Field test of high-power microwave-assisted mechanical excavation for deep hard iron ore

Microwave-assisted mechanical excavation has great application prospects in mines and tunnels,but there are few field experiments on microwave-assisted rock breaking.This paper takes the Sishanling iron mine as the research object and adopts the self-developed high-power microwave-induced fracturing test system for hard rock to conduct field experiments of microwave-induced fracturing of iron ore.The heating and reflection evolution characteristics of ore under different microwave parameters(antenna type,power,and working distance)were studied,and the optimal microwave parameters were obtained.Subsequently,the ore was irradiated with the optimal microwave parameters,and the cracking effect of the ore under the action of the high-power open microwave was analyzed.The results show that the reflection coefficient(standing wave ratio)can be rapidly(<5 s)and automatically adjusted below the preset threshold value(1.6)as microwave irradiation is performed.When using a right-angle horn antenna with a working distance of 5 cm,the effect of automatic reflection adjustment reaches the best among other antenna types and working distances.When the working distance is the same,the average temperature of the irradiation surface and the area of the high-temperature area under the action of the two antennas(right-angled and equal-angled horn antenna)are basically the same and decrease with the increase of working distance.The optimal microwave parameters are:a right-angle horn antenna with a working distance of 5 cm.Subsequently,in further experiments,the optimal parameters were used to irradiate for 20 s and 40 s at a microwave power of 60 kW,respectively.The surface damage extended 38 cm×30 cm and 53 cm×30 cm,respectively,and the damage extended to a depth of about 50 cm.The drilling speed was increased by 56.2%and 66.5%,respectively,compared to the case when microwaves were not used.

A Simple and Effective Surface Defect Detection Method of Power Line Insulators for Difficult Small Objects

Insulator defect detection plays a vital role in maintaining the secure operation of power systems.To address the issues of the difficulty of detecting small objects and missing objects due to the small scale,variable scale,and fuzzy edge morphology of insulator defects,we construct an insulator dataset with 1600 samples containing flashovers and breakages.Then a simple and effective surface defect detection method of power line insulators for difficult small objects is proposed.Firstly,a high-resolution featuremap is introduced and a small object prediction layer is added so that the model can detect tiny objects.Secondly,a simplified adaptive spatial feature fusion(SASFF)module is introduced to perform cross-scale spatial fusion to improve adaptability to variable multi-scale features.Finally,we propose an enhanced deformable attention mechanism(EDAM)module.By integrating a gating activation function,the model is further inspired to learn a small number of critical sampling points near reference points.And the module can improve the perception of object morphology.The experimental results indicate that concerning the dataset of flashover and breakage defects,this method improves the performance of YOLOv5,YOLOv7,and YOLOv8.In practical application,it can simply and effectively improve the precision of power line insulator defect detection and reduce missing detection for difficult small objects.

Review of Power Supply and Distribution Construction Technology for Highway Electromechanical Engineering

In recent years,China has made significant progress in the construction of highways,resulting in an improved highway network that has provided robust support for economic and social development.However,the rapid expansion of highway construction,power supply,and distribution has led to several challenges in mechanical and electrical engineering technology.Ensuring the safe,stable,and cost-effective operation of the power supply and distribution system to meet the diverse requirements of highway operations has become a pressing issue.This article takes an example of a highway electromechanical engineering power supply and distribution construction project to provide insight into the construction process of highway electromechanical engineering power supply and distribution technology.

Effect of Laser Power on the Microstructure and Mechanical Properties of TiN/Ti_3Al Composite Coatings on Ti6Al4V

Laser nitriding is one of the effective techniques to improve the surface properties of titanium alloys and has potential application in the life extension of last-stage steam turbine blades. However, cracking of surface coating is a common problem due to heat concentration in laser nitriding process. Conventionally, the cracks can be avoided through heat treatment, which may have an important influence on the mechanical properties of coating. Crack-free TiN/Ti3Al IMC coatings on Ti6Al4V are prepared by plasma spraying and laser nitriding. The microstructures, phase constitutes and compositions of the coating are observed and analyzed with scanning electron microscopy(SEM), X-ray diffraction(XRD) and X-ray energy-dispersive spectroscopy(EDS). Microhardness, elastic modulus, fracture toughness of the coating are measured. The results show that the crackand pore-free IMC coatings can be made through the proposed method; with increasing laser power, the amount and density of TiN phase in the coating first increased and then decreased, leading to the similar trend of microhardness and elastic modulus and the reverse trend of fracture toughness of the coating. Both the average microhardness and elastic modulus of the coating increase three times higher than those of the substrate. The volume fraction of the TiN reinforced phase in composite can be controlled by varying the laser power and the cracking problem in laser nitriding process is successfully solved.

铜基漆酶模拟酶Cu-MP的制备及活性研究

天然漆酶的催化活性和稳定性易受外界环境因素的不良影响,受天然漆酶活性中心和电子转移的启发,利用6-巯基嘌呤与铜离子的配位反应合成一种新型漆酶模拟酶(Cu-MP),并采用SEM-EDS、BET、FTIR、XRD、XPS对其性能进行表征并分析。结果表明:Cu-MP呈珊瑚状多孔网状结构,可为催化反应提供较大的比表面积;6-MP主要通过硫和碱基氮(N7)与铜离子配位合成Cu-MP。催化机理推测,模拟酶Cu-MP通过铜离子从底物获取电子后,按照S-C_(6)-C_(5)-N_(7)通道实现电子转移;与相同质量浓度下的天然漆酶相比,Cu-MP对底物的亲和力更佳,其最大反应速度v_(max)是天然漆酶的4.7倍;在25℃下储存7 d后,Cu-MP的酶活保留率达84.03%;经过9轮循环利用,酶活保留率在70%以上;甚至在高盐或有机溶液中,Cu-MP仍能保持相对稳定的催化活性。因此,Cu-MP可以取代天然漆酶,尤其在一些极端条件下,用于处理酚类等环境污染物,是一种具有发展和应用前景的环境催化剂。

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

Investigating Periodic Dependencies to Improve Short-Term Load Forecasting

With a further increase in energy flexibility for customers,short-term load forecasting is essential to provide benchmarks for economic dispatch and real-time alerts in power grids.The electrical load series exhibit periodic patterns and share high associations with metrological data.However,current studies have merely focused on point-wise models and failed to sufficiently investigate the periodic patterns of load series,which hinders the further improvement of short-term load forecasting accuracy.Therefore,this paper improved Autoformer to extract the periodic patterns of load series and learn a representative feature from deep decomposition and reconstruction.In addition,a novel multi-factor attention mechanism was proposed to handle multi-source metrological and numerical weather prediction data and thus correct the forecasted electrical load.The paper also compared the proposed model with various competitive models.As the experimental results reveal,the proposed model outperforms the benchmark models and maintains stability on various types of load consumers.

Power Quality Disturbance Identification Basing on Adaptive Kalman Filter andMulti-Scale Channel Attention Fusion Convolutional Network

In light of the prevailing issue that the existing convolutional neural network(CNN)power quality disturbance identification method can only extract single-scale features,which leads to a lack of feature information and weak anti-noise performance,a new approach for identifying power quality disturbances based on an adaptive Kalman filter(KF)and multi-scale channel attention(MS-CAM)fused convolutional neural network is suggested.Single and composite-disruption signals are generated through simulation.The adaptive maximum likelihood Kalman filter is employed for noise reduction in the initial disturbance signal,and subsequent integration of multi-scale features into the conventional CNN architecture is conducted.The multi-scale features of the signal are captured by convolution kernels of different sizes so that the model can obtain diverse feature expressions.The attention mechanism(ATT)is introduced to adaptively allocate the extracted features,and the features are fused and selected to obtain the new main features.The Softmax classifier is employed for the classification of power quality disturbances.Finally,by comparing the recognition accuracy of the convolutional neural network(CNN),the model using the attention mechanism,the bidirectional long-term and short-term memory network(MS-Bi-LSTM),and the multi-scale convolutional neural network(MSCNN)with the attention mechanism with the proposed method.The simulation results demonstrate that the proposed method is higher than CNN,MS-Bi-LSTM,and MSCNN,and the overall recognition rate exceeds 99%,and the proposed method has significant classification accuracy and robust classification performance.This achievement provides a new perspective for further exploration in the field of power quality disturbance classification.

Effect of Rectus Plication during Abdominoplasty on the Mechanical Power and Airway Pressures: Comparison of Two Ventilatory Strategies

Background: Abdominoplasty is a commonly requested procedure for aesthetic improvement of the affected soft tissue layers of skin, fat, and muscle through the slightest incision feasible. The degree of plicature generates an increase in intraabdominal pressure that causes an increase in intrathoracic pressure. Pressure, volume, flow, and respiratory rate are components of a unique physical variable, the mechanical power (MP), and is an integrated variable linked to most factors related to postoperative pulmonary complications. Purpose: To assess the effect of rectus plication (RP) during abdominoplasty on lung pressures and the contribution to increasing the MP. Method: A open-label study was conducted at TJ Plast Advanced Center for Plastic Surgery in Tijuana, México, from September 2021 to May 2022. The study included forty-six female patients subjected to abdominoplasty or liposuction with abdominoplasty. After the induction of general anesthesia and neuromuscular blockade, they were allocated into two groups: Group 1 pressure control ventilation-volume guaranteed (PCV-VG) and Group 2 volume control ventilation (VCV). Respiratory pressures and MP were assessed before and after RP. Results: During VCV, patients had a greater increase in peak pressure (PIP) (P 0.000). Plateau pressure (Pplat) increased 1.78 ± 0.35 cmH2O in group 2 after RP (P = 0.001). MP had a greater increase in group 2 after RP (P 0.01). Conclusion: This prospective study showed that RP is related to an increase in PIP and Pplat and an increase in the MP better controlled with PCV-VG ventilation.

The Short-Term Prediction ofWind Power Based on the Convolutional Graph Attention Deep Neural Network

The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large scale.Therefore,wind power forecasting plays a key role in improving the safety and economic benefits of the power grid.This paper proposes a wind power predicting method based on a convolutional graph attention deep neural network with multi-wind farm data.Based on the graph attention network and attention mechanism,the method extracts spatial-temporal characteristics from the data of multiple wind farms.Then,combined with a deep neural network,a convolutional graph attention deep neural network model is constructed.Finally,the model is trained with the quantile regression loss function to achieve the wind power deterministic and probabilistic prediction based on multi-wind farm spatial-temporal data.A wind power dataset in the U.S.is taken as an example to demonstrate the efficacy of the proposed model.Compared with the selected baseline methods,the proposed model achieves the best prediction performance.The point prediction errors(i.e.,root mean square error(RMSE)and normalized mean absolute percentage error(NMAPE))are 0.304 MW and 1.177%,respectively.And the comprehensive performance of probabilistic prediction(i.e.,con-tinuously ranked probability score(CRPS))is 0.580.Thus,the significance of multi-wind farm data and spatial-temporal feature extraction module is self-evident.

激光功率和离焦量对2000 MPa级热成形钢激光焊接接头组织与性能影响

目的研究激光功率和离焦量对PHS2000型热成形钢激光焊接接头焊缝区及热影响区显微组织、拉伸特性和硬度分布的影响。方法采用光学显微镜(OM)、扫描电子显微镜(SEM)分析焊接接头的显微结构;利用拉伸实验和显微硬度实验探究焊接接头力学性能的变化规律。结果随着激光功率从3500 W增至4700 W,焊缝区与热影响区平均晶粒尺寸总体呈上升趋势,抗拉强度先上升后下降,焊缝区平均显微硬度值在635HV~651HV内浮动,热影响区平均显微硬度值在434HV~451HV内浮动;离焦量对焊缝区的组织分布有显著影响,不同离焦量下的组织分布均较为分散,热影响区的晶粒尺寸在离焦量为−3 mm时达到最大,为10.67μm。在不同激光功率和离焦量下,焊接接头的显微硬度值存在上下浮动,焊接接头各区的显微硬度分布规律基本一致,以焊缝为中心,两侧趋于对称分布。硬度分布规律如下:焊缝区硬度>母材区硬度>热影响区硬度。结论在本实验条件下,与离焦量相比,激光功率对焊接接头显微组织及拉伸强度的影响更大。在焊接速度为150 mm/min条件下,设置激光功率为4100 W、离焦量为−2 mm,此时抗拉强度最大,为1715 MPa,达到母材抗拉强度的85%。

Morphology and Mechanical Properties of PS/Al_2O_3 Nanocomposites Based on Selective Laser Sintering

Selective laser sintering （SLS） is a new process to prepare the polystyrene （PS）/Al2O3 nanocomposites. In this paper, with different laser power and other processing parameters unchanged, the morphology, density and mechanical properties of the sintered specimens were investigated. It was found that nano-sized inorganic particles are uniformly located in the PS matrix and the maximum density of the sintered specimens with pure PS powder reaches 1.07 g/cm^3, higher than 1.04 g/cm^3 that of the sintered specimens with mixture powder. Due to strengthening and toughness of the nano-sized Al2O3 inorganic particles, the maximum notched impact strength and tensile strength of the sintered part mixed with nano-sized inorganic particles are improved greatly from 7.5 to 12.1 kJ/m^2 and from 6.5 to 31.2 MPa, respectively, under the same sintering condition.

Improved edge lightweight YOLOv4 and its application in on-site power system work

A“cloud-edge-end”collaborative system architecture is adopted for real-time security management of power system on-site work,and mobile edge computing equipment utilizes lightweight intelligent recognition algorithms for on-site risk assessment and alert.Owing to its lightweight and fast speed,YOLOv4-Tiny is often deployed on edge computing equipment for real-time video stream detection;however,its accuracy is relatively low.This study proposes an improved YOLOv4-Tiny algorithm based on attention mechanism and optimized training methods,achieving higher accuracy without compromising the speed.Specifically,a convolution block attention module branch is added to the backbone network to enhance the feature extraction capability and an efficient channel attention mechanism is added in the neck network to improve feature utilization.Moreover,three optimized training methods:transfer learning,mosaic data augmentation,and label smoothing are used to improve the training effect of this improved algorithm.Finally,an edge computing equipment experimental platform equipped with an NVIDIA Jetson Xavier NX chip is established and the newly developed algorithm is tested on it.According to the results,the speed of the improved YOLOv4-Tiny algorithm in detecting on-site dress code compliance datasets is 17.25 FPS,and the mean average precision(mAP)is increased from 70.89%to 85.03%.

An Anisotropic Geomechanical Model for Jointed Rock Masses at Taishan Nuclear Power Station, Southern China

An anisotropic geomechanical model for jointed rock mass is presented. Simultaneously with deriving the orthotropic anisotropy elastic parameters along the positive axis, the equivalent compliance matrix for the deflection axis orthotropic anisotropy was derived through a three- dimensional coordinate transformation. In addition, Singh＇s analysis of the stress concentration effects of intermittent joints was adopted, based on two groups of intermittent joints and a set of cross- cutting joints in the jointed rock mass. The stress concentration effects caused by intermittent joints and the coupling effect of cross-cutting joints along the deflection-axis are also considered. The proposed anisotropic mechanics parameters method is applied to determine the deformation parameters of jointed granite at the Taishan Nuclear Power Station. Combined with the deterministic mechanical parameters of rock blocks and joints, the deformation parameters and their variability in jointed rock masses are estimated quantitatively. The computed results show that jointed granite at the Taishan Nuclear Power Station exhibits typical anisotropic mechanical characteristics; the elastic moduli in the two horizontal directions were similar, but the elastic modulus in the vertical direction was much greater. Jointed rock elastic moduli in the two horizontal and vertical directions were respectively about 24% and 37% of the core of rock, showing weakly orthotropic anisotropy; the ratio of elastic moduli in the vertical and horizontal directions was 1.53, clearly indicating the transversely isotropic rock mass mechanical characteristics. The method can be popularized to solve other rock mechanics problems in nuclear power engineering.

Research and applications of FDMP algorithm for power quality signal analysis

The accuracy of unsteady-state disturbance analysis of power quality signals is reduced by the steadystate components with high amplitudes and energies. In this paper,a novel frequency-domain matching pursuits (FDMP) algorithm is proposed to estimate the parameters of the steady-state components and separate the unsteady-state disturbances from power quality signals. Firstly,the time-frequency atoms and redundant dictionaries are constructed according to the characteristics of power quality signal spectra. Secondly,the steady-state components and unsteady-state disturbances of power quality signals are decomposed by FDMP into two mutually orthogonal subspaces in Hilbert space. Furthermore,the expressions for parameters calculation of steady-state components have been derived. The experiments show that the relative errors of frequency and amplitude estimations of steady-state components are less than 2 × 10 -4 and 5 × 10 -3 respectively,and phase estimation errors are less than 1. 6° under the existence of both interharmonics and unsteady-state disturbances. The steady-state components and unsteady-state disturbances are separated quickly and accurately.

Effects of laser power density on static and dynamic mechanical properties of dissimilar stainless steel welded joints

The mechanical properties of laser welded joints under impact loadings such as explosion and car crash etc. are critical for the engineering designs. The hardness, static and dynamic mechanical properties of AISI304 and AISI316L dissimilar stainless steel welded joints by CO2 laser were experimentally studied. The dynamic strainstress curves at the strain rate around 103 s-1 were obtained by the split Hopkinson tensile bar （SHTB）. The static mechanical properties of the welded joints have little changes with the laser power density and all fracture occurs at 316 L side. However, the strain rate sensitivity has a strong depen- dence on laser power density. The value of strain rate factor decreases with the increase of laser power density. The welded joint which may be applied for the impact loading can be obtained by reducing the laser power density in the case of welding quality assurance.

Characteristics on Hydro-mechanical Transmission in Power Shift Process

To improve the vehicular power and acceleration performance and reduce the shift impact, the study of the characteristics on power shift is necessary. Based on the flexible hydraulic unit of hydro-mechanical transmission, this paper explores the feasibility of shift without power interruption. With the four models concerning displacement ratio, rotational speed, rotational torque and power at ideal shift point, the characteristics on power shift in different running conditions are analyzed, and the rules of power shift are revealed. The theoretical analysis and test results show that the hydro-mechanical transmission can shift without power interruption in different running conditions. Furthermore, there exists an ideal shift point in theory, at which point the cycle power in hydro-mechanical transmission can＇t be generated, and the impact on the system can be reduced to the minimum. However, if before or after this ideal shift point, a cycle power can be generated.

Study of Mechanical Model During Power Spinning Simulation of Cylindrical Workpiece

Whether the proposed mechanical model fits in the nature of technology is the key to solving the problems during three dimensional simulation of power spinning. The study of mechanical model includes: the definition of the contour of contact zone and processing the velocity and frictional force boundary conditions on contact zone. The movement locus of roller surface is a spiral cone and contact zone between roller and workpiece is a part of cone surface of roller. So the contour of the contact zone is intersected by roller cone surface, spiral cone surface and cylindrical surfaces. In this paper, a solution to defining the contour and applying space restriction of the contact zone was proposed. Considering the sudden change in the direction of foctional force on the contact zone during power spinning, an inverse tangential frictional model was adopted to solve the problem. So a new mechanical model comes into being and the 3 - D FEM simulation results prove it to be right.

Structural Characteristics and Mechanical Properties of Rock Mass in the Field of Tianwan Nuclear Power Plant, China

The structural characteristics and mechanical properties of the rock mass are important parts of the feasibility study on the nuclear power engineering field. In this study, by means of in situ investigation and statistics, the structural plane and joint fissure features of the rock mass were analyzed and discussed at different plots and different depth scopes in the Tianwan Nuclear Power engineering field, the rock mass integrality and its weathered degree were evaluated respectively, and especially, the unfavorable geological phenomena of strongly-weathered cystid existing in the field were studied. According to the results of indoor rock mechanical tests, in combination with drilling, the shallow seismic prospecting, sonic logging and point load tests, the statistical results of physical and mechanical indices of rocks at key plots of the field were analyzed, and the design parameters of the field were calculated. It provided scientific basis for the foundation design of the nuclear power plant.