude signals to single equal magnitude ones as the distance changes to be far. However, one common feature of the anomalous information related to these four events is that almost electromagnetic emissions were collected in two low frequency bands of CH2 and CH1 instead of CH3 band, which means ULF band (0.01 - 1.0 Hz) is more sensitive than VLF band (1 - 9 kHz) at this TOA station.

Exposure of Weak Time-Invariant Electromagnetic Fields to B16-BL6 Cell Cultures Alter Biophoton Emission Profile as a Function of Distance

Biophoton emission is produced by all living systems;this emission pattern has been shown to be altered by the presence of an electromagnetic field (EMF). Cultures of B16-BL6 cells were exposed to a weak EMF produced by a specially constructed EM generator, called the “Resonator”, for one hour. This EM generator incorporates multiple geometric ratios in its design, including the golden ratio (phi), pi, root 2, root 3, and root 5. It has been used previously to purify water of toxins. There was a significant decrease in mean photon counts from B16-BL6 cells exposed at a distance of 1 m compared to those exposed at 0 m. Alterations in the spectral power density variability were also observed in the 8 - 10 Hz range. The EM generator may have an impact on the viability of the exposed cell cultures, but only at specific distances.

Ultra-Low Frequency Electromagnetic Emissions Registered during the 21 May 2021 Yangbi <i>M</i>_S6.4 Earthquake in China

Four ULF (0.01 Hz - 20 Hz) electromagnetic stations had been gradually established and put into service from 2010 to 2011 in Zhaotong area, Yunnan province. Two stations of Qiaojia and Yongshan have been running with continuous and high quality recordings and free of influence of solar activities, like magnetic storms. In this investigation, daily recordings from 1 January 2020 to 22 May 2021 have been examined of these both stations. The results show that weak anomalous signals appeared at the beginning of March 2021 with relative low magnitudes of 0.6 nT at Qiaojia station and 0.3 nT at Yongshan station. At the end of this month, the emissions gained an abrupt increase and the amplitudes reached up to 3.8 nT at Qiaojia station and 1.2 nT at Yongsha station. Then, the amplitude decreased to be 0.5 - 1.5 nT and 0.6 - 1.3 nT respectively at both stations but with a high variation frequency in all components. This situation lasted till the Yangbi MS 6.4 earthquake happened on May 21, 2021, more than 300 km away from these two ULF observing stations. Totally, the ULF magnetic emissions had been characterized by a synchronous variation in all components at two observing stations.

Electron Dynamics and Characteristics of Attosecond Electromagnetic Emissions in Relativistic Laser-Plasma Interactions

Generation of attosecond electromagnetic （EM） pulses and the associated electron dynamics are studied using particle-in-cell simulations of relativistic laser pulses interacting with over-dense plasma foil targets. The inter- action process is found to be so complicated even in the situation of utilizing driving laser pulses of only one cycle. Two electron bunches closely involved in the laser-driven wavebreaking process contribute to attosecond EM pulses through the coherent synchrotron emission process whose spectra are found to follow an exponential decay rule. Detailed investigations of electron dynamics indicate that the early part of the reflected EM emission is the high-harmonics produced through the relativistic oscillating mirror mechanism. High harmonics are also found to be generated through the Bremsstrahlung radiation by one electron bunch that participates in the wavebreaking process and decelerates when it experiences the local wavebreaking-generated high electrostatic field in the moving direction.

VLF/LF Electromagnetic Emissions Predict an Earthquake

The present consolidated paper represents the VLF/LF (very low frequency/low frequency) electromagnetic radiation as the earthquake’s true precursor. The search is mainly carried out on the basis of a theoretical model of the generation of electromagnetic emissions during the earthquake preparation period and earthquake prediction methodology. It is shown that this parameter is capable of describing the fault formative process in the focal area. Besides, VLF/LF electromagnetic radiation frequency analysis gives the possibility simultaneously to determine all necessary three characteristic parameters (magnitude, epicenter, time of occurring) for incoming earthquake prediction with great precision.

Joule-Lenz Energy of Quantum Electron Transitions Compared with the Electromagnetic Emission of Energy

In the first step, the Joule-Lenz dissipation energy specified for the electron transitions between two neighbouring quantum levels in the hydrogen atom has been compared with the electromagnetic energy of emission from a single level. Both the electric and magnetic vectors entering the Pointing vector of the electromagnetic field are referred to the one-electron motion performed along an orbit in the atom. In the next step, a similar comparison of emission rates is performed for the harmonic oscillator. Formally a full agreement of the Joule-Lenz and electromagnetic expressions for the energy emission rates has been attained.

Guided and Direct Wave Evaluation of Controlled Source Electromagnetic Survey Using Finite Element Method

Deep target hydrocarbon detection is still challenging and expensive. Direct hydrocarbon indicators (DHIs) in seismic data do not correspond to economical hydrocarbon exploration. Due to unreliability in seismic data for the detection of DHIs, new methods have been investigated. Marine controlled source electromagnet (MCSEM) or Sea bed logging (SBL) is new method for the detection of deep target hydrocarbon reservoir. Sea bed logging has also the potential to reduce the risks of DHIs in deep sea environment. Modelling of real sea environment helps to reduce the further risks before drilling the oil wells. 3D electromagnetic (EM) modelling of seabed logging requires more accurate methods for the detection of hydrocarbon reservoir. Finite element method (FEM) is chosen for the modelling of seabed logging to get more precise EM response from hydrocarbon reservoir below 4000 m from seabed. FEM allows to investigate the total electric and magnetic fields instead of scattered electric and magnetic fields, which shows accurate and precise resistivity contrast below the seabed. From the modelling results, It was investigated that Hz field shows higher magni- tude with 342% than the Ex field. It was observed that 0.125 Hz frequency can be able to show better resistivity contrast of Hz field (31.30%) and Ex field (16.49%) at target depth of 1000 m below seafloor for our proposed model. Hz and Ex field delineation was found to decrease as target depth increased from 1000 m to 4000 m. At the target depth of 4000 m, no field delineation response was seen from the current electromagnetic (EM) antenna used by the industry. New EM antenna has been used to see the EM response for deep target hydrocarbon detection. It was investigated that novel EM antenna shows better delineation at 4000 m target depth for Ex and Hz field up to 10.3% and 15.1% respectively. Novel EM antenna also shows better Hz phase response (128.4%) than the Ex phase response (38.3%) at the target depth of 4000 m below the seafloor.

Improved Study on Position Measurement System for Linear Motor Applied in Electromagnetic Launch System

The linear motor applied in electromagnetic emission system uses a closed loop position control strategy,which needs a set of position measurement system with high reliability,high resolution and integration to achieve real-time acquisition and analysis of position signals.The existing position controller is based on the simple logic chip design without memory function,and does not have the storage analysis and preprocessing function to position signals.Therefore,the system has insufficient scalability,low integration and reliability.Aiming at the improvement of the existing position measurement system,an intelligent position measurement system integrating the functions of position signals acquisition,processing and uploading,data storage and analysis is proposed in this paper,and its working principle and system composition are discussed in detail.The position,speed and acceleration obtained on the electromagnetic emission platform are in good agreement with the expected value of the system.As results,the feasibility and accuracy of the improved integrated intelligent position measurement system are verified,and the control performance of the system is also satisfied well,which can be good guidance and reference for subsequent engineering practice.

Spatio-Temporal Changes of Soil Salinity in Arid Areas of South Xinjiang Using Electromagnetic Induction

The aim of this paper was to research the spatio-temporal changes in total soluble salt content （TS） in a typical arid region of South Xinjiang, China, where the climate is arid and soil salinization happens easily. The total soluble salt content was interpreted by measurements made in the horizontal mode with EM38 and EM31. The electromagnetic induction （EM） surveys were made three times with the apparent soil electrical conductivity （ECa） measurements taken at 3 873 locations in Nov. 2008, 4 807 locations in Apr. 2009 and 6 324 locations in Nov. 2009, respectively. For interpreting the ECa measurements into total soluble salt content, calibtion sites were needed for EM survey of each time, e.g., 66 sites were selected in Nov. 2008 to measure ECa, and soils-core samples were taken by different depth layers of 0-10, 10-20 and 20-40 cm at the same time. On every time duplicate samples were taken at five sites to allevaite the local-scale variability, and soil temperatures in different layers through the profiles were also measured. Factors including TS, pH, water content, bulk density were analyzed by lab experiments. ECa calibration equations were obtained by linear regression analysis, which indicated that soil salinity was one primary concern to ECa with a determination coefficient of 0.792 in 0-10 cm layer, 0.711 in 10-20 cm layer and 0.544 in 20-40 cm layer, respectively. The maps of spatial distribution were predicted by Kriging interpolation, which showed that the high soil salinity was located near the drainage canal, which validated the trend effect caused by the irrigation canal and the drainage canal. And by comparing the soil salinity in different layers, the soluble salt accumulated to the top soil surface only in the area where the soil salinization was serious, and in the other areas, the soil salinity trended to increase from the top soil surface to 40 cm depth. Temporal changes showed that the soil salinity in November was higher than that in April, and the soil salinization trended to aggravate, especially in the top soil layer of 0-10 cm.

Deep learning-based method for detecting anomalies in electromagnetic environment situation

The anomaly detection of electromagnetic environment situation(EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment.In this paper,we proposed a deep learning-based method for detecting anomalies in EMES to address the problem of relatively low efficiency of electromagnetic environment situation anomaly detection(EMES-AD).Firstly,the convolutional kernel extracts the static features of different regions of the EMES.Secondly,the dynamic features of the region are obtained by using a recurrent neural network(LSTM).Thirdly,the Spatio-temporal features of the region are recovered by using a de-convolutional network and then fused to predict the EMES.The structural similarity algorithm(SSIM) is used to determine whether it is anomalous.We developed the detection framework,de-signed the network parameters,simulated the data sets containing different anomalous types of EMES,and carried out the detection experiments.The experimental results show that the proposed method is effective.

Emission of High Energy during Super-Compressibility of Supersonic Jets

New source of light emission of high energy is found due to arising of instability in supersonic jets. These phenomena are observed in gas jets flowing from the nozzle with a central cone. It leads to high accelerations of the molecules, ions and elementary particles. The emission spectra of the jets are obtained. Decoding of the spectra allowed us to define inverted population of rotational and vibrational levels, electrons temperature, rotational and vibrational temperatures for molecular ions. Internal energy decreasing provides the instability and gas volume decreasing due to internal forces;super-compressibility is result of it;its produce high density of light energy emission in various continuous media.

Numerical Method for Solving Electromagnetic Scattering Problem by Many Small Impedance Bodies

In this paper, we study electromagnetic (EM) wave scattering problem by many small impedance bodies. A numerical method for solving this problem is presented. The problem is solved under the physical assumptions ka??1, where a is the characteristic size of the bodies and k is the wave number. This problem is solved asymptotically and numerical experiments are provided to illustrate the idea of the method. Error estimate for the asymptotic solution is also discussed.

Semisolid slurry of 7A04 aluminum alloy prepared by electromagnetic stirring and Sc, Zr additions

Slurry preparation is one of the most critical steps for semisolid casting, and its primary goal is to prepare slurry with uniformly distributed fine globules. In this work, electromagnetic stirring(EMS) and the addition of Sc and Zr elements were used to prepare semisolid slurry of 7A04 aluminum alloy in a large diameter slurry maker. The effects of different treatments on the microstructure, composition and their radial homogeneity were investigated. The results show that, compared to the slurry without any treatment, large volume slurry with finer and more uniform microstructure can be obtained when treated by EMS, Sc, or Zr additions individually. EMS is more competent in the microstructural and chemical homogenization of the slurry while Sc and Zr additions are more excellent in its microstructural refinement. The combined treatment of EMS, Sc and Zr produces premium 7A04 aluminum alloy slurry with uniformly distributed fine α-Al globules and composition. The interaction mechanism between EMS and Sc and Zr additions was also discussed.

Progress of Expert Systems in Electromagnetic Engineering

It is urgent to solve various problems in electromagnetic （EM） engineering under the increasingly complicated environment. Some expert systems （ES） come into being just to keep up with the demand for solving these problems. Combined with the analysis of development orES technology and the development trend of EM engineering software in recent years, the application orES technology in EM engineering is discussed, and especially the progress of complete ES in electromagnetic compatible （EMC） is introduced.