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Plasmonic nanocavities formed by a metal nanoparticle located close to a thin metal film or other nanoparticle are of great interest for nanophotonics. Their properties can be used for optical superresolution, optoelectronics, and the creation of new materials with increased non-linearity. However, the interpretation of Raman spectra enhanced by a nanoresonator is complicated by depolarization effects. In this work, the analysis of tip-enhanced Raman scattering (TERS) on a single organic molecule in the plasmonic nanocavity formed by a metal tip and a gold substrate is carried out. The linear and nonlinear regimes of TERS are considered. The reasons for the selective enhancement of Raman spectral bands are analysed using anisotropic molecule of the free base porphyrin (FBP) dye as an example. The observed vibrational symmetry of the molecule changes even greater in nonlinear regime of spectroscopic TERS measurements. We believe that our results are beneficial for the development of the tools to control vibrations of molecules at the nanoscale.

In order to better understand the influence degree of temperature curve parameters on the growth characteristics of intermetallic compounds (IMC) in solder joints during reflux welding, the influence of different temperature curve parameters on the thickness of IMC in Sn63Pb37 solder joints was explored based on the orthogonal test method. A multiple regression model was established for each parameter and the thickness of IMC. In addition, the results show that: (1) The influence degree of temperature curve parameters on IMC thickness in descending order is the highest temperature, liquidus time, cooling time and cooling rate. (2) The coefficient of the established multiple regression model is R2=0.70391. In this model, the IMC thickness increases with the increase of the maximum reflow temperature and liquidus time and decreases with the increase of the cooling time. (3) When the thickness of IMC is 1 μm- 4 μm, the thermal shock reliability of solder joints decreases with the increase of IMC thickness.

Canadian gum, epoxy resin, and emery are used in the production of general rock thin section materials. These materials have fluorescence, so it is not possible to make fluorescent thin sections. The use of other colloids or transparency is not good, because the use of abrasive emery will also lead to the specimen having fluorescence, which cannot be selected. At present, 502 is usually used to make fluorescent sheet adhesive in China, but the colloid is soluble in water and the colloid is not impact-resistant. During sample preparation, it cannot be used for a long time by water grinding, only dry grinding or oil grinding. The samples of water grinding are susceptible to moisture and scratches, so the rock sheet cannot be preserved for a long time, which seriously affects the efficiency and quality of production. In recent years, the team has come up with a variety of materials and methods to make fluorescent rock-thin sections through repeated trials and achieved good results.

To improve the operation economy of the microgrid in a complex environment, a low-carbon operation strategy of microgrid with distributed compressed air energy storage is proposed. Firstly, considering the complex environment of regional microgrids, the coupling structure of distributed compressed air energy storage systems and microgrids is proposed. The new energy output and compressed air energy storage system model are established. On this basis, considering the consumption of new energy, a low-carbon operation strategy of the microgrid is constructed to improve the consumption level of new energy in the microgrid. Finally, the feasibility and competitiveness of the proposed low-carbon operation scheme are verified by simulation. The results show that the operation strategy of a low-carbon microgrid with distributed compressed air energy storage can reduce the operation cost by 57.3 %, and the new energy consumption rate can reach 97.2 %. The research results provide a theoretical basis and decision-making reference for applying distributed compressed air energy storage systems in complex environments.

The konjac polysaccharide aerogel filter rod has the functions of high filtration efficiency and cooling. The biodegradation rate of konjac polysaccharide aerogel filter rod prepared by vacuum freeze drying machine was studied in this paper. The results showed that at the end of the degradation experiment (the 106th day), the biodegradation rate of konjac polysaccharide gel filter rod reached 84.9%, which was close to the degradation rate of thin-layer chromatography grade cellulose, indicating that it had good biodegradability.

The repowering of wind farms is a rapidly developing area of research and is expected to represent 40 GW of wind projects by 2030 in the European Union. This has led to the emergence of energy yield assessment methods that incorporate operational data from existing farms with the aim of surpassing traditional methods that rely solely on physical modelling and onsite measurements. The current literature on repowering relies upon the assumption that learning from operational farm data applies to the future farm. Indeed, calibration and adjustment methods assume that physics-driven models (PDMs) have spatially and temporally correlated errors. This study investigates this assumption by analysing PDM errors for 25 pairs of nearby wind projects. A statistically significant correlation is observed. We discuss whether it is reasonable to utilise operational data from existing farms, which possess different characteristics, to improve the long-term production prediction of a repowered farm.

Safety is an important factor restricting the cascade utilization of lithium-ion batteries (LIBs). In this paper, the safety characteristics of fresh and retired lithium iron phosphate batteries are investigated by means of a heating-triggered thermal runaway (TR). The results show that under the heating condition of 200 W, the internal short circuit (ISC) can directly cause the TR of a new battery and lead to an explosion with an overpressure of 98.9 kPa. However, there is still a buffer time of 13.1-22.3 min between the ISC and TR for the retired battery with states of health (SOHs) of 80% - 60%, and the retired battery cannot explode. The large-scale ISC onset time, TR onset time, and TR onset temperature of the 70% SOH battery are 27.4 min, 40.5 min, and 179.9 °C, respectively, which are the smallest among retired batteries, indicating that the 70% SOH battery may be more likely to trigger TR. The findings can provide guidance for the safe application of retired batteries.

The purpose of this paper is to present a parametrized relativistic quantum theory (pRQT) in curved spacetime. The formulation of pRQT in curved spacetime is developed and applied to free particle motion in flat and curved spacetime. It provides a theory for calculating probability amplitudes in curved spacetime. Unlike other formulations of parametrized relativistic dynamics (pRD), this work assumes that the metric tensor does not depend on the invariant evolution parameter.

With the rapid development of the Internet, the length and themes of text content in social network environments are becoming more and more abundant. The probability and degree of semantic similarity between different words in different texts are also increasing. It is difficult to effectively identify text topics and their sentiment tendencies. This paper takes the text data of the Ford Forum of the PCauto as the research object, builds a word vector model based on Word2vec, uses HDBSCAN to classify social network context, and calculates the sentiment value of different topic through SO-PMI. It aims to explore the complexity of the semantic evolution and feature extraction process and its generating text topics, based on which we further analyze the variability of sentiment tendencies between words and topics and then summarize their characteristics.

Otto Stern’s 1933 measurement of the unexpectedly large proton magnetic moment indicated to most physicists that the proton is not a point particle. At that time, many physicists modeled elementary particles as point particles, and therefore Stern’s discovery initiated the speculation that the proton might be a composite particle. In this work, we show that despite being an elementary particle, the proton is an extended particle. Our work is motivated by the experimental data, which we review in section 1. By applying Occam’s Razor principle, we identify a simple proton structure that explains the origin of its principal parameters. Our model uses only relativistic and electromagnetic concepts, highlighting the primary role of the electromagnetic potentials and of the magnetic flux quantum Φ M = h/e. Unlike prior proton models, our methodology does not violate Maxwell’s equation, Noether’s theorem, or the Pauli exclusion principle. Considering that the proton has an anapole (toroidal) magnetic moment, we propose that the proton is a spherical shaped charge that moves at the speed of light along a path that encloses a toroidal volume. A magnetic flux quantum Φ M = h/e stabilizes the proton’s charge trajectory. The two curvatures of the toroidal and poloidal current loops are determined by the magnetic forces associated with Φ M . We compare our calculations against experimental data.

“Green” hydrogen produced using electrolysis and zero-carbon electricity may be a path for the EU to reduce its dependence on natural gas imports and support the green transition. The EU uses 10 Mt of natural gas yearly for hydrogen production, representing a potential 120 GW market for the wind industry. Placing the hydrogen production (electrolysers) near the energy source (wind turbines) instead of the consumer (e.g. fertiliser producers) changes the energy transportation from power to hydrogen and opens new design possibilities. This work investigates how an off-grid wind turbine designed for hydrogen production may differ from a traditional one. The paper first describes the numerical modelling framework used to estimate the hydrogen production and cost of a “hydrogen wind turbine.” The main parameters of the system (generator rating, rotor diameter, electrolyser rating and battery capacity) are then optimised to reduce the levelised cost of hydrogen (LCOH). Results show that an LCOH-optimised wind turbine should have a lower specific power (i.e. a larger rotor) than an LCOE-optimised design. We find a 7% LCOH reduction compared to the reference system, opening the door for future wind turbines designed directly for hydrogen production.

In this paper, an ultrasonic target identification system based on Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) is proposed to improve the productivity efficiency of industrial production. The proposed system can accurately identify targets of different shapes. Two pieces of 3 × 3 PMUTs arrays with a resonant frequency of 115 kHz are used as the transmitter and receiver of the PMUTs-based ultrasonic sensor. The sensor is small in size and has high instability. In addition, the PMUTs based ultrasonic sensors have lower environmental requirements than vision sensors and are less expensive than laser sensors. Therefore, the sensors are suitable for large-scale use in industry. The characteristics of the proposed system are investigated in the shape experiments on the square, circle, frame, and ring targets. The four kinds of targets are acrylic plates with a thickness of 5mm. The experimental results show that the system can accurately identify the shapes of the four targets through the grid-based scheme. Besides, the identification process is automatically completed by the 3D mobile platform. The proposed system has demonstrated a cost-effective method to identify targets of different shapes, which can more efficiently guide the robotic manipulator’s grasping and other behaviors.

The aim of this study is to compare the hardness of Co–Cr metal alloy specimens made by different methods and how it is influenced by multiple temperature changes. Fifty-four samples are made by three different methods and are accordingly divided in three groups – group M (Milling), group LP (Laser Printing) and group LW (Lost Wax), with 18 samples each. All of them contain three subgroups with six samples – metal samples with no thermal cycles (subgroup 1), metal samples with one thermal cycle (subgroup 2) and metal samples with two thermal cycles (subgroup 3). Their Vickers hardness is evaluated by a weight of 1 kg applied for 20 s. The results are presented in tables. The average hardness is the highest for group LP – 509, followed by group M – 440, and for group LW it is 401. For the subgroups, the best results are exhibited by the samples of subgroup 2 – 430, followed by subgroup 3 – 457, and subgroup 1 – 450.

ANSYS workbench finite element analysis software was adopted to simulate and study the thermal process of electron beam welding of T2 copper and 304 steel heterogeneous materials in this paper. A solid model was established according to the size of the specimens, and a double ellipsoidal moving heat source model of the temperature field of the specimens of the three-dimensional dynamic simulation was imposed. Copper and steel welding transient temperature field distribution pattern and molten pool morphology were studied, and the temperature field welding thermal cycle curve was analyzed. The results show that the peak temperature of the steel side is higher than the copper side, the morphology of the welding pool is basically biased toward the steel side, and the highest temperature during the welding process appears in the center of the weld on the steel side about 0.5 mm.

To solve the problems with the penetrant testing of transportable pressure vessels (“TPVs”), such as failure to detect near-surface defects, low testing efficiency, and damage of penetrating agents to testers’ health and the high-purity media in the TPVs, an experimental study on the eddy current array (“ECA”) testing technology is carried out, and the result is compared with the results of the dye penetrant testing and fluorescent penetrant testing. According to the experiment result, the ECA testing technology is characterized by moderate requirements for the status of the surface to be tested, fast testing, environmental-friendliness, electronic data storage, testing imaging, and accurate testing results. These advantages enable the ECA testing technology to be a green and environmental-friendly nondestructive testing technology that will promote future development and have exciting prospects in TPV testing.

With the development of a new generation of radar performance requirements, the chip integration and module assembly density of onboard electronic equipment have been greatly improved. The integration of the system is becoming more complex. This paper designs a kind of electronic equipment with a superposition structure. Separate functional modules are strung together by a screw. Each module unit has the same sectional size. The conventional cabinet form structure is abandoned. The main contradiction of volume, weight, and reliability is solved well. The mechanical properties of electronic equipment are analyzed by the finite element method, and the structure of the fixed lug is optimized. The result shows that the electronic equipment meets the requirements of structural safety margin. The structural design is safe and reliable.

Wind power as a renewable energy source has both strong fluctuations in output power affecting the power balance in real-time operation of the system. In power systems with high wind power penetration, energy storage devices are used to dissipate wind energy and achieve optimal allocation of resources for generating units and storage devices to meet economic requirements. In this paper, we mainly use horizontal planning and vertical planning to calculate the total cost of power generation and the optimal wind power access to optimize the output quota of each unit.

The proper design of buildings should ensure that the indoor conditions are comfortable, and users experience thermal comfort throughout the year, especially in sophisticated, modern intelligent buildings. The existing model of thermal comfort comes from the 60’s/70’s and was the basis for the ISO 7730 Standard. It utilizes the concept of the PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) indicators. The current paper compares the actual expressions of people (as indicated by them in the anonymous questionnaires) with the PMV/PPD values calculated according to the Standard. Differences between these values have been discussed and conclusions have been drawn as to the usability of this thermal comfort model in intelligent buildings, which still seem to be a novelty in Central European countries and data on their thermal comfort performance is still quite modest.

Today’s healthcare system relies heavily on medical imaging to carry out non-invasive diagnostic treatments. For clinical analysis, it entails the development of graphical and functional models of the human body and organs. In order to diagnose non-small cell lung cancer, the Multi-resolution patch (MSP) approach is introduced in this study. The model can enhance detection performance by utilizing an atrous convolution network, however caution must be used while selecting the atrous rate. More data from many institutions is needed to improve the generalization of the model because the validation CT data was only collected at one center; this dataset included lung CT imaging data from healthy individuals. The outcome indicates that the model’s performance can be further enhanced by include data from healthy individuals in the training process. Additionally, two sets of experiments show the value of the pre-processing module and the superiority of the suggested network.

In order to explore the influence mechanism of different parameters on Multi-rotor aircraft dynamic characteristics, Hamilton principle and the theory of medium deformation beam were used to derive the rotors/nacelle/wing coupling structure dynamic equation, and a solution method suitable for the analysis of coupled modal was established. By using literature as an example calculate rotor and wing modal, the error is less than 5% compared with the experimental results in the literature, indicating that the coupling model in this paper is accurate and effective. On this basis, the influences of, nacelle offset, rotor collective pitch, blade center of mass on the coupling modal are studied.

The development of regenerative braking technology for a pure electric vehicle is the key technology to solving the current limited range of the electric vehicle. Accurately identifying the driver’s braking intent is fundamental to controlling the braking system of an electric vehicle.A brake intent recognition controller is designed in this paper, which is based on a lot of driving data and fuzzy principles. In addition, two typical regenerative brake control strategies are compared. The simulation results of Matlab/Simulink and AMESim show that the SOC of the power battery increases obviously at different braking intensities of 30 km/h. Besides, energy recovery is up to 20.5%, and battery energy increases by 6.5 wh.

This paper takes PWM modulated DC-DC Buck converter as the object to improve the traditional LADRC method. Firstly, the LESO module directly feeds back an error differential signal, which can improve its disturbance observation performance. Secondly, the disturbance differential term is imported to the LESO module to enhance the observation speed of disturbance. Finally, a first-order inertial link is joined to the disturbance estimation channel to suppress the high-frequency noise disturbance caused by the increase in observation bandwidth. By analyzing the frequency response characteristic curves of the improved LADRC method and the conventional LADRC method, it can found that improved LADRC method has preferable disturbance resistance performance. Using Simulink model, experimental consequence confirm the availability and correctness of the optimization method.

In previous publications, it was argued that because energy and matter are aligned in the thin increment of present time for an observer, spacetime should and must have surface tension. In this paper, we review how to apply 4-dimensional continuum mechanics with imaginary time coordinates to derive a mechanical model of spacetime with surface tension. Then, to continue model development, we discuss the concept of preferred curvature from the physical chemistry of surfaces and attempt to apply those concepts to spacetime geometry. We show how the model exhibits quantum fluctuations at the Plank scale and components resembling dark matter and dark energy at the cosmic scale.

More than two-thirds of freshwater consumed worldwide are used for irrigation, and the existing control system for irrigation and fertilization is not intelligent and efficient enough. It is necessary to improve the utilization efficiency of irrigation water and fertilizer, and the intelligent level of irrigation and fertilization system. We have built tomato fertilizer deficiency and fertilization decision model based on leaf images and deep learning, this paper develops an Raspberry Pi-embedded intelligent control system for irrigation and fertilization based on previous deep learning models. The system included sensors, image acquisition, control part, control panel and remote control, the type of main hardware and sensors were selected, and the circuit of the system were designed. The C language is used to compile the source code of the deep learning framework, and the Python language is used to compress the deep learning model. The result shows that the compression rate of the deep learning model can reach 36.7% and the decision-making time can be shortened by 36% under the condition of ensuring the model accuracy. The Raspberry Pi-embedded intelligent control system can help farmers improve the utilization efficiency of irrigation and fertilizer.

In order to evaluate the vibration state of the overhead line, the φ-OTDR (phase-sensitive optical time-domain reflectometry) is applied to the vibration monitoring for the optical fiber composited in overhead transmission line. The principle of φ-OTDR and the IQ demodulation algorithm is introduced. Common mono-mode dark optical fiber simulates the optical fiber composited in an overhead line. The sinusoidal vibration is applied to the optical fiber using an arbitrary waveform generator and piezoelectric ceramic transducer (PZT). The vibration status in the optical fiber is measured by optical fiber vibration monitoring system using φ-OTDR. The result reveals that this system can demodulate the vibration applied to the optical fiber. This paper provides a reference for vibration monitoring optical fiber composite overhead lines.

Fault diagnosis of rolling bearings has become a critical measure to ensure the security, efficiency, and availability of wind turbine systems. In this work, an approach called a transfer deep learning network is reported to resolve the drawbacks of existing rolling bearing fault algorithms on the basis of deep learning, such as large training parameters, long training time, and insufficient training samples. The reported approach mainly consists of two steps: feature transfer using transfer component analysis and network transfer using the pre-trained convolutional neural network. One dataset of rolling bearings with four fault types is gathered to estimate the classification performance, and the peer model is employed for a comparison study. The derived research results show that the reported algorithm based on the feature transfer and the network transfer can yield outstanding results in the rolling bearing fault diagnosis.

The EHV transformer is one of the core transmission equipment of China’s EHV/UHV transmission system, and its reliability directly affects the operational stability of the power grid. In the long-term operation process, affected by sudden short-circuit, resonance, and aging, it will produce faults such as loose winding, loose iron core, inverted discharge, and shim block shedding. Most of the methods for transformer fault diagnosis need off-line monitoring and cause some damage to transformer equipment. At present, the use of transformer acoustic signal for diagnosis and identification is in the initial stage, and there is still room for improvement in the accuracy of fault diagnosis, and how to classify the unbalanced data samples also deserves attention. Therefore, an EHV transformer fault diagnosis method based on acoustic perception and sparse autoencoder-BNCNN is proposed in this paper. Firstly, the sparse autoencoder is trained to ensure the processing ability of the network on imbalanced data. Then, the high-step CNN network is optimized using the BN layer, the data is fed into the improved CNN network for feature extraction, and the classifier outputs the fault diagnosis results. Finally, the transformer acoustic data are processed, and the dataset is formed to evaluate the performance of the proposed method. The experimental results show that the proposed method not only improves the accuracy substantially compared with other methods but also has the ability to handle imbalanced data.

In order to make full use of node energy and extend the network’s lifetime, a data fusion algorithm for wireless sensor networks is proposed in this paper. The algorithm improves the traditional clustering routing protocol and introduces a deep learning model to build the data fusion algorithm based on the optimized clustering architecture. When optimizing cluster routing protocol, the cluster head is selected by comprehensively considering such factors as node density, residual energy of nodes and the reasonable cluster size. The deep learning model and classification model are introduced in the data fusion process. The optimal parameters of the network are obtained by training the deep learning model of the sink node, then the sink nodes transfer these parameters to the corresponding sensor nodes. The cluster head extracts, classifies and fuses similar features of the data. The nodes in the cluster use the deep learning model to fit the collected raw data. Simulation results show that the data fusion algorithm proposed in this paper can reduce the redundant data transmitted to the sink node of wireless sensor networks, reduce the network energy consumption and prolong the network’s life. The overall performance of the network is improved.

Due to its material, function, safety, and other characteristics, there are also special requirements in terms of the design and verification of civil aircraft batteries. This paper studies the airworthiness compliance design method of the civil aircraft battery system. First, it introduces the battery technology used in mainstream civil aircraft, obtains specific design requirements by analyzing the airworthiness clauses applicable to battery systems, and then proposes the key issues that need to be considered in the design process of civil aircraft battery systems based on these design requirements. That is to say, the design of a civil aircraft battery system must fully consider the requirements of function, performance, and installation, which are defined in airworthiness regulations, and then it can be used safely on a civil airplane.

In this paper, the composition of the drag-free CubeSat platform was introduced first. Then the control strategy of drag-free CubeSat orbit keeping was proposed. Finally, the simulation with the control scheme of the Homan transfer orbit was compared. By comparing and analyzing the fuel consumption of the drag-free track and Homan transfer track, it is demonstrated that the continuous drag compensation of the drag-free control scheme can significantly reduce the consumption of thruster mass, and the drag-free technology has good advantages in track stability.

The fault conditions at the receiving end of the hybrid cascaded UHVDC project cause the transmission energy to be blocked, and the sending end cannot respond quickly in a short time, resulting in temporary excess power in the receiving system. A DC controllable self-recovery energy dissipation device for a hybrid cascaded UHVDC project is proposed. The related technical research is carried out, the working principle of the controllable self-recovery energy dissipation device is explained, and the design scheme of the controllable self-recovery energy dissipation device is given. Finally, the feasibility and reliability of the controllable self-recovery energy dissipation device for suppressing system transient overvoltage are verified by simulation. The successful development of the controlled self-recovery energy dissipation device provides a new technology for suppressing transient overvoltage of hybrid cascaded UHVDC faults.

It has been researched that the surface structure of many organisms has unique resistance reduction properties and it is important to replicate the morphological features of the biological body surface on the material surface. So, a method for creating a biomimetic fish-scale surface using a laser is proposed by observing the laminar arrangement features of three common fish scales on the body surface, and a composite structure of bionic fish scale macrostructure and different microstructures of bionic fish scale were machined on on aluminium alloy surfaces. The surface morphology and elemental composition were characterized before the resistance reduction test. The results indicate that both the biomimetic fish-scale macrostructure and composite structure have an obvious effect of reduced drag, among which, maximum resistance reduction can be achieved 44.02% at a flow rate of 0.6 m/s for the bionic carp fish scale composite structure.

Modelling of evaporative condensers relies heavily on the correct choice of the correlations for transport coefficients to give an accurate estimate of the dissipated thermal load and evaporated water mass flowrate, yet the literature does not cover all flow arrangements, nor operating conditions. In order to avoid expensive, and often impractical, experimental campaigns devoted to the determination of these quantities for a specific piece of equipment, a statistical approach based on the analysis of variance can be adopted: by analysing the sensitivity of the dependent variables on the choice of the transport coefficients, the best set of correlations can be determined, depending on whether a more accurate estimate is desired for the heat flux or evaporated mass flowrate, or if both are equally important.

Owing to their unique material design-ability and excellent weight reduction properties of carbon fibre reinforced polymers(CFRP), commercial aircraft OEMs have been innovating design and manufacturing approaches to wider the application of advanced composites. In this paper, the bearing capacity of composite hat-stiffened panels is determined by an improved engineering calculation method and numerical analysis method. The effectiveness of both methods is verified by the test. The advantage of the engineering estimation method is simple and fast, which is suitable for the parametric analysis of the structure in the preliminary design phase. The finite element method can better simulate the test process and is suitable for the comprehensive evaluation of structural strength. The combination of the two methods has a high reference value for rapid design and selection.

In the present study, flow over aerodynamics models is analysed in water channel flow to understand flow physics at affordable cost. The water channel flow visualization setup is constructed to analyse the analogy between Froude number and Mach number and flow visualization over various models is observed. In order to conduct the study, the shallow water speed is varied from 0.4 m/s to 0.6 m/s in the test section of water channel which will corresponds to the Froude number, Fr= 2. The water channel results will be finally validated to wind tunnel at Mach number, M=2. The velocity of water channel can be found by tracing the motion of suspended particles over shallow water at defined length and also by the volumetric flow rate. Several tests were conducted over a spike model to understand the flow visualization and videos were captured. The hydraulic jump and divergent angle in the water surface will be observed and validated with the corresponding shock angle in air medium. Failure analysis throughout the constructs are discussed to understand and resolve different problems faced with the specimen, test section along with camera setup. The present setup can be used multiple times for long duration to observe the flow visualization for undergraduate students.

The oil level of the power transformer is an important predictor to analyze the working state. The conventional oil level detection method cannot detect the level when the power transformer is working, which is not convenient for the actual application. In this paper, an oil level detection method based on double pressure sensors is proposed to online measure the oil level for power transformer, the basic principle of the proposed oil level detection method is explained and studied, and a prototype is developed to verify the proposed method. The tested results show that the developed prototype can reach high precision for oil level detection of a transformer.

Dynamic simulation is critical for robotic design and control. In this study, a modular simulation platform is developed using a novel explicit dynamic modeling method. Combined with a PD controller and a globally linearized compensator, the dynamic modeling method presents an explicit and canonical form for tree-chain and closed-chain multi-body systems. Paired with the new approach, the platform makes it convenient for modeling, and it performs well in real-time with a high update frequency. The platform also offers a thorough parameter setting and simulation scene presentation interface through the construction of several modules. A simulation experiment using a 6-DOF manipulator demonstrates the platform’s capacity for real-time, stable, and practical simulations, which is also applicable for high-DOF multi-body systems of future uses.

To calculate the loss in each power supply supplying power to different loads in a multi-power supply system, this paper proposes a complex proportional relationship between the power supply loss in the power transmission process to a specific load and the power injected by the power supply. And based on the circuit theory, the theoretical derivation is carried out. According to the known power flow results, this method uses the power component theory to track the network power flow forward and backward to construct a single power supply to a single load power supply network. It then scientifically strips out the loss of a single power supply to a single load power supply from the total loss and its complex proportional relationship to the power generation. The derivation process satisfies the classical circuit theory and does not introduce too many assumptions. While ensuring accuracy, it makes up for the lack of physical meaning of the previous network loss calculation methods. It provides a physical basis for formulating more economical scheduling schemes and promoting fair trading in the transmission market. The method is applied to a 7-node distribution network system, and the results confirm the correctness and effectiveness of the model.

This paper put forward a method on the premise of not changing the hardware circuit of the HPLC communication unit of the online electrical meter. In the HPLC communication unit of the electrical meter, the electrical meter address is modulated to the electric-power line through a high-speed carrier signal by the method of on-off keying. In the intelligent molded case circuit breaker of the meter box, after the new-type instrument transformer is used to extract the signal, the optimization algorithm is adopted to extract the electrical meter address to achieve physical topology identification of the meter box, forming a physical topographic map of low-voltage distribution area at the meter box level, which has the characteristics of low cost and high identification rate. This method is particularly suitable for the situation where HPLC communication units have been used in large quantities. Based on the current meter box operating method, it can effectively achieve the physical topology identification for the low-voltage distribution area, improve the physical topology identification rate for the meter box and reduce the identification cost.

With the rapid development of the wind power industry, the total installed capacity of wind power has increased dramatically worldwide, and a large number of wind power installations need to be connected to the grid. In wind turbines, voltage flicker due to output power fluctuations caused by wind speed changes, and the application of a Voltage Source Converter (VSC) cause harmonic richness and other power quality problems to become more and more prominent. In this regard, the research is focused on the harmonic and reactive current distribution, impedance frequency characteristics, and voltage distortion rate of several offshore wind farm access systems, including the establishment of a harmonic current simulation model of the offshore wind farm delivery system, simulation analysis of network impedance frequency characteristics, simulation analysis of harmonic currents, and proposed a preferred filtering scheme. Taking into full consideration the characteristic harmonics of the wind farm, the system resonance generated by the submarine cable and the background harmonic level of the power grid, combined with the simulation results of the harmonic voltage, harmonic current, and network impedance frequency characteristics of each node, the technical solution of adding a direct-mounted high-voltage filtering device to the 220 kV bus at the metering station is proposed, which can destroy the system resonance conditions of the 3rd to 6th times of the submarine cable. Various wind farms and system operating conditions are able to form a stable harmonic absorption point to avoid the problem of harmonic amplification.

The energy-saving of hydraulic excavators is evaluated by two significant indicators: operating efficiency (digging weight per unit time) and fuel consumption (volume of fuel consumed per unit time). These two indicators are only the final test results and cannot quantitatively evaluate the whole operation process of the excavator. In this paper, a complete set of experimental protocols is designed to quantify the energy-saving of the excavator by collecting its attitude data, fuel consumption data, and digging weight data in real-time. By restoring the excavator’s three-dimensional posture through the multi-body dynamics model, the posture corresponding to the energy efficiency of the excavator can be grasped very intuitively, which provides a research direction for optimizing the energy efficiency of the excavator.

The process of identifying specific examples of an item inside an image or video is referred to as “object detection,” and it is one of the computer vision techniques. When individuals look at pictures or movies, they are able to recognize and find things that are of interest to them. The primary goal of the field of object recognition is to achieve this level of intelligence via the use of a computer. Image segmentation and blob analysis, which uses simple object properties such as size, shape, or color, and Feature-based object detection, which uses feature extraction, matching, and RANSAC to estimate the location of an object, are two of the many common techniques that are used in conjunction with deep learning and machine learning-based object detection. There are also many other common techniques that are used in conjunction with deep learning and machine learning-based object detection. The most challenging aspects of object detection are the processes of categorizing things and pinpointing their locations. When seen from a different perspective, the same object might seem to be completely different. Detection algorithms have a tough time distinguishing between various things at different scales and perspectives since the sizes and proportions of items almost always alter. The camera input would be used to determine an object’s shape, according to this project’s proposal. Circle, square, and triangle are the three distinct shapes that we are determining an item to be right now. The finished result is shown in MATLAB’s graphical user interface (GUI). The productive identification process is carried out with the assistance of MATLAB. Using the SFTA Algorithm, the application extracts features from the specific image of a video. The neural network algorithm is used to classify the image of video. Image segmentation and image detection are two examples of related computer vision methods that are inextricably intertwined with object recognition. These techniques allow us to better comprehend and analyze the situations shown in movies and still photographs. It has been determined whether or not the suggested system is suitable. Because of this, the testing has shown that the suggested system generates generally accurate indications of real performance at a rate of 99.4%.

Carbon pollution has gradually become a serious environmental problem in recent years. The low-carbon optimization dispatch of the Integrated Energy Systems (IES) can realize the complementary and energy-use substitution of multiple energy sources and solve the problem of high carbon emission. In this paper, we first construct a system model and a carbon emission model. Then, we introduce carbon capture equipment into the system and construct a system optimization model with equipment constraints for each unit. Finally, we solve the proposed model with a complex solver in Matlab to verify the accuracy of the proposed model and the effectiveness of the method. The results show that the strategy can effectively reduce the carbon emissions of the IES.

The existing research on the wind solar coupling hydrogen generation system lacks the evaluation of factors such as the reliability of power supply to the microgrid system. This paper establishes a multi-objective optimization configuration model of wind-solar coupling hydrogen generation system under grid-connected operation mode for hydrogen generation. From the perspective of system economy and stability analysis, the model optimizes the capacity of the wind power unit, photovoltaic unit, energy storage unit, and hydrogen generation unit to improve the economy and reliability of microgrid operation, to minimize load loss rate, system annual cost, renewable energy power generation loss rate, and energy surplus rate.

This paper uses ANSYS-CFX to simulate a 100kW supercritical CO2 radial inflow turbine. The internal vortex structure of the nozzle is identified based on Q-criterion and helicity. The internal flow loss of the nozzle is quantified based on Kock-Herwig’s theory of entropy production. Finally, the mechanism of internal loss formation in the nozzle is analyzed by combining the distribution law of entropy production. The analysis of the internal flow loss of the nozzle shows that the flow loss inside the supercritical CO2 radial inflow turbine nozzle is mainly caused by turbulent dissipation, and the turbulent pulsation induced by viscous shear stress plays a dominant role in this process.

Here we present experimental results on the modification of graphite suspensions in bi-distilled water by laser irradiation in a flow mode system. The fundamental wavelength of a Nd:YAG laser system (λ= 1064 nm) was used in our experiments. The morphology of the sedimented and dried powders was studied by transmission electron microscopy (TEM). Their phase composition and structure were explored by Raman spectroscopy, GIXRD, as well as TEM.

Tissue engineering is emerging as a preferred choice for regeneration of irreversible bone tissue defects. It’s main “weapons” are the artificially created biocompatible three-dimensional cellular matrices that mimic the extracellular matrix’s structure and provide a mechanically stable inert substrate for the natural growth of cells. These porous scaffolds provide sufficient inner surface for cell adhesion, migration, proliferation and protrusion “inside” the temporal implant, facilitating in that way the natural bone ingrowth and vascularization. This leads, eventually, to overgrowing the outer and inner surface of the biomimetic implant with recipient self-formed bone tissue, thus avoiding a possible immune response. In the current study 3D Polystyrene (PS) non-resorbable synthetic cellular bone scaffolds, produced by 3D microfabrication technology, were additionally structured by applying femtosecond (fs) laser radiation with variable parameters thus achieving optimal laser processing conditions, for creation of 3D matrix with enhanced fiber surface properties. The main aim is the establishment of surface structured microporous biomimetic scaffolds, providing improved cell adhesion, infiltration and formation of extracellular matrix. The 3D laser functionalized PS samples were investigated by Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray analysis (EDX), confocal (optical profilometer) and roughness analyses for evaluation of their morphological and chemical properties before and after fs structuring was performed. Water contact angle (WCA) evaluation was also conducted. Future experimental work will include in vitro cellular studies for determining the optimal structuring laser parameters, providing osteoconductive and osteoinductive qualities of the 3D fs-microstructured PS scaffolds.

It is of great significance to study the mixing combustion characteristics of solid rocket ramjet for better organizing the secondary combustion of the air flowing into the inlet and the combustion-rich gas, enhancing the mixing degree of the supplementary combustion chamber, and improving the combustion efficiency. In this paper, the L-W model is used as the boron particles ignition combustion model. Combined with the UDF function of fluent, the boron particle ignition combustion program is self-programmed, the finite rate/eddy dissipation model is used as the gas combustion model, and the Realizable k-e turbulence model is used as the turbulence model. The numerical simulation was carried out under the cold flow state and the hot flow state, and the flow field distribution and parameters were obtained, and the mixing characteristics were analyzed. The error of simulation results and test results shows that that the numerical simulation results are in good agreement with the experimental results. By comparing the combustion efficiency and mixing degree, it is found that generally, When the mixing effect is not good, the combustion efficiency must be bad; When the mixing effect is good and the mixing degree is high, the combustion efficiency may be high.

At present, the setting of monitoring nodes for optimal allocation of energy storage capacity in micro-grid is generally target-based, with slow allocation speed and weak pertinence, which can easily lead to the increase of the final difference adjustment coefficient and affect the final allocation effect. Therefore, the research and analysis on the optimal allocation method of distributed micro-grid energy storage capacity based on the improved whale algorithm are proposed. According to the actual disposal requirements and standards, the basic operation frequency and reserve capacity of the micro-grid are determined, the multi-level monitoring node deployment form is set, the monitoring range is expanded, and the speed and pertinence of configuration are improved to complete the layout of energy storage capacity monitoring nodes. The optimal allocation model of the improved whale calculation of grid energy storage capacity is constructed. The optimal allocation is realized by constraint programming. The test results verify that the energy storage power of the micro-grid will be enhanced with the increase of the frequency modulation times of energy storage calculated by the whale calculation optimization configuration test group. In this context, the difference adjustment coefficient of the micro-grid configuration becomes lower, only 1.03, indicating that in the process of practical application, the energy storage capacity configuration of micro-grid is optimized. The frequency modulation fluctuation is slowed down, the running frequency is faster, and the method has practical application value.

In response to the outstanding problems of poor motion flexibility and poor terrain adaptability of conventional mobile robots in unstructured environments, a multi-vehicle modular articulated mobile robot capable of adapting to complex and variable obstacle terrain was developed by designing and introducing a flexible articulation device. By constructing a kinematic model of the single body module of the robot, integrating the motion constraint relations among the modules, and establishing the overall robot attitude equations, we propose a robot soft motion control method. Based on the analysis of robot motion characteristics under special obstacle terrain, the relationship model between obstacle parameters and robot pose is constructed, and the correction strategy under unilateral unstable motion state is proposed through the analysis of robot motion state under unilateral unstable condition. Theoretical analysis and experimental results show that the robot has good motion flexibility and complex terrain adaptability.