A coplanar-volume coupled discharge utilizing a capillary coplanar dielectric barrier discharge (CDBD) as a pre-ionization source and employing a negative direct current (DC) voltage to prompt plasma propagation from the dielectric surface to the air gap is proposed and experimentally investigated. Optical-electrical properties, spatial-temporal evolution of plasma, and active species generation are systematically studied to provide in-depth insights into the plasma characteristics of coplanar-volume coupled discharge based on pre-ionization. Compared to traditional dielectric barrier discharge, this approach reduces the inception voltage and significantly enhances the discharge intensity. Spatial-temporal evolution of plasma morphology demonstrates two distinct discharge processes occurring in coplanar-volume coupled discharge: coupled primary discharge and coupled secondary discharge. These processes are developed from the coplanar primary discharge and coplanar secondary discharge in capillary CDBD, respectively. Through analyzing the effects of pulse voltage and negative DC voltage on the physical and chemical properties of plasma, coplanar-volume coupled discharge based on high pre-ionization exhibits strong plasma luminous intensity, elevated discharge energy, and heightened chemical activity.

Coal resources account for 94% of the fossil energy structure in China, while accidents under mines occur frequently throughout the country, seriously threatening the lives of miners. Realizing precise positioning of underground personnel is an important guarantee for safe production of miners and rapid search and rescue work in the event of accidents. This article adopts the bilateral bidirectional ranging (DS-TWR) method to measure the distance between the positioning base station and the positioning label. This method does not require clock synchronization between the positioning base station and the positioning label system, and improves the positioning accuracy by improving the ranging accuracy. Based on the obtained distance measurement information, a position calculation algorithm combining the full centroid algorithm and Taylor algorithm with Kalman filtering is used to estimate the coordinates of the positioning label. The performance of the algorithm is analyzed through static and dynamic experiments, and the positioning accuracy is evaluated through root mean square error.

In response to the problems of cumulative errors and inaccurate correction results in the attitude calculation method of hydraulic supports based on inertial measurement units, a fully mechanized working face hydraulic support attitude monitoring method based on particle swarm optimization (PSO) - extreme learning machine (ELM) is proposed. Using the pitch angle of the hydraulic support top beam as the monitoring object, a tilt sensor and gyroscope are used to collect real-time information on the support attitude of the hydraulic support top beam. The collected data is preprocessed and input into the PSO-ELM error compensation model to obtain the predicted solution error. At the same time, the hydraulic support attitude is calculated through Kalman filtering fusion to obtain the calculated value. Then the method uses the error prediction value to compensate for the error in the calculated value, in order to obtain more accurate data on the top beam support attitude. This method only considers the relationship between acceleration and angular velocity data and solution errors, without relying on specific physical models. It can effectively reduce the cumulative error of attitude solution. The experimental results show that the average absolute error of the pitch angle of the top beam of the hydraulic support has been reduced from 1.420 8° before compensation to 0.058 0°. The error curve has good convergence, verifying that the proposed method can sustainably and stably monitor the support attitude of the hydraulic support.

This paper presents a fault diagnosis method for a vacuum contactor using the generalized Stockwell transform (GST) of vibration signals. The objective is to solve the problem of low diagnostic performance efficiency caused by the inadequate feature extraction capability and the redundant pixels in the graph background. The proposed method is based on the time-frequency graph optimization technique and ShuffleNetV2 network. Firstly, vibration signals in different states are collected and converted into GST time-frequency graphs. Secondly, multi-resolution GST time-frequency graphs are generated to cover signal characteristics in all frequency bands by adjusting the GST Gaussian window width factor λ. The OTSU algorithm is then combined to crop the energy concentration area, and the size of these time-frequency graphs is optimized by 68.86%. Finally, considering the advantages of the channel split and channel shuffle methods, the ShuffleNetV2 network is adopted to improve the feature learning ability and identify fault categories. In this paper, the CKJ5-400/1140 vacuum contactor is taken as the test object. The fault recognition accuracy reaches 99.74%, and the single iteration time of model training is reduced by 19.42%.

The deicing process and its status characteristics of dual-side pulsed surface dielectric barrier discharge (SDBD) are studied via electro-optical diagnostics, thermal properties, and numerical simulation. Experimental results show that the dual-side pulsed SDBD can remove the glaze ice compared to the traditional pulsed SDBD under the applied pulse voltage of 8 kV and a pulse frequency of 1 kHz. The maximal temperature of dual-side pulsed SDBD reaches 39.5 °C under the discharge time of 800 s, while the maximal temperature of traditional pulsed SDBD is still below ice point about −7.8 °C. Surface temperatures of dual-side pulsed SDBD demonstrate that the SDBD with a gap of 1 mm possesses prospects in deicing. The maximal surface temperature reaches 37.1 °C under the pulse of 8 kV after the discharge time of 90 s. Focusing on the thermal effect, a two-dimensional plasma fluid model is implemented, and the results also indicate that the dual-side pulsed SDBD with a gap of 1 mm produces a highest heat density among the three different configurations. Comparing the spatial-temporal evolutions of plasma on both dielectric sides, primary positive streamer has a longer propagation length of 8.6 mm than the secondary negative streamer, the primary negative streamer, and the secondary positive streamer, which induces a long heat covered area. Four stages of deicing process are analyzed through a series of electrical parameters under different covered ice conditions.

Polypropylene (PP) is considered as a candidate for high-voltage direct current (HVDC) cable insulation owing to its excellent thermal stability, insulation properties, and environmental friendliness. It is a semi-crystalline polymer, and the difference in cooling rate during processing affects its crystallisation morphology and characteristics, which may change its insulation properties. In this study, PP film samples with varying cooling rates of 10, 20, 40, 70, 120, and 170 degrees C min-1 were prepared. The crystal morphology was observed, crystal characteristics were analysed, and the space charge distribution and direct current (DC) breakdown strength were measured. It can be concluded that with an increase in the cooling rate, the spherulite size of PP decreased, the spherulite number increased, and the characteristic breakdown strength increased. Notably, the variation trends of the space charge distortion factor and carrier mobility of PP are opposite to that of crystallinity. When the cooling rate was 40 degrees C min-1, the number of space charges in PP was small, the distortion of the electric field was not obvious, the apparent mobility of carriers was high, the charge decay was rapid in the depolarisation process, and the average breakdown strength was acceptable. Therefore, during the processing of the HVDC cable, the space charge characteristics of PP can be optimized by adjusting the cooling rate.

With the widespread use of nonlinear and asymmetric loads in power systems, the assessment of power quality has increasingly drawn the attention of scholars. The essence of power quality evaluation lies in a multi-attribute decision optimization problem. To address the critical issue of determining the weights of power quality indicators, a method combining Rough Analytic Hierarchy Process (RAHP) and improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed. This method first calculates the weights of indicators using RAHP, and then applies the improved TOPSIS method to comprehensively evaluate the power quality at five measurement points of a substation bus. The results of the case study demonstrate that the proposed method adequately considers both subjective and objective factors, resulting in a more comprehensive and accurate assessment.

盆式绝缘子作为GIS设备的主要绝缘部件,其裂纹缺陷将直接影响到设备的安全运行.为了实现超声导波对盆式绝缘子的裂纹检测,文章首先研究了兰姆波在盆式绝缘子内部的传播机理并绘制了相应的频散曲线,提出了利用传感器离散电压信号计算超声导波能量的简化公式,进一步通过有限元仿真模型探究了裂纹对超声导波能量传播规律的影响,最后,通过实验对检测方法可行性进行了验证.研究结果表明,在超声发射端不变的情况下,传感器接收信号的能量衰减率将随裂纹尺寸的增大而增大,且距离缺陷位置越近,其能量衰减率变化越大.该检测方法可实现盆式绝缘子的裂纹检测,且提高了超声导波检测微小裂纹时的灵敏度,具有一定的工程实践价值.

Algebraic and geometric methods are commonly used to realize drilling arm positioning control of bolt drilling rig. However, there are some problems such as low efficiency, no solution, multiple solutions, or poor universality. Using particle swarm optimization（POS） algorithm for positioning control of the drilling arm has the advantages of simple programming, strong search performance and good fault tolerance. But it is easy to fall into the local optimal solution. At present, the drilling arm positioning control based on improved PSO algorithm has low overall optimization efficiency and long optimization time. In order to solve the above problems, a chaotic crossover elite mutation opposition-based PSO（CEMOPSO） algorithm is designed by introducing chaos initialization, crossover operation, mutation operation and extreme value perturbation based on elite oppositionbased PSO（EOPOS） algorithm. The method uses standard test functions to test PSO algorithm, EOPSO algorithm, CEOPSO algorithm and CEMOPSO algorithm. The results show that CEMOPSO has the best stability,precision and convergence speed. The motion model of the drilling arm of the bolt drilling rig is established. The CEMOPSO algorithm is used to control the drilling arm positioning. The simulation of the control performance is carried out in Matlab. The results show that under the same iteration times and error precision constraints, the position error and posture error of the drilling arm have a very fast convergence rate from the initial iteration when using the CEMOPSO algorithm. The position error and posture error are smaller than those of the other three algorithms. The error curve is smooth, and the maximum position error is 0.005 m and the maximum posture error is 0.005 rad. When the position error is 1 mm and the posture error is 0.01 rad, the average iteration number of the CEMOPSO algorithm is 343. When the position error is 0.1 mm and the posture error is 0.001 rad, the average iteration number is 473. Under the same positioning precision, the convergence speed and stability of the CEMOPSO algorithm are better than those of the other three algorithms. The results meet the requirements of engineering application. The higher the accuracy of the solution, the better it is.

With the continuous advancement of smart grid construction, efficient and accurate short-term load forecasting for distribution networks is an essential requirement for the economic and reliable operation of power systems. To address the issues of insufficient consideration of factors and inadequate feature exploration in current load forecasting methods, a deep learning-based approach for short-term load forecasting in regional intelligent distribution networks is proposed. Firstly, the maximum information coefficient (MIC) is used to select features that affect load data. Then, Bidirectional Gated Recurrent Unit (BiGRU) model is utilized to explore the internal patterns and variations within the data, with the addition of an attention mechanism to highlight important information. Additionally, the dung beetle optimization algorithm (DBO) is employed to optimize the hyperparameters of the hybrid network model. Finally, a case study is conducted using real data from a distribution network in Shanxi province. The results show that compared to other methods such as LSTM, GRU, GRU-Attention, and SSA-BiGRU-Attention, the proposed method achieves higher forecasting accuracy.

千米钻机电控系统工况复杂、负载多变,并且融合多个一次回路,从而使瞬态干扰频谱分布随机性高,易出现模态混叠现象.为提升智能感知精度,千米钻机电控系统二次回路往往采用高带宽增益运算放大器,已有适用于二次侧端口设备的模型不再适用于小信号检测电路的稳定性分析.千米钻机电控系统瞬态干扰频域分布范围广泛,要求电路在很宽的频域内有较强的抗干扰能力.传统抗干扰措施存在频带较窄、高频抑制作用不佳的缺陷;多级RC、LC滤波电路存在阻抗不匹配、体积大的问题.针对上述问题,以 15000型千米钻机电控系统的二次回路信号采集电路为研究对象,对二次回路中瞬态干扰进行分析.采用无参尺度空间表达的经验小波变换(EWT)算法,利用尺度空间变换划分得到频谱分割点,进而提取出具有紧支撑框架的模态分量,引入模态分量的峭度指标特征划分瞬态干扰信号与白噪声信号,确定瞬态干扰的频域分布.通过构建电控系统二次回路含寄生参数的小信号电路等效模型,探寻反馈回路引脚寄生电容与触发振铃或自激振荡的干扰信号频率阈值的规律,分析瞬态干扰频域特征对电路稳定性的影响.结果表明:在输入输出存在 30 pF引脚寄生电容时,传导进入瞬态干扰信号使稳定性下降,且引起失稳的触发频率随引脚寄生电容增加而降低.利用铁氧体磁珠类似并联谐振的高阻特性,设计了一种二阶滤波电路.实验室试验结果表明:当干扰经过含铁氧体磁珠的二阶滤波电路后,在信号采样电路敏感的 0.2 MHz以上频段,干扰幅值均抑制在-35 dBV以下,信号采样电路无异常输出.工业样机运行数据中敏感频段干扰幅值均抑制在-35 dBV以下,与实验室试验结果基本一致,满足抗干扰要求.

The communication system is the channel and bridge for information transmission in the hydraulic support electro-hydraulic control system of the fully mechanized mining face. Currently, CAN bus is commonly used as the communication bus. It is susceptible to interference from the complex electromagnetic environment underground, resulting in internal communication hardware failures of the support controller and causing the phenomenon of 'disconnection' of the controller. In addition, the CAN bus communication system adopts a multi master communication mode. The disconnection of a single controller will cause the entire electro-hydraulic control system to malfunction, posing a safety hazard. A CAN communication protection circuit has been designed to ensure stable operation of the communication system under high load conditions and strong anti-interference capability in complex environments. A fault detection and diagnosis method for CAN bus communication is proposed based on the CAN bus communication protocol combined with the token ring network concept. By designing the frame structure and fault detection method of data reasonably, the defect of difficult positioning of nodes when lost in CAN bus communication mode is compensated. The impact of increasing data length on transmission load is minimized to ensure good communication performance. Two end controllers are combined with six hydraulic support controllers to form a ring network. The upper computer issues commands from time to time to simulate the actual load situation of the bus during underground operation. The experimental verification of the bus communication fault detection and diagnosis method for the hydraulic support electro-hydraulic control system is carried out. The results show that this method has a low impact on the system load rate and will not affect the normal operation of the system. When a faulty node occurs, the faulty controller can be detected within 300 ms and an alarm can be sent to the entire working face, with a fault elimination rate of 100%.

目前针对本安电路本安特性的研究大多以IEC火花实验装置为实验平台,仅对单一电容电路或电感电路的放电特性进行分析,存在适用性差、实验条件要求高等问题,缺少对混合型本安电路本安特性的研究.针对该问题,在GB/T 3836.4-2010《爆炸性环境第 4部分:由本质安全型"i"保护的设备》的基础上,以截流型保护方式下的混合型电路为实验对象进行短路瞬态能量实验,通过分析短路瞬态能量释放过程,建立了短路瞬态能量数学模型,分析了等效数学模型中电容、电感、电源电压和保护时间对短路瞬态能量的影响.Matlab仿真结果表明:随着电容和电感的增大,短路瞬态能量会逐渐增大,最后趋于一个稳定值;增大电源电压会显著增加短路瞬态能量;缩短动作保护时间可有效降低瞬态能量,但只有当保护时间小于临界时间时其作用才明显.基于短路瞬态能量数学模型开发了本安电源,进行了短路实验.实验结果表明:短路电流和电压波形与理论分析基本吻合,短路瞬态能量为 33.22μJ,符合本安要求,可为本安电源的设计提供参考.

盆式绝缘子是GIS中重要的支撑部件,当固定它的法兰螺栓松动后,盆体会因受力不均而破裂,引起重大安全事故.文中提出一种盆式绝缘子螺栓松动检测方法,将压电传感器以一发一收的方式布置在待检测螺栓附近,通过超声信号仪激励一侧压电传感器发射超声波,并在另一侧对压电传感器接收到的信号分别进行互相关和自相关计算,获得表征螺栓松动的超声信号声时差和能量.通过实验研究了螺栓不同松动程度下信号能量和声时差的变化规律,结果表明,随着螺栓扭矩增加,超声透射信号的声时差逐渐减小、信号能量逐渐增大;当螺栓扭矩增大到一定程度后,超声透射信号的声时差不再变化而能量继续增大.可见,能量相比声时差对螺栓松动更敏感,所以可以通过计算超声信号能量来实现盆式绝缘子固定螺栓的松动检测.

Basin-type insulator is the key insulation device of gas insulated switchgear （GIS）. It is fastened and connected with the flanges of the gas chambers on both sides by bolts. When the bolt preload is unevenly distributed， the stress distribution of the basin insulator will be uneven， and in severe cases， the insulator will be cracked， which will affect the safety and reliability of power equipment operation. The article builds an ultrasonic detection system for the looseness of flange bolts of basin insulators to obtain ultrasonic signals of different bolts under different working conditions. The features of the ultrasonic signals are extracted based on the convolutional neural network （CNN）. The experimental results show that the CNN can automatically extract the bolt loosening feature of the basin insulator. When the number of iterations is 320 and the learning rate is 0.001， the recognition accuracy of ten bolt loosening conditions reaches 100%. The detection method can realize the detection of the looseness of the flange bolts of the basin-type insulator， judge the looseness of the bolts， and has certain practical engineering value.

The intelligent distribution network, as a crucial component of the smart grid, represents the future direction of power distribution. It serves as an effective means to achieve energy efficiency, enhance power supply reliability, and reduce line losses. However, due to its large scale, high complexity, and susceptibility to various factors, traditional management methods struggle to meet modern requirements. Therefore, the scientific and rational assessment of the operational status of the intelligent distribution network has become an unresolved issue. In this study, we focus on a regional distribution network in Shanxi province. We have constructed a comprehensive set of scientifically and rationally designed evaluation indicators for assessing the operational status of the intelligent distribution network. Furthermore, the CRITIC method has been employed for weight assignment, while the fuzzy comprehensive evaluation method has been utilized to establish a comprehensive assessment model for the intelligent distribution network. Through practical case validation, the effectiveness and feasibility of the proposed approach have been verified.

盆式绝缘子是GIS中的重要组成部分,盆式绝缘子主要通过法兰螺栓进行固定,但螺栓松动会导致盆式绝缘子受力不均甚至气体泄漏等问题,严重影响GIS运行可靠性.文中提出了一种GIS盆式绝缘子法兰螺栓松动的超声波监测方法,通过控制压电片进行超声信号的激励与接收,根据压电片接收信号的均方根偏差来反映螺栓松动状态,研究了不同工况下超声接收信号幅值及其均方根偏差的变化规律,并进行了有限元分析及实验验证.结果表明,随着松动螺栓数量的增加,压电片接收信号的幅值逐渐下降,信号均方根偏差逐渐增加;同时距离松动螺栓最近的压电片信号均方根偏差值最大.文中提出的方法可判断GIS盆式绝缘子法兰螺栓松动的数量及位置,实现法兰螺栓松动监测.

相比于传统的有线充电,无线充电是一种更加方便和可靠的充电方式,在电动汽车、生物医学等领域具有较为广泛的应用前景.然而传输效率的低下却限制了无线电能传输技术的进一步推广.磁耦合谐振式做为一种最主要的无线电能传输技术,其主要由高频电源,补偿结构,磁耦合结构以及整流滤波四部分构成.目前磁耦合谐振式无线电能传输系统的传输效率分析时大多仅考虑磁耦合结构的损耗,对系统中高频电源以及整流滤波的损耗考虑欠少.文章在预定效率以及恒功率条件下计算磁耦合谐振式无线电能传输系统中各部分损耗与互感之间的关系,寻求满足系统要求的互感值.最后设计了一套传输功率为1 000W,传输效率为85％的磁耦合谐振式无线电能传输系统,实验结果表明文中的损耗计算方法具有较高的准确性.研究结果为无线充电系统分析及性能改善起到积极推动作用.

基于热电厂实际供热工况,设计了满足全供热周期供热负荷需求的6种灵活性供热模式,并基于实时热负荷和锅炉负荷,提出了灵活性供热控制策略,最后对山西某亚临界2×300 MW热电联产机组进行了工程试验.结果表明:灵活性供热控制策略能够根据锅炉负荷和供热负荷需求的实时变化自动切换至最优供热模式;通过参数优化,在保障供热的前提下全厂发电量提升了5.5 MW,经济效益明显提升.

Dielectric capacitors with higher working voltage and power density are favorable candidates for renewable energy systems and pulsed power applications. A polymer with high breakdown strength, low dielectric loss, great scalability, and reliability is a preferred dielectric material for dielectric capacitors. However, their low dielectric constant limits the polymer to achieve satisfying energy density. Therefore, great efforts have been made to get high-energy-density polymer dielectrics. By compositional and structural tailoring, the synergic integrations of the multiple components and optimized structural design effectively improved the energy storage properties. This review presents an overview of recent advancements in the field of high-energy-density polymer dielectrics via compositional and structural tailoring. The surface/interfacial engineering conducted on both microscale and macroscale for polymer dielectrics is the focus of this review. Challenges and the promising opportunities for the development of polymer dielectrics for capacitive energy storage applications are presented at the end of this review.