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In this paper, a novel impact load identification and localization method on actual engineering structures using machine learning is proposed. Three machine learning models, including a gradient boosting decision tree (GBDT) model based on ensemble learning, a convolutional neural network (CNN) model and a bidirectional long short-term memory (BLSTM) model based on deep learning, are trained to directly identify and locate impact loads according to dynamic response. The GBDT model and the CNN model can reversely identify force peak and location of impact loads. The BLSTM model can reconstruct the time history of impact loads. The method is verified on a thin-walled cylinder with obvious nonlinearity. The result shows that the method can accurately identify impact loads and its location. The characteristics of the three models are compared and the influence of structural boundary conditions on the accuracy of identification is discussed. The proposed method has the potential to be applied to various engineering structures and multiple load types.

The inchworm piezoelectric actuator has a wide application prospect in the field of precision instruments. However, in view of the complex structure of the existing inchworm piezoelectric actuator and the far distance between the driving feet of the actuator, it is difficult to realize alternate driving and the high output speed of the driving feet, etc. In this paper, an inchworm piezoelectric linear actuator based on two-stage amplification mechanism is designed, which amplifies the output displacement of the driving feet by two-stage amplification mechanism, and improves the driving efficiency of the actuator stator by the way of alternating driving. We present an inchworm piezoelectric actuator with three piezoelectric stacks and a two-stage amplification mechanism, which is simple in structure design, compact in actuator structure and easy to realize alternate driving. The kinematics and dynamics models of the inchworm piezoelectric actuator are established by analyzing the flexible hinge and its structure with the pseudo-rigid body method. The length of the lever structure and the angle of the triangular structure of the piezoelectric actuator are solved by kinematics, and the natural frequency of the whole structure is calculated by dynamics. Through finite element analysis, the simulation magnification ratio of the piezoelectric actuator is obtained, so as to evaluate and verify the theoretical calculation and further optimize the structure. The experimental results show that the inchworm piezoelectric linear actuator using two-stage amplification mechanism has a high driving speed of 5.53 mm s−1 under voltage of 135 V and frequency of 70 Hz.

With the purpose of the design problem of electromagnetic launch distributed measurement and control system, this paper proposes a design method of scalable large-scale distributed interconnected measurement and control system based on FlexRay bus. The task execution time deviation of each node in the distributed system, including phase deviation and frequency deviation, is reduced by using the macro tick generation process and clock synchronization process to achieve task synchronization in the distributed system. The synchronization of timing generation is realized based on the universal clock technology. When the timing interval is zero, the pulse power units are guaranteed to be close to the ideal full synchronization, thus ensuring that the released energy during transmission is close to the design value. In the state of adjustable timing, when the pulse power supply module conducts pulse discharge, the trigger discharge times of the modules are set according to the load needs. The flat top, sawtooth, and other characteristic current waveforms are adjusted accurately. At the same time, a combined multi-level protection structure based on hardware and software is realized. The verification results show that the distributed electromagnetic launch measurement and control system implemented in this paper can meet the high efficiency, fast and continuous launch target.

The caesium atomic fountain clock is a primary frequency standard. During its operation, a Majorana transition frequency shift will occur once a magnetic field at some special locations along the atomic trajectory is singular. In this study, by developing a physical model, we analyzed the magnetic field requirements for atomic adiabatic transition and calculated the influence of the Majorana atomic transition on the atomic state via a quantum method. Based on the simulation results for the magnetic field in the fountain clock, we applied the Monte Carlo method to simulate the relationship between the Majorana transition frequency shift and the magnetic field at the entrance of the magnetic shielding, as well as the initial atomic population. Measurement of the Majorana transition frequency shift was realized by state-selecting asymmetrically populated atoms. The relationship between the Majorana transition frequency shift and the axial magnetic field at the entrance of the magnetic shielding was obtained. The measured results were essentially consistent with the calculated results. Thus, the magnetic field at the entrance of the magnetic shielding was configured, and the Majorana transition frequency shift of the fountain clock was calculated to be 4.57 × 10−18.

A cardiomyocyte is the basic structural and functional unit of the heart, which is the actual executor of the systolic function. The study of the contraction and relaxation characteristics of cardiomyocyte is of great significance to the physiological behavior and pathology of the heart. How to dynamically express its contraction and relaxation behaviors in 3D has become a challenging issue. Although the video analysis method under the optical microscope can observe the changes in the horizontal direction, it is difficult to describe the changes in the vertical direction. The atomic force microscope (AFM) can accurately express the mechanical and morphological characteristics of the changes in the vertical direction, but it cannot be fully expressed in real time because it is acquired by scanning with a single probe. In order to express the contraction and relaxation characteristics of cardiomyocyte accurately and three dimensionally, a dynamic imaging method in this study is proposed using the periodicity of AFM acquisition and the periodicity of cardiomyocyte contraction. Compared with the optical experiment, it is proven that this method can dynamically represent the contraction and relaxation processes of cardiomyocyte and solve the problem of how to express it in 3D. It brings a new way for the study of physiological characteristics of cardiomyocytes and dynamic imaging by AFM.

Temperature is one of the important parameters of power cables with normal operation. In this article, the electromagnetic and thermal characteristics of three-core cable joints were investigated. And the core and surface temperature gradient were obtained with a three-core cable joint. The research results show that the core temperature of the center is about higher than 14 °C than the body part. The surface temperature is distributed as high at the center and low at the body. The surface fluctuation amplitude of the joint center temperature is about 10 °C. The maximum surface temperature gradient with the center can reach 1697 °C/m of cable joint. The results here should have potential application value in characteristics of electromagnetic-thermal coupling field under the action of internal defects of cable joint.

Using solar energy to enhance the transformation rate of organic molecules is a promising strategy to advance chemical synthesis and environmental remediation. Plasmonic nanoparticles responsive to sunlight show great promise in the catalysis of chemical reactions. In this work, we used a straightforward wet-chemistry method to synthesize plasmonic octahedral gold nanoparticles (NPs) coated with thin molybdenum oxide (MoO3−x ), Au@MoO3−x NPs, which exhibited strong surface plasmon resonance in a broad wavelength range. The synthesized Au@MoO3−x NPs were characterized by UV–vis, SEM, TEM, EDS, XPS, and the electrochemical technique of cyclic voltammetry (CV). The catalytic performance of Au@MoO3−x NPs under visible light irradiation was investigated using the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) as a model reaction. The presence of a thin capping layer of MoO3−x on our Au NPs contributed to the broadening of their range of absorption of visible light, resulting in a stronger intra-particle plasmonic resonance and the modulation of surface energy and electronic state. Accordingly, the kinetics of plasmon photocatalytic transformation of 4-NP to 4-AP was significantly accelerated (by a factor of 8.1) under visible light, compared to uncapped Au NPs in the dark. Our as-synthesized Au@MoO3−x NPs is an example that the range of plasmonic wavelengths of NPs can be effectively broadened by coating them with another plasmon-active (semiconducting) material, which substantially improves their plasmonic photocatalytic performance. Meanwhile, the synthesized Au@MoO3−x NPs can be used to accelerate the transformation of organic molecules under visible light irradiation.

The circuit breaker is a device that cuts off and connects the load circuit in the power system, cuts off the fault circuit, prevents the accident from expanding, and ensures safe operation. Detecting circuit breaker failures is necessary to ensure power systems’ safety. Before fault identification, the circuit breaker must be identified and positioned first. In this paper, a circuit breaker identification technology based on SSD is adopted, and SSD is used to identify the circuit breaker and mark the voltage name quickly.

Temperature is widely used to detect the state of electric equipment. Almost all the data is collected and sorted. And image analyzed by manual, which cause some trouble. In order to improve the intelligence level of power equipment detection, this paper proposes an infrared scene identification method for 220 kV current transformers, including target identification, temperature extraction, and image fusion. Firstly, a semantic segmentation model is built on VGG, which can effectively extract the target temperature information in complex environments. Then combined with the method of data set expansion, 3224 images of 220 kV current transformers were used for training. Finally, an image fusion method is used to extract equipment temperature. The experimental show that the method proposed in this paper for semantic segmentation and identification of 220 kV current transformers accuracy reaches 99.68%. In contrast, the traditional CNN identification method is 44%, effectively improving the target identification efficiency of 220 kV current transformers and has a good reference for electric equipment intelligence detection.

We consider random dynamical systems on manifolds modelled by a skew product which have certain geometric properties and whose measures satisfy quenched decay of correlations at a sufficient rate. We prove that the limiting distribution for the hitting and return times to geometric balls are both exponential for almost every realisation. We then apply this result to random C 2 maps of the interval, random parabolic maps on the unit interval and random perturbation of partially hyperbolic attractors on a compact Riemannian manifold.

Perovskite oxides are promising electrocatalysts for oxygen evolution reaction (OER) in alkaline electrolytes. With high activity and low cost, they are being pursued by researchers worldwide. However, due to the compositional and structural diversity of perovskite-type oxides, the conventional method based on experimental trials on thousands of elemental combinations is inefficient and time-consuming, which hampers the development of this type of electrocatalyst. Here we employed a symbolic regression (SR) method under a machine learning framework to build mathematical formulae that best fit datasets based on 105 experimentally studied perovskite-type electrocatalysts and identified a simple parameter as the OER activity descriptor. Results show that B-site cations with a large number of d electrons and a small radius, such as Ni4+, Co4+, and Fe4+, are beneficial to high OER activity in perovskite oxides, which provide a guide for materials design.

The enhanced Loran signal transmits the signal through the atmospheric channel. Considering the obstacles and other factors, the radio wave will be affected by path loss, shadow fading and multipath fading. Therefore, the signal power at different distances from the transmitting point is different. The scaled model antenna is used to transmit and receive the enhanced Loran signal, and the Loran receiver is used to receive. According to the different power of the received signal of the receiver, the signal propagation distance can be deduced by using the correlation model, so as to correct the path delay, that is, the timing accuracy can be improved.

The coarse sun sensor is used to measure the satellite’s attitude relative to the sun. If the satellite can maintain the earth-pointing attitude by the high-precision sensor, the coarse sun sensor information can be used to determine the satellite’s yaw attitude, which is effective in coping with the short-term failure of the satellite’s yaw attitude sensor. This paper proposes a method to determine the yaw attitude of the satellite using the coarse sun sensor information. In view of the main factors affecting the accuracy of the coarse sun sensor, the measures to improve the yaw accuracy are proposed: the sensor calibration method based on historical data and effective measurement range selection. Simulation with satellite onboard data, the expected function can be achieved, and by correcting the measurement data, the yaw attitude accuracy can be significantly improved.

The multi-objective optimization method for distributed energy storage configuration has the problem of high network loss expectation. A multi-objective optimization method for distributed energy storage configuration under distribution network operation constraints is designed to solve the above problems. The intra-day charge/discharge balance is used as a criterion to identify the characteristics of distributed energy storage configuration, calculate the network loss sensitivity of nodes, construct a siting and capacity setting model, and integrate multiple power quality indicators to improve the multi-objective optimization model under the distribution network operation constraint. The experimental results show that the mean values of network loss expectations for the distributed energy storage configuration multi-objective optimization method in the paper and the other two distributed energy storage configuration multi-objective optimization methods are: 226.731 kW, 270.762 kW, and 276.728 kW, respectively, indicating that the designed distributed energy storage configuration multi-objective optimization method is more feasible after fully considering the distribution network operation constraints.

To solve the problem of low Earth orbit (Leo) satellite constellation link spread spectrum signal acquisition in the high dynamic weak environment, this paper proposes a acquisition strategy based on transfer model. In this paper, we analyze the dynamic characteristics of link signal. An improved method of parallel code phase search acquisition based on transfer model acquisition strategy is introduced, the improvement of the proposed acquisition strategy to the traditional acquisition algorithm is illustrated through theoretical analysis. Simulation results verify the superiority of the acquisition strategy based on the transfer model for high dynamic weak signal acquisition.

The fault diagnosis of a wind turbine gearbox is helpful for reducing the operating costs and risks of wind power systems. However, existing machine-learning-based gearbox fault diagnosis methods have two shortcomings: (a) data samples of gearbox faults are always scarce; and (b) due to the complex structure of gearboxes, the collected vibration signals often contain a large amount of low-frequency noise, which is detrimental to both feature extraction and fault diagnosis. To solve the above two problems, a combination of deep convolutional generative adversarial networks (DCGANs) and a convolutional network with a high-pass filter (CNHF) is proposed in this paper. Among them, the DCGAN combined with one-dimensional (1D) vibration data converted to a grayscale map is used to expand the fault data to solve the problem of a lack of fault data samples. The CNHF is realized by adding an adaptive high-pass filter to the conventional convolutional layer, and the threshold of the high-pass filter is adaptively set by the 1D convolution according to different data characteristics, thus greatly filtering out the interference of low-frequency noise and realizing the accurate diagnosis of faults. Experiments are performed on a drivetrain dynamics simulator rig to verify the efficacy of the proposed method.

Technologies such as external sensors, data acquisition, trend analysis, and cloud services make remote operation and maintenance of equipment status monitoring more convenient and lower maintenance costs. In this paper, an industrial robot operation and maintenance system is designed. First, the online monitoring of the robot is realized by collecting the control parameters, state parameters, fault information and external sensor monitoring information of the industrial robot. Then, the health baseline of the industrial robot is established based on the historical operation data. The online data is compared with the baseline data to realize the online assessment of the robot’s health status. Finally, a visualization platform for remote operation and maintenance of the robot is built to realize the online display of parameters, health trend tracking and fault status early warning, which is convenient for maintenance personnel to take timely countermeasures.

This paper presents an ultra-wide bandwidth (UWB) low-frequency radio astronomical cryogenic receiver for the Five-hundred-meter Aperture Spherical radio Telescope (FAST). It covers 6.6:1 bandwidth from 0.5 to 3.3 GHz. The receiver consists of a Quad-Ridged Flared Horn (QRFH), a cryogenic microwave unit, an optical transceiver and a warm microwave and frequency mixing unit. A QRFH with a concentric-loaded dielectric spear is developed: the average return losses are larger than 20 dB; the average ports polarization isolation is 43.87 dB; the average dish efficiency is higher than 65%. Many UWB cryogenic low loss components are developed for the fabrication of a cryogenic microwave unit. The average noise temperature lower than 14.2 K and 22.5 K are achieved as referred to the input ports of cryogenic Dewar and the output of horn, respectively. Compared to other similar advanced UWB receivers, such as Parkes 0.7–4.2 GHz (6:1 bandwidth) receiver and FAST 0.27–1.62 GHz (6:1 bandwidth) receiver, wider relative bandwidth of the proposed receiver is achieved and it is a new attempt to expand the bandwidth of UWB low-frequency receiver.

The acceleration sensor with high g value is widely used in a variety of fields, including collision impact, aerospace, and defense security and thus is a key focus in the future. The sensor with a double-ended four-beam structure is investigated in this paper via finite element simulation analysis. The measurement sensitivity of the sensor can be improved by changing the position of the cantilever beam. Furthermore, transverse interference in the X-direction and Y-direction can be eliminated in theory through the layout of piezoresistors and the Wheatstone circuit. The simulation results show that the sensor's sensitivity is 2.6μV/g while its cross-sensitivity in the X-direction and Y-direction is 0%, indicating that the sensor's performance has been substantially improved.

With modern society’s increasing reliance on electric energy, rapid growth in demand for electricity, and the increasingly high requirements for power supply quality, sudden power outages are bound to cause damage to people’s regular order of life and the normal functioning of society. Currently, the commonly used emergency power protection equipment is mainly based on diesel generator sets, while there is also flywheel energy storage equipment in the application of emergency power protection. In today’s society, we strongly advocate green, energy-saving, and emission reduction background, and the demand for new mobile power supply systems becomes very urgent. Mobile energy storage vehicles can not only charge and discharge, but they can also facilitate more proactive distribution network planning and dispatching by moving around. The basic model and typical application scenarios of a mobile power supply system with battery energy storage as the platform are introduced, and the input process and key technologies of mobile energy storage devices under different operation modes are elaborated to provide strong support for further input and reasonable dispatch of mobile energy storage vehicles.

The traditional influence on the sidewall damage of Micro-LED was mostly focused on the research of I-V-L. In this paper, we discussed the influence of Micro-LED sidewall damage from the perspective of optical and microstructural characterization. Scanning electron microscopy showed that the Micro-LED structure with smaller size was more irregular after inductively coupled plasma etching. High-resolution transmission electron microscopy and energy dispersive x-ray spectroscopy analysis showed that the area of the upper and lower regions of the quantum well was inconsistent, there was about 2 nm lattice disorder on the surface of the sidewall of the mesa, and oxygen and silicon impurity atoms were enriched. For optical characterization, a method combining laser scanning confocal microscopy and photoluminescence (PL) was proposed to evaluate the optical performance of the mesa. The results showed that the luminescence of Micro-LED mesa was uneven, the luminous intensity at the edge of the mesa was reduced by more than 65%, and the luminous wavelength was shifted by several nanometers. Finally, we optimized the sidewall treatment process, effectively improved the performance of Micro-LED devices by combining tetramethylammonium hydroxide treatment and SiO2 passivation, and increased the luminous intensity of Micro-LED 2 μm away from the edge by about 4.7 times and PL uniformity was greatly improved. These results provided an available reference for the development of Micro-LED.

The preparation of surface-enhanced fluorescence (SEF) substrates is often influenced by experimental strategies and factors such as the morphology and size of the nanostructures. In this study, using the natural reed leaves (RLs) without any special pretreatment as the substrate, metal silver is modified by magnetron sputtering technology to prepare a stable and efficient SEF system. The abundant “hedgehog-like” protrusions on the RL substrate surface can generate high-density “hot spots”, thus enhancement factor (EF) is enhanced up to 3345 times. The stability and reproducibility are verified in many measurements. The contribution of the intervention of silver nanostructure to the radiation attenuation process of fluorescent molecules is analyzed with the aid of Jablonski diagrams. Three-dimensional (3D) finite difference time domain (FDTD) simulates the spatial electric field and “hot spots” distribution of the substrate. The “hedgehog-like” protrusion structure generates multiple “hot spots”, which produce an excellent local surface plasmon resonance (LSPR) effect and provide higher fluorescence signal. Finally, RL/Ag-35 substrate is used to detect crystal violet (CV), and the detection limit is as low as 10−13 M. This “hedgehog-like” SEF substrate provides a new strategy for the trace detection of CV, which has a good practical application value.

The effective-medium theory (EMT) has proved successful in modeling the non-saturating linear magnetoresistance induced by inhomogeneity. However, calculating magnetoresistance using the EMT usually involves solving coupled integral equations which have no analytical solutions, and therefore, it is still difficult to directly compare the predictions of EMT with experimental data. Here we demonstrate that the linear magnetoresistance predicted by the EMT can be either exactly formulated or well approximated by a simple analytical equation Δ ρ / ρ 0 = k 2 B 2 + a 2 − a in a number of known situations. The relations between the EMT parameters and the phenomenological parameters k and a are evaluated. Our results provide a convenient and effective method for extracting the EMT parameters from experimental data.

Diamond based quantum sensing is a fast-emerging field with both scientific and technological significance. The nitrogen–vacancy (NV) center, a crystal defect in diamond, has become a unique object for microwave sensing applications due to its excellent stability, long spin coherence time, and optical properties at ambient condition. In this work, we use diamond NV center as atomic receiver to demodulate on–off keying (OOK) signal transmitted in broad frequency range (2 GHz–14 GHz in a portable benchtop setup). We proposed a unique algorithm of voltage discrimination and demonstrated audio signal transceiving with fidelity above 99%. This diamond receiver is attached to the end of a tapered fiber, having all optic nature, which will find important applications in data transmission tasks under extreme conditions such as strong electromagnetic interference, high temperatures, and high corrosion.

Through the analysis of gas pipeline leakage causes and gas leakage diffusion model, the preventive measures for gas leakage accidents are put forward, which is of great significance for the harm of gas leakage and explosion accidents. In this paper, the mathematical model of gas leakage is established through hydrodynamics and pipeline gas motion equation, and the leakage process is analyzed by means of numerical simulation, the change law of gas dynamic leakage is obtained from the aspects of gas leakage conditions, gas movement and diffusion law.

Urban rainwater pipe network is a direct way to resist urban waterlogging, and its safe and stable operation is the premise to ensure the normal operation of the city. However, in China and even around the world, the monitoring means for the operation of urban rainwater pipe network are very limited. For the occurrence and solution of urban waterlogging, it often mainly depends on the means of personnel inspection to monitor where the rainwater pipe network overflows, and then take measures. There is no effective monitoring method for the whole rainwater pipe network. Therefore, an accurate and efficient rainwater pipe network monitoring method is urgently needed. To solve the current problem of real-time monitoring of rainwater pipe network, the core problem is how to monitor the liquid level data of any pipe section of the whole rainwater pipe network in real time, so it is necessary to introduce hydrodynamic model. The traditional hydrodynamic model mainly simulates the hydraulic and hydrological, and does not simulate the rainwater pipe network, but makes a generalized estimation of the drainage of the rainwater pipe network. In addition, some hydrodynamic models for drainage pipe network are not established for the problem of rainwater pipe network monitoring. The ultrasonic liquid level gauge with real-time acquisition function is not introduced into the calculation simulation, and it does not have the ability of adaptive correction. Therefore, the traditional rainwater monitoring methods and hydrodynamic models can not fundamentally solve the problem of real-time monitoring of the whole rainwater pipe network. Using hydrodynamic model calculation, combined with rain gauge and liquid level gauge to monitor and modify model parameters, so as to intelligently monitor the whole rainwater pipe network, which can greatly improve the current monitoring level of urban rainwater pipe network and reduce the work cost of manual patrol monitoring.

With the increase of fine-grained soil content, the properties continue to transform to fine-grained soil, which will affect the permeability and strength of the soil. Even if the content of silt and clay in fine-grained soil is not high, it will significantly impact soil properties. When the content of coarse particles is low, the nature of soil depends on the fine particles in the soil. When the content of coarse particles gradually increases, and the coarse particles are overhead, the nature of soil only depends on the coarse-grained soil, and the influence of fine particles on the nature of soil gradually weakens. To reveal the interaction mechanism between coarse and fine particles in high moisture content clayey gravel, this project conducts a systematic experimental study on the high moisture content clayey gravel, takes 0.5mm as the particle size limit, takes the separation of coarse and fine particles in the soil sample as the control test, and systematically tests the shear strength of the separated fine particles; systematic shear strength tests were also carried out on the separated coarse particles. In addition, shear strength tests were carried out on soil samples with different fine particle content.

Recent experiments have found that in contrast to the nonsuperconducting bulk RNiO2 (R = Nd, La, and Pr), the strontium-doped R 1 – x Sr x NiO 2 thin films show superconductivity with the critical temperature T c of 9–15 K at x = 0.2, whose origin of superconductivity deserves further investigation. Based on first-principles calculations, we study the electronic structure, lattice dynamics, and electron–phonon coupling (EPC) of the undoped and doped RNiO2 (R = Nd, La, and Pr) at the experimental doping level. Our results show that the EPC-derived T c’s are all about 0 K in the undoped and doped RNiO2. The electron–phonon coupling strength is too small to account for the observed superconductivity. We hence propose that the electron–phonon interaction can not be the exclusive origin of the superconductivity in RNiO2 (R = Nd, La, and Pr).