Interference Characteristics Research Articles

접지 전위 간섭의 특성을 반영한 접지저항 측정 방법

Domestic low-voltage electrical equipments have an environment prone to ground potential interference, due to the characteristics of grounding system. This ground potential interference affects electrical equipments and communication facilities, and amplify the error of ground resistance measurement. It is desirable to find and eliminate the root cause of ground potential interference, however it is difficult to remove that in an environment such as in a dense urban area or an area adjacent to the transmission line. In this paper, the pattern of the potential interference voltage and the effect on the conventional ground resistance measurement are analyzed based on the actual field measurement cases of the ground potential interference, and propose a ground resistance measurement method that reflects the characteristics of ground potential interference.

A Design Method and Application of Backfilling Hydraulic Supports in Reforming Top-Coal Caving Hydraulic Supports

Solid backfilling is an environmentally friendly method of coal mining. Backfilling hydraulic supports are important devices in solid backfill mining. In order to speed up the design and manufacturing process of them, this paper proposes a method of hydraulic support reformation and evaluation. The mechanical models of top-coal caving hydraulic support and backfilling hydraulic support were established to analyze the stress characteristics of the main structure. ABAQUS was used to establish the 3D numerical model to analyze the load-bearing characteristics, as well as verify the strength requirement. In addition, the structural characteristics, compaction characteristics, geological adaptation characteristics, and interference characteristics of the structure were analyzed using motion simulation. After reforming, the ramming force is just above 2.0 MPa, and the utilization ratio of the old parts of the top-coal caving hydraulic support is more than 50%, which saved the costs of the new backfilling hydraulic support and reduced the waste of idle top-coal caving hydraulic support. The successful application of the backfilling hydraulic support in the Tangshan mine showed the rationality of the reform design.

A SOC Estimation Method for Li-Ion Batteries under High-Rate Pulse Conditions based on AO-BPNN Model

The estimation of state of charge (SOC) in lithium-ion batteries is important for ensuring the safe and stable operation of battery systems. Under high-rate pulse conditions, the characteristics of short discharge time, high frequency, large current, strong interference, and complex transient characteristics that make lithium-ion batteries exhibit marked nonlinear characteristics. The existing battery management system has difficulties in capturing the rising and falling edge data of the pulses due to limitations in the sampling frequency. The short idle time makes it challenging to obtain accurate open-circuit voltage, and there are difficulties in identifying the model parameters. Therefore, using a combination of coulomb counting method, open-circuit voltage correction method, and Kalman filtering method to estimate SOC poses certain challenges. This study applies backpropagation neural network (BPNN) combined with Aquila optimizer (AO) algorithm to estimate SOC under high-rate pulse conditions, and experimental verification is performed using special 3-Ah lithium iron phosphate battery. We compared the estimation accuracy of the AO-BPNN model for SOC with the BPNN, support vector machine, extreme learning machine, and Fuzzy neural network models and verified the superiority of AO-BPNN. Furthermore, by utilizing data with larger acquisition intervals, we obtained accurate evaluation results and reduced the data requirements. The effectiveness of the assessment of AO-BPNN was individually verified under different high-rate pulse conditions and different static times through pulse experiments conducted under 9 operating conditions, with the estimation error controlled within 5%. Finally, the robustness of the proposed model was validated using test data with different sampling intervals and random measurement errors.

Criminal characteristics of illegal interference in the operation of automated systems in bodies and institutions of the judicial system

Criminal characteristics of illegal interference in the operation of automated systems in bodies and institutions of the judicial system

A highly explicit electrochemical biosensor for catechol detection in real samples based on copper-polypyrrole.

Catechol is a pollutant that can lead to serious health issues. Identification in aquatic environments is difficult. A highly specific, selective, and sensitive electrochemical biosensor based on a copper-polypyrrole composite and a glassy carbon electrode has been created for catechol detection. The novelty of this newly developed biosensor was tested using electrochemical techniques. The charge and mass transfer functions and partially reversible oxidation kinetics of catechol on the redesigned electrode surface were examined using electrochemical impedance spectroscopy and cyclic voltammetry scan rates. Using cyclic voltammetry, chronoamperometry, and differential pulse voltammetry, the characteristics of sensitivity (8.5699 μA cm-2), LOD (1.52 × 10-7 μM), LOQ (3.52 × 10-5 μM), linear range (0.02-2500 μM), specificity, interference, and real sample detection were investigated. The morphological, structural, and bonding characteristics were investigated using XRD, Raman, FTIR, and SEM. Using an oxidation-reduction technique, a suitable biosensor material was produced. In the presence of interfering compounds, it was shown that it was selective for catechol, like an enzyme.

3D NAND Flash Memory Cell Current and Interference Characteristics Improvement With Multiple Dielectric Spacer

3D NAND Flash Memory Cell Current and Interference Characteristics Improvement With Multiple Dielectric Spacer

Variational time–frequency adaptive decomposition of machine multi-impact vibration signals

The vibration signal of a mechanical equipment shell displays multi-impact coupling characteristics, when reciprocating mechanical vibration signals of large marine diesel engines and petrochemical reciprocating compressors, which exhibits the characteristics of nonstationarity, strong coupling, and strong interference in the time–frequency domain. Signal decomposition and multi-source impact identification have great significance for early fault diagnosis. However, existing decomposition methods for extracting fault frequency bands cannot satisfy demands for extracting impacts from the multi-source impact signals of reciprocating machinery. In this study, variational time–frequency adaptive decomposition (VTFAD) for multi-impact vibration signals is established to decompose and extract single-impact components. A variational model based on the minimization of a spectral center moment is proposed based on the two-dimensional morphological characteristics of energy concentration and discrete distribution in the time–frequency spectrum of the impact signal. An iterative solution is obtained using the alternating direction multiplier method; the time–frequency center and effective time–frequency domain components of the impact are calculated adaptively. A parameter optimization selection scheme is designed for selecting the number of time–frequency domain decompositions and quadratic penalty factor in the optimization process. The test of simulated mechanical multi-impact signals demonstrated that the proposed method can adaptively and accurately identify the time–frequency centers and time–frequency domain characteristics of the impacts in multi-impact vibration signals. VTFAD was applied to a diesel engine connecting the rod-bearing wear-fault vibration signal. The results show that VTFAD can effectively identify the new impacts caused by the fault and accurately extract the key characteristics of the impacts.

Deep learning-driven MIMO: Data encoding and processing mechanism

Large-scale Multiple-Input Multiple Output (MIMO) is the key technology of 5G communication. However, dealing with physical channels is a complex process. Machine learning techniques have not been utilized commercially because of the limited learning capabilities of traditional machine learning algorithms. We design a deep learning hybrid precoding scheme based on the attention mechanism. The method mainly includes channel modeling and deep learning encoding two modules. The channel modeling module mainly describes the problem formally, which is convenient for the subsequent method design and processing. The model design module introduces the design framework, details, and main training process of the model. We utilize the attention layer to extract the eigenvalues of the interference between multiple users through the output attention distribution matrix. Then, according to the characteristics of inter-user interference, the loss minimization function is used to study the optimal precoder to achieve the maximum reachable rate of the system. Under the same condition, we compare our proposed method with the traditional unsupervised learning-based hybrid precoding algorithm, the TTD-based (True-Time-Delay, TTD) phase correction hybrid precoding algorithm, and the deep learning-based method. Additionally, we verify the role of attention mechanism in the model. Extensive simulation results demonstrate the effectiveness of the proposed method. The results of this research prove that deep learning technology can play a driving role in the encoding and processing of MIMO with its unique feature extraction and modeling capabilities. In addition, this research also provides a good reference for the application of deep learning in MIMO data processing problems.

In-situ fault diagnosis for the harmonic reducer of industrial robots via multi-scale mixed convolutional neural networks

The faults of harmonic reducers result in excessive vibration affecting the joint stabilization of industrial robots and manufacturing quality. In-situ fault diagnosis of harmonic reducers can avoid the disassembly of industrial robots to reduce the downtime of production lines. Compared with disassembly diagnosis in an experimental environment, in-situ signals for diagnosis are more complex due to the multi-scale characteristics of harmonic reducers and industrial noise interference. In this paper, an in-situ fault diagnosis method via the multi-scale mixed convolutional neural networks (MSMCNN) model is proposed. The MSMCNN model with the multi-scale feature extraction ability is specially designed for the harmonic reducer of multi-joint industrial robots with multi-scale characteristics, which can extract more comprehensive and complementary fault features from complex in-situ multi-channel signals with industrial noise. Integrated experiments are performed on real industrial robot datasets and public disassembling part datasets for assessing and analyzing the effectiveness of the proposed method. The experiment results show that the MSMCNN achieves 97.08% and is superior to classical and some state-of-the-art congener DL methods in terms of diagnosis accuracy.

Effect of electrified surface casing on the interference characteristics of stray current generated by deep‐well anode beds

AbstractCurrently, the impressed current cathodic protection with deep‐well anode beds has been found that the surface casing was charged. In this study, 13 deep‐well anode beds were selected randomly to investigate whether their surface casings were electrified. Possible causes of the electrification of surface casings are also discussed. A numerical model for simulating the geoelectric field of a representative deep‐well anode bed with an electrified surface casing was established and validated by data from on‐site testing. The difference in the interference characteristics between situations with charged and uncharged casings was also discussed. The results showed that 30.7% of deep‐well anode beds had electrified surface casings. The leading root causes may be that the anode cable had been damaged unexpectedly during the construction process or the electrical resistance between the anodes and the surface casing had been reduced dramatically. The peak potential gradient and comprehensive interference intensity were about 20 times and 3–6 times, respectively, those in situations where the casing was uncharged. A polyvinyl chloride surface casing is, therefore, recommended in deep‐well anode beds. Reliable electrical insulation should be implemented if steel casings are used. Furthermore, regular electrification tests on steel surface casings should be conducted during completion acceptance and daily operation.

Dynamic and high-speed measurement system for blade tip clearance of engine with optical comb

For blade tip clearance measurement, the optical measurement method has the characteristics of high precision, anti-electromagnetic interference, and non-contact measurement. A dynamic and high-speed blade tip clearance measurement system based on time stretch dispersive Fourier transform with the optical comb is proposed and demonstrated. The dynamic experiments are designed to verify the accuracy of the system. The results show that the measuring speed is up to 17.6 MHz and the measurement errors are less than 1 μm under dynamic conditions. The experiments prove that the system has the advantages of high measurement accuracy, high speed, and good repeatability. It can provide a new tool for engine health monitoring.

Theory of holey twistsonic media

Rotating two overlapping lattices relative to each other produces the well known moiré interference patterns and has surprisingly led to strongly correlated superconductivity in twisted bilayer graphene. This seminal effect that is associated with electrons occupying flat dispersion bands has stimulated a surge of activities in classical wave physics such as acoustics to explore equivalent scenarios. Here, we mimic twisted bilayer physics by employing a rigorous sound wave expansion technique to conduct band engineering in holey bilayer plates, i.e., twistsonic media. Our numerical findings show how one flexibly is able to design moiré sound interference characteristics that alone are controlled by the twist angle and the interlayer air separation. More specifically, our numerical approach provides a significant advantage in both computational speed and storage size in comparison with widely used commercial finite-element-method solvers. We foresee that our findings should stimulate further studies in terms of band engineering and exotic topological twisted phases.

Time Domain Measurement System for Electric Field of Radio Interference Generated by Corona Discharge

When corona discharge occurs around the wire, it will be accompanied by the movement of space charge, and then generate corona discharge effects such as radio interference and audible noise. In order to reveal time domain characteristics of the electric field of radio interference generated by corona discharge, a set of time domain measurement systems for radio interference, including oscillator antenna, sampling resistance, and data acquisition system, is developed. Based on the characteristics of corona-generated radio interference and antenna theory, the size of the antenna, the equivalent circuit model, and the selection of sampling resistance are discussed carefully to satisfy the requirements for the measurement of corona-generated radio interference. To verify the effectiveness of the measurement system, an experimental platform with a single corona source is built, and the time domain waveforms of corona current and radio interference are simultaneously measured. Besides, the attenuation law of radio interference is obtained by using a time domain measurement system. The results show that the amplitude of the measured voltage of radio interference decreases exponentially with distance. The time domain measurement system presented in this paper can lay a solid foundation for the time-domain evaluation of the radio interference level generated by corona discharge.

РАНГОВАЯ ОБРАБОТКА СИГНАЛОВ ДАТЧИКА ВИБРАЦИЙ ДЛЯ СИГНАЛИЗАЦИИ ПРИВОДНЕНИЯ САМОЛЕТА-АМФИБИИ В УСЛОВИЯХ АПРИОРНОЙ НЕОПРЕДЕЛЕННОСТИ

The purpose of the work is to use a rank model of signal processing for signaling the landingof an amphibious aircraft. Rank processing refers to nonparametric methods of detecting asignal against a background of interference. Nonparametric methods are used if the functionaltype of the input data distribution is unknown and only the most general differences between thepresence and absence of a signal are indicated. Almost all nonparametric detectors contain devicesas a component element that perform some invariant transformation of the S array of samplevalues of X. As a result of this transformation, a new array Z = SX is formed, the distribution ofelements of which is precisely known in the absence of a signal. The transformation S, which ischosen heuristically, allows us to reduce the problem of detecting a signal against a backgroundof interference with an unknown distribution to the problem of testing a simple hypothesis regardingthe distribution of the array Z. Research objectives: 1) preliminary digital filtering of amphibiousaircraft flight records for the use of rank processing; 2) conducting an experiment to obtainthe characteristics of a rank detector used to signal the landing of an amphibious aircraft;3) analysis of the results obtained. A model of signal processing of a vibration sensor for signalingthe landing of an amphibious aircraft is proposed. The model consists of a bandpass filter (PF), aCOEX calculator, a divider, a rank detector and a reference sample generator. The rank detectorallows you to reduce the task of detecting the vibration sensor signal against the background ofinterference to the task of testing a simple hypothesis regarding the distribution of ranks. The nonparametricWatson agreement criterion is used to make a decision on the presence of a drive signal.The proposed processing model provides the following parameters of the flood alarm system:1) insensitivity to changing characteristics of signals and interference, 2) the decision-makingalgorithm guarantees high quality of detection in conditions of significant a priori uncertainty.The results of the conducted studies show: 1) the distribution of ranks in the absence of a signal isalways approximated by a uniform distribution law. In situations where a signal is present in themixture, the uniform distribution is destroyed, and the presence of a signal is determined by a setthreshold, 2) the sensor based on rank criteria provides high quality detection of the amphibiousaircraft landing signal. The proposed approach to solving the detection problem can find a placein many applied problems where there is a priori uncertainty. For example, in radar, sonar, communications,medicine and other fields of science and technology.

Research on RCS Jet Interaction Characteristics of the Capsule Entry Vehicle at Subsonic and Transonic Speed

In this paper, the RCS jet interaction characteristics of the capsule entry vehicle were studied by numerical simulation. The jet interference characteristics under different re-entry ballistic parameters were compared. The influence of the angle of attack on the jet flow field structure and aerodynamic characteristics was analyzed.

Evaluation of the heat extraction performance of an abandoned well pattern in multilayer commingled production oil reservoirs

Oilfield geothermal energy is one important part of geothermal resources, and it can be developed and used for power generation and heating. The geothermal reserves and production of multi-layer sandstone oil reservoirs account for 50% of the total geothermal reserves and production in China, respectively, but due to the influence of interlayer heterogeneity, interlayer interference is common in the process of geothermal development by water injection. Therefore, it is in an urgent need to evaluate the heat extraction performance of oil-bearing geothermal reservoirs in multi-layer commingled production. Taking a depleted oil reservoir (and even a high- or an extra-high water-saturation oil reservoir) as the research object, this paper establishes a numerical model of coupled oil–water two-phase heat flow in a multi-layer commingled production oil reservoir. Then, interlayer interference characteristics and temperature and pressure distribution situations under different porosity, permeability and initial oil saturation are compared. Finally, the influence of interlayer interference on heat extraction performance is analyzed. And the following research results are obtained. First, under the research conditions and model settings of this paper, the injection–production pressure difference and production temperature difference between low-permeability layers and high-permeability layers of the reservoir with different permeability after 20 years' production are up to 3.27 MPa and 24.5 K, respectively, which are much higher than the corresponding differences of oil-bearing homogeneous reservoirs. Second, the lower the initial oil saturation, the smaller the reservoir production temperature and injection–production pressure difference. And after 20 years, the maximum difference is 1.32 MPa. Third, interlayer interference is sensitive to permeability. The fluid in the high-permeability layers comes from the injection well of the same layer and low-permeability layers. The production temperature of the reservoirs with different permeability can rise by 5.33 K at most. In conclusion, permeability is the key parameter influencing production temperature and injection–production pressure difference of oil-bearing reservoirs while porosity has less influence on production behaviors. In addition, injection–production pressure difference is more sensitive to the change of initial oil saturation and the existence of oil phase can increase the injection pressure significantly. Furthermore, if there is a boundary geothermal source, the reservoirs with strong interlayer interference can obtain high heat extraction more easily, so this type of reservoirs can be given priority in the heat extraction of abandoned wells.

Study on energy conversion characteristics and pressure fluctuation interference characteristics between two stage impellers of the pump as turbine

The process pump as turbine (PPAT) is an important infrastructure in chemical and oil refining process. When it operates in pump mode, it can provide high-pressure energy for chemical and oil refining system, and when it operates in turbine mode, it can recover the high-pressure energy from the oil medium. The operation stability of PPAT directly affects the normal operation and production of chemical and oil refining process. In this paper, the velocity slip characteristics of the PPAT in turbine mode and pump mode were studied, and the unsteady operation characteristics and the energy conversion and distribution mechanism of the first-stage impeller and second-stage impeller in pump mode were mainly studied, the pulsation amplitude frequency characteristics and induction mechanism of flow passage components under different flow conditions in pump mode are analyzed. The results show that PPAT has an efficiency peak in both pump mode and turbine mode, and the efficiency zone is significantly wider and the velocity slip loss is smaller in turbine mode; In turbine mode, with the increase of flow, the velocity slip loss of the first-stage impeller is larger than that of the second-stage impeller; In the pump mode, the velocity slip loss of the first-stage impeller is greater under the conditions of minimum flow and maximum flow, the pressure fluctuation in the PPAT is mainly distributed in the first stage diffuser and the second stage diffuser. The main factor causing the pressure fluctuation in the PPAT is the dynamic and static interference effect between the first-stage impeller and the first-stage diffuser.

Influences of salinity and temperature on propagation of radially polarized rotationally-symmetric power-exponent-phase vortex beams in oceanic turbulence.

In this paper, the propagation properties of radially polarized rotationally-symmetric power-exponent-phase vortex beams (RP-RSPEPVBs) in oceanic turbulence were theoretically and experimentally studied. Based on the extended Huygens-Fresnel diffraction integral and vector beams theories, the theoretical propagation model of RP-RSPEPVBs in the oceanic turbulence was established. Then, the numerical simulations were carried out to study the influences of the propagation distance z, the rate of dissipation of turbulence kinetic energy per unit mass of fluid ε, the temperature-salinity contribution ratio ω, and the dissipation rate of the mean-squared temperature χT on the optical intensity, spectral degree of polarization (DOP) and spectral degree of coherence (DOC) of RP-RSPEPVBs. Further, an experiment setup was demonstrated to confirm the influences of salinity and temperature on propagation of RP-RSPEPVBs in oceanic turbulence. The results showed that increasing salinity, propagation distance, and turbulence intensity, will result in beam diffusion and intensity reduction of the RP-RSPEPVBs, as well as depolarization and decoherence. Contrarily, high temperature mitigated the intensity loss of the RP-RSPEPVBs and the spectral DOP and spectral DOC increased when the turbulence tends to be dominated by temperature. As a vector beam, the RP-RSPEPVB shows well anti-turbulence interference characteristics, which provides a new choice for optical underwater communication and imaging.

Study on Reradiation Interference Characteristics of Steel Towers in Transmission Lines

With the development of ultrahigh-voltage transmission lines in China, the reradiation interference caused by the steel tower used in ultrahigh-voltage transmission becomes increasingly aggravating for nearby radio stations. In this paper, using the multilevel fast multipole algorithm, the reradiation interference of an ultrahigh-voltage transmission steel tower is investigated. Additionally, the reradiation interference characteristics of a transmission steel tower were investigated with various frequencies and azimuth angles of incidence wave. The results show that the frequency and the azimuth angle of incident wave are the impact factors for the reradiation interference of steel towers. It is better to use a detailed angle steel model for the truss structure of steel towers at high frequency, while a simplified structural model can be used at low frequency. Additionally, the diffraction at the edge of the angle steel has a great influence on the reradiation interference, particularly at high frequencies.

Improvement of the SPICE Model of Diode Based on Measurement and Nonlinear Fitting Random Optimization Algorithm

This paper proposes a modeling method for improvement of the SPICE Model of a diode based on measurement and a nonlinear fitting random optimization algorithm. First, the mechanism of electromagnetic interference generated by diodes at high frequencies was analyzed: dynamic characteristic parameters such as reverse recovery of diodes and junction capacitance. Second, the method of obtaining the I-V characteristic curve and junction capacitance characteristics of the diode through testing was introduced in detail, and a nonlinear fitting random optimization algorithm was proposed to calculate the static and dynamic characteristic parameters of the diode, which can be applied to improvement of the SPICE model of the diode. A simulation and test circuit were built, and the simulation and test results were compared in the time and frequency domains. The model in this study can not only truly reflect the peak voltage owing to the electromagnetic interference characteristics, but also ensure that the harmonic components and component amplitudes are within three times the fundamental frequency, verifying the accuracy of the electromagnetic compatibility model.