Electromagnetic environments in roadways of underground coal mines and a novel testing method

The electromagnetic environment of laneways in underground coal mines is an important area for the design of new electronic products,as well as a fundamental space for mine monitoring,surveillance,communications and control systems.An investigation of electromagnetic interference in coal mines is essential for the enhancement of performances of these systems.In this study,a new field method is provided in which radiated emission tests in coal mine laneways have been carried out.We conclude that:1) the wiring motor vehicles can radiate interference with a bandwidth up to 1 GHz and with an amplitude 10 dBμV/m higher than the background noise;2) the PHS(Personal Handy phone System) mobile communication system can cause interference 40 dBμV/m higher than the background noise;3) an interference 25 dBμV/m higher than the background noise can be generated during the communication at a working bandwidth of 48.8 MHz;and 4) power cables,battery vehicles as well as mechanical and electrical dong rooms have little effect on the electromagnetic radiation environment in coal mine tunnels.

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.

A Spectrum Prediction-Based Frequency Band Pre-Selection over Deteriorating HF Electromagnetic Environment

As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in efficient manner becomes one of the key challenges in HF communication. Spectrum prediction infers the future spectrum status from history spectrum data by exploring the inherent correlations and regularities. The investigation of HF electromagnetic environment data reveals the correlations and predictability of HF frequency band in both time and frequency domain. To solve this problem, we develop a Spectrum Prediction-based Frequency Band Pre-selection(SP-FBP) for HF communications. The pre-selection of HF frequency band mainly incorporated in prediction of HF spectrum occupancy and prediction of HF usable frequency, which provide the frequency band ranking of spectrum occupancy and alternative frequency for spectrum sensing, respectively. Performance evaluation via real-world HF spectrum data shows that SP-FBP significantly improves the efficiency of finding quality frequency in HF communications.

The Measurement and Evaluation of the Electromagnetic Environment from 5G Base Station

In order to evaluate the electromagnetic environment of 5G base station, measurement and evaluation of the electromagnetic environment are studied. The 12 measuring points are chosen on the roof, inside and outside of the building, which has a 5G base station on the top. The electric field intensity, magnetic field intensity, and power density have been measured. The measurement methods include background measurement and work measurement. Background measurement is the measurement of environmental electromagnetic field (EMF) before the installation of 5G base station while the working measurement is the measurement after the installation of 5G base station. The evaluation methods include t-test for qualitative evaluation and electromagnetic gain for quantitative evaluation. The results show that the electromagnetic environment after the installation of 5G base station in most places is different from that in the background. And the environmental electromagnetic fields in certain parts are lower than those in the background. The conclusions are as follows: 1) The electromagnetic environment of 5G base station is far lower than the control limit of the national standard and conforms to the national standard;2) The electromagnetic environment of 5G base station has little impact on the electromagnetic environment;3) It is not sufficient to assume that 5G is harmful to health without the results of the epidemiological investigation;4) Before the construction of 5G base station, do background EMF detection, which can provide support for future evaluation.

A Prediction Model of MF Radiation in Environmental Assessment

Objective To predict the impact of MF radiation on human health. Methods The vertical distribution of field intensity was estimated by analogism on the basis of measured values from simulation measurement. Results A kind of analogism on the basis of geometric proportion decay pattern is put forward in the essay. It showed that with increasing of height the field intensity increased according to geometric proportion law. Conclusion This geometric proportion prediction model can be used to estimate the impact of MF radiation on inhabited environment, and can act as a reference pattern in predicting the environmental impact level of MF radiation.

Current Status and Main Scientific Outcomes of the CSES Mission

This report briefly introduces the current status of the CSES(China Seismo-Electromagnetic Satellite)mission which includes the first satellite CSES 01 in-orbit(launched in February 2018),and the second satellite CSES 02(will be launched in 2023)under development.The CSES 01 has been steadily operating in orbit for over four years,providing abundant global geophysical field data,including the background geomagnetic field,the electromagnetic field and wave,the plasma(in-situ and profile data),and the energetic particles in the ionosphere.The CSES 01 platform and the scientific instruments generally perform well.The data validation and calibration are vital for CSES 01,for it aims to monitor earthquakes by extracting the very weak seismic precursors from a relatively disturbing space electromagnetic environment.For this purpose,we are paying specific efforts to validate data quality comprehensively.From the CSES 01 observations,we have obtained many scientific results on the ionosphere electromagnetic environment,the seismo-ionospheric disturbance phenomena,the space weather process,and the Lithosphere-Atmosphere-Ionosphere coupling mechanism.

Transient Response of Twisted Wire Pairs IIIuminated by HEMP

In this paper,the time domain characters of the response of twisted wire pairs(TWPs) excited by the high-altitude electromagnetic pulse (HEMP) have been proposed.The finite different time domain transmission line model (FDTD-TLM) method,which we have proposed previously,is used to calculate the terminal response of TWP.It shows that the time domain response includes two stages:The transient stage and damped stage.The transient stage is the key point of the coupling and protecting research.The influence factors of the transient stage have been analyzed.In the end,we obtain the changes of the induced voltage when the incident wave parameters and TWP parameters change.

Virtual electromagnetic environment modeling based data augmentation for drone signal identification

Radio frequency(RF)-based drone identification technologies have the advantages of long effective distances and low environmental dependence,which has become indispensable for drone surveillance systems.However,since drones operate in unlicensed frequency bands,a large number of co-frequency devices exist in these bands,which brings a great challenge to traditional signal identification methods.Deep learning techniques provide a new approach to complete endto-end signal identification by directly learning the distribution of RF data.In such scenarios,due to the complexity and high dynamics of the electromagnetic environments,a massive amount of data that can reflect the various propagation conditions of drone signals is necessary for a robust neural network(NN)for identifying drones.In reality,signal acquisition and labeling that meet the above requirements are too costly to implement.Therefore,we propose a virtual electromagnetic environment modeling based data augmentation(DA)method to improve the diversity of drone signal data.The DA method focuses on simulating the spectrograms of drone signals transmitted in real-world environments and randomly generates extra training data in each training epoch.Furthermore,considering the limited processing capability of RF receivers,we modify the original YOLOv5s model to a more lightweight version.Without losing the identification performance,more hardware-friendly designs are applied and the number of parameters decreases about 10-fold.For performance evaluation,we utilized a universal software radio peripheral(USRP)X310 platform to collect RF signals of four drones in an anechoic chamber and a practical wireless scenario.Experiment results reveal that the NN trained with augmented data performs as well as that trained with practical data in the complex electromagnetic environment.

COMPARISONS OF RAY-TRACING AND PARABOLIC EQUATION METHODS FOR THE LARGE-SCALE COMPLEX ELECTROMAGNETIC ENVIRONMENT SIMULATIONS

It is important for the wireless communication field to conduct research on large-scale complex electromagnetic environment(CEME)simulation.There exist many models for computing CEME simulation,including empirical models,half-empirical or halfdeterministic models and deterministic models.Most of these models cannot obtain satisfactory results due to the limitation of the capacity of computers.The ray tracing(RT)and parabolic equation(PE)methods are very suitable for large-scale CEME simulation.Based on the introduction of RT and PE,qualitative comparisons of the two methods are analyzed in view of algorithm theory,the category of the model,solution to the model and the application field,and then four specific indices are focused on to analyze the computational complexity,accuracy,speed and parallelism in details.The numerical experiments are presented by the three-dimensional(3D)RT method employing the software of Wireless InSite(WI)and a quasi-3DPE method using the sliced method.Although both RT and PE methods can achieve high speedup using coarse-grained parallel computing,the experimental results indicate that the PE method can obtain a higher speed than the RT method,and the two methods can acquire an approximate precision.A hybrid procedure using both RT and PE methods can obtain a better result for solving CEME problems.

Research on electromagnetic visualization method

It is significantly important to have the knowledge of electromagnet situation of battlefield,because it contains a lot of useful information to understand the situation of the whole battlefield.Electromagnet situation visualization would be very useful to help people to understand the situation,and handle battlefield situation,such as the size and quality of the electromagnetic radiation source,target objects,and operational purposes by the two parties engaged in combat scale.This paper proposes two electromagnet situation visualization methods,one is an isoline tracking algorithm based on floating rectangle and the other is an isoline filling algorithm based on linear interpolation,which also solves the problem of low accuracy and low efficiency.This paper also implements and displays the visualization results using different ways of demonstration modules,which show that the visualization results are more intuitive.

The Harmful Effect on Optical Cable From External Electromagnetic Environment

There is a harmful effect on optical cable in a dangerous electromagnetic environment. The optical cable ed he affected by high-intensity electromagnetic impulse due to temperature rise. This paper will discuss these effects and introduce some protection measures. Finally, we point out other ef fects on optical cable from moisture, nuclear radiation and dangerous industrial environment.

Survey of Technologies of Line Commutated Converter Based High Voltage Direct Current Transmission in China

This paper reviews the applications of line commutated converter based high voltage direct current transmission(LCC-HVDC)technologies in China,with a special focus on UHVDC technology developed in the last 10 years.The paper examines six specific aspects of areas—voltage increase,capacity upgrade,reliability improvement,engineering design innovation,equipment and materials innovation,and the R&D of next step.Subsequent advances in LCC-HVDC technologies in recent years are also discussed.