Intelligent Islanding Detection of Multi-distributed Generation Using Artificial Neural Network Based on Intrinsic Mode Function Feature

The integration of distributed energy resources(DERs) into distribution networks is becoming increasingly important, as it supports the continued adoption of renewable power generation, combined heat and power plants, and storage systems. Nevertheless, inadvertent islanding operation is one of the major protection issues in distribution networks connected to DERs. This study proposes an intelligent islanding detection method(IIDM) using an intrinsic mode function(IMF)feature-based grey wolf optimized artificial neural network(GWO-ANN). In the proposed IIDM, the modal voltage signal is pre-processed by variational mode decomposition followed by Hilbert transform on each IMF to derive highly involved features. Then, the energy and standard deviation of IMFs are employed to train/test the GWO-ANN model for identifying the islanding operations from other non-islanding events. To evaluate the performance of the proposed IIDM, various islanding and non-islanding conditions such as faults, voltage sag, linear and nonlinear load and switching, are considered as the training and testing datasets. Moreover, the proposed IIDM is evaluated under noise conditions for the measured voltage signal. The simulation results demonstrate that the proposed IIDM is capable of differentiating between islanding and non-islanding events without any sensitivity under noise conditions in the test signal.

Adaptive Variational Mode Decomposition for Bearing Fault Detection

Rolling element bearings are commonly used in rotary mechanical and electrical equipment. According to investigation, more than half of rotating machinery defects are related to bearing faults. However, reliable bearing fault detection still remains a challenging task, especially in industrial applications. The objective of this work is to propose an adaptive variational mode decomposition (AVMD) technique for non-stationary signal analysis and bearing fault detection. The AVMD includes several steps in processing: 1) Signal characteristics are analyzed to determine the signal center frequency and the related parameters. 2) The ensemble-kurtosis index is suggested to decompose the target signal and select the most representative intrinsic mode functions (IMFs). 3) The envelope spectrum analysis is performed using the selected IMFs to identify the characteristic features for bearing fault detection. The effectiveness of the proposed AVMD technique is examined by experimental tests under different bearing conditions, with the comparison of other related bearing fault techniques.

Comprehensive Reliability Allocation Method for CNC Lathes Based on Cubic Transformed Functions of Failure Mode and Effects Analysis

Reliability allocation of computerized numerical controlled（CNC）lathes is very important in industry.Traditional allocation methods only focus on high-failure rate components rather than moderate failure rate components,which is not applicable in some conditions.Aiming at solving the problem of CNC lathes reliability allocating,a comprehensive reliability allocation method based on cubic transformed functions of failure modes and effects analysis（FMEA）is presented.Firstly,conventional reliability allocation methods are introduced.Then the limitations of direct combination of comprehensive allocation method with the exponential transformed FMEA method are investigated.Subsequently,a cubic transformed function is established in order to overcome these limitations.Properties of the new transformed functions are discussed by considering the failure severity and the failure occurrence.Designers can choose appropriate transform amplitudes according to their requirements.Finally,a CNC lathe and a spindle system are used as an example to verify the new allocation method.Seven criteria are considered to compare the results of the new method with traditional methods.The allocation results indicate that the new method is more flexible than traditional methods.By employing the new cubic transformed function,the method covers a wider range of problems in CNC reliability allocation without losing the advantages of traditional methods.

Analysis of functional failure mode of commercial deep sub-micron SRAM induced by total dose irradiation

Functional failure mode of commercial deep sub-micron static random access memory（SRAM） induced by total dose irradiation is experimentally analyzed and verified by circuit simulation. We extensively characterize the functional failure mode of the device by testing its electrical parameters and function with test patterns covering different functional failure modes. Experimental results reveal that the functional failure mode of the device is a temporary function interruption caused by peripheral circuits being sensitive to the standby current rising. By including radiation-induced threshold shift and off-state leakage current in memory cell transistors, we simulate the influence of radiation on the functionality of the memory cell. Simulation results reveal that the memory cell is tolerant to irradiation due to its high stability, which agrees with our experimental result.

Agricultural Development Mode Transformation and Government Functions in Guizhou Province

Based on the brief account of the connotation of transforming economic development pattern and government functions,the thesis will introduce the development status of agricultural economy in Guizhou Province:firstly,single agricultural industrial structure;secondly,large gap between urban and rural development;thirdly,low-level utilization of agricultural science and technology;fourthly,fierce contradiction between agricultural mode of production and ecological environment.Then it analyzes the basic requirements for government functions in transforming the development pattern of agricultural economy in Guizhou Province:the first one is the function to guide sustainable development and the structural adjustment of agricultural production;the second is the function to coordinate urban-rural development and equally supply basic public goods;the third is the function to input science and technology to serve agriculture;the fourth one is the dominant function to promote the harmonious development of man and nature as well as to reduce the number of peasants.In order to promote the transformation of agricultural development mode and maintain the sound and rapid economic development,some corresponding measures and suggestions are proposed from the perspective of government functions:firstly,promoting the optimization and upgrading of industrial structure;secondly,the government should take the lead in providing rural public goods;thirdly,strengthening the skills training and technological education of rural labor force;fourthly,reducing the number of farmers and retaining the farmers.

Scheme for direct measurement of Wigner function in two-mode cavity QED driven by classical fields

We propose a scheme for the direct measurement of Wigner function in two-mode cavity QED. The atoms are sent to resonantly interact with two orthogonally polarized cavity modes in the presence of strong classical field. The probability of measuring the atom in the ground state directly gives the useful information of the cavity field. This method can be used for quantum non-demolition measurement of the photon number.

Assignment of terahertz vibrational modes of L-glutamine using density functional theory within generalized-gradient approximation

The crystal structure of L-glutamine is stabilized by a three-dimensional network of intermolecular hydrogen bonds.We utilize plane-wave density functional theory lattice-dynamics calculations within the generalized-gradient approximation（GGA）, Perdew–Burke–Ernzerhof（PBE）, PBE for solids（PBEsol）, PBE with Wu–Cohen exchange（WC）, and dispersion-corrected PBE, to investigate the effect of these intermolecular contacts on the absorption spectra of glutamine in the terahertz frequency range. Among these calculations, the solid-state simulated results obtained using the WC method exhibit a good agreement with the measured absorption spectra, and the absorption features are assigned with the help of WC. This indicates that the vibrational modes of glutamine were related to the combination of intramolecular and intermolecular motions, the intramolecular modes were dominated by rocking or torsion involving functional groups; the intermolecular modes mainly result from the translational motions of individual molecules, and the rocking of the hydrogenbonded functional groups.

Simulation study of the two-time intensity correlation function of a two-mode laser system with both pump and quantum noises

This paper investigates the two-time intensity correlation function of a two-mode ring laser system subjected to both pump and quantum noises by stochastic simulation. It finds that the decay rate of the intensity correlation function of one mode gets faster with decreasing values of relevant parameters, i.e., the coupling constant ξ, the cross-correlation coefficient A, the difference of the pump parameters Aa and the pump parameter al; however, its variations get complex in the other mode when relevant parameters are changed. The investigating results also show that the effects of the mode competition on intensity correlation function are obvious.

Analysis of Vibration Mode for H_2+F→HF+H Reaction Mechanism: Density functional Theory Calculation

Three density functional theory methods (DFT) have been used to investigate the H2+F?HF+H reaction comparing with the Hartree-Fock method and Moller-Plesset (MP2) perturbation theory method. Through the analysis of the vibrational mode and vibrational frequency in the reaction process, the reaction mechanism has been discussed. The activation energy, the reorganization energy and rate constant of the ET reaction are calculated at semi-quantitative level.

Wave functions of a new kind of nonlinear single-mode squeezed state

We explore the theoretical possibility of extending the usual squeezed state to those produced by nonlinear singlemode squeezing operators. We derive the wave functions of exp[-（ig/2）（（1-X2）1/2P ＋ P（1-X2）1/2）]｜0 in the coordinate representation. A new operator＇s disentangling formula is derived as a by-product.

一种灰色关联分析优化ICEEMDAN的VP倾斜仪信号降噪模型

VP倾斜仪固体潮信号受仪器监测复杂环境限制,多含有大量环境噪声。为获得真实固体潮曲线,提出一种基于灰色关联分析优化改进的自适应噪声完备集合经验模态分解(ICEEMDAN)VP倾斜仪信号降噪模型(GRA-ICEEMDAN)。该方法首先将含噪信号进行ICCEMDAN处理,得到若干个固有模态函数(IMF),并依次排列与标记;然后基于这些IMF分别计算相关系数、互信息、R^(2)、Adj-R^(2)、MSE、SSE、RMSE、MAE、MAPE、样本熵等10个评价指标值,构建IMF可信度评价指标矩阵;最后借助灰色关联分析(GRA)计算各评价指标与不同IMF之间的关联系数和关联度,依据关联度大小对各个IMF进行排序,将排名靠前的IMF进行线性重构,即可完成信号降噪。仿真去噪实验和实测去噪实验均表明,GRA-ICEEMDAN模型优于卡尔曼滤波、70阶低通FIR滤波、Savitzky-Golay等经典降噪模型,能显著区分噪声成分和有效成分,原始信号分解后的重构误差与信号损失极小,可推广至其他仪器的复杂信号降噪中。

基于数字孪生和深度学习的结构损伤识别

土木工程实际结构损伤状态的时间跨度通常只占总生命周期的一小部分。为解决传统基于数据驱动的结构损伤识别方法缺乏足够多的损伤训练数据的问题,提出结合数字孪生和深度学习的结构损伤识别方法,并应用于实际工程。该方法利用数值仿真模型和在线监测数据构建结构的数字孪生,以获得不同损伤工况下结构动力响应的“大数据”;为了摆脱对外激励信息的依赖,应用经验模态分解法和传递率函数对得到的数据进行预处理;将预处理后的固有模态传递率函数数据作为深度学习的输入进行训练,实现结构的损伤识别。为验证方法的有效性,对实际结构未经训练的监测数据进行分析,结果表明,该方法泛化能力良好,能够有效识别结构损伤状况。通过数字孪生技术解决了传统方法数据匮乏的问题,不需要任何地震信息,利用固有模态传递率函数数据训练的深度神经网络仍能保持较高的损伤识别准确率,二者结合可以使工程结构健康监测更为主动、可靠、高效。

Sliding mode control of uncertain systems with distributed time-delay: parameter-dependent Lyapunov functional approach

The robust stability and robust sliding mode control problems are studied for a class of linear distributed time-delay systems with polytopic-type uncertainties by applying the parameter-dependent Lyapunov functional approach combining with a new method of introducing some relaxation matrices and tuning parameters, which can be chosen properly to lead to a less conservative result. First, a sufficient condition is proposed for robust stability of the autonomic system; next, the sufficient conditions of the robust stabilization controller and the existence condition of sliding mode are developed. The results are given in terms of linear matrix inequalities （LMIs）, which can be solved via efficient interior-point algorithms. A numerical example is presented to illustrate the feasibility and advantages of the proposed design scheme.

行为分阶段转变理论的个案管理模式在慢性阻塞性肺疾病稳定期患者中的应用

目的探讨行为分阶段转变理论的个案管理模式在慢性阻塞性肺疾病(以下简称“慢阻肺”)稳定期患者中的应用效果。方法纳入南京市第一医院2021年6月至2022年6月门诊访视的112例慢阻肺稳定期患者进行前瞻性研究,通过随机数字表法将其分为对照组和观察组,各56例。对照组给予个案管理模式干预,观察组给予行为分阶段转变理论的个案管理模式。两组均连续干预6个月。比较干预前、干预6个月后呼吸功能[圣乔治呼吸问卷(SGRQ)、改良版英国医院研究委员会呼吸困难量表(m MRC)]、自我管理能力[健康行为能力自评量表(SRAHP)]。结果干预后,两组SGRQ、m MRC评分均低于干预前,且观察组低于对照组,差异有统计学意义(P<0.05)。干预后,两组SRAHP评分高于干预前,且观察组高于对照组,差异有统计学意义(P<0.05)。结论行为分阶段转变理论的个案管理模式提高慢阻肺稳定期患者的自我管理能力,改善呼吸功能,具有较好应用效果。

全过程人民民主视域下人大代表联络站的功能定位与完善路径

人民代表大会制度是实现我国全过程人民民主的重要制度载体,而人大代表联络站则是我国人民代表大会制度和全过程人民民主在基层的生动实践平台。近年来,人大代表联络站得到快速发展,但也同样面临一系列困境与挑战。因此,进一步厘清人大代表联络站的功能定位、践行全过程民主模式、完善人大代表联络站制度具有重要的理论价值和现实意义。已有研究缺乏对人大代表联络站的实践发展进行全方位的理论探讨和系统总结。本文基于全过程人民民主视角,分别从法律定位、政治定位、角色定位和实践定位四个维度阐释人大代表联络站的具体功能定位,梳理浙江省人大代表联络站践行全过程人民民主的创新模式和做法,剖析人大代表联络站在身份认同、代表履职、实践功能、组织建设和协商议事等五个方面所面临的主要困境,最后提出完善人大代表联络站的对策路径。

基于新型自适应滑模观测器的PMSM无传感器控制

为了实现无位置传感器控制策略在永磁同步电机中的应用,在传统滑模观测器的基础上提出了一种改进型的自适应滑模观测器算法。提出的改进型自适应滑模观测器中使用更平滑的sigmoid函数取代了传统的符号函数,并结合反电动势的自适应律有效地减少了提取的反电动势中包含的高频分量,避免了低通滤波器在使用过程中带来的抖振和相位延迟现象。最后反电动势中包含的转子位置信息与速度信息通过锁相环提取。为了验证模型的可行性,基于MATLAB/Simulink搭建了仿真模型进行了仿真分析,并以TMS320F28377芯片为核心搭建了永磁同步电机硬件实验平台进行实验验证,仿真与实验结果验证了该方法的有效性和实用性。

基于微分平坦的板球系统反步滑模控制

为改善板球系统轨迹跟踪控制误差大,控制精度低的问题,提出了一种基于微分平坦的板球系统反步滑模控制方法。首先基于欧拉-拉格朗日方程建立板球系统的运动学模型,通过合理简化得到解耦线性状态空间模型。以X轴方向控制器设计为例,利用微分平坦技术获得系统的目标状态量以及前馈控制量,建立误差系统,进而采用反步法实现对误差系统的滑模控制,利用李雅普诺夫稳定性理论证明了闭环系统的稳定性。算法中使用双曲正切函数抑制滑模的抖动,实现了对板球系统的轨迹高精度跟踪控制。仿真实验结果表明,该方法控制精度高,具有良好的控制效果。

职业教育数字教材建设与应用探析

职业教育数字化教材建设与应用前景广阔。通过对职业教育数字教材定义的辨析和梳理,以及将其和类似的教育信息化产品进行比较,厘清职业教育数字教材的概念和内涵,指出其应当具备特殊出版物特性、职业教育特点、数字化特征。进而,在回顾职业教育数字教材的发展与演进的基础上,阐述了其应当具备的三个层次功能。在刻画职业教育数字教材生态体系应具备的创作、审核、发布(发行)、应用的完整闭环,并涵盖作者服务、读者服务、管理者服务、出版者内部流程和线上编审校服务系统的基础上,提出建设普惠性标准化的数字教材出版平台,开发不同类型不同层次的数字化教材产品的工作要点。之后,辨析了其与新型活页式教材、工作手册式教材的不同点与整合创新的意义。梳理总结了此类教材的开发基本原则和主要策略。最后,从内容彰显职教特点、数字资源规范化开发、建立开发流程标准、建设质量评价体系四个方面提出了标准和规范化的开发策略。

基于多域信息融合与深度分离卷积的轴承故障诊断网络模型

针对传统卷积神经网络(CNN)对滚动轴承振动信号的故障识别准确率不高这一问题,提出了一种基于多域信息融合结合深度分离卷积(MDIDSC)的轴承故障诊断方法。首先,利用自适应噪声的完全集合经验模态分解(CEEMDAN)算法对轴承振动信号进行了分解;然后,利用分解出的本征模态函数(IMF)的各个分量构建了多空间状态矩阵,并将该多空间状态矩阵输入该深度分离卷积模型中,进行了卷积训练;同时,在该深度分离卷积模型中添加了残差结构,对数据特征进行了复利用,并对卷积核进行了深度分离,解决了深度模型的网络退化问题;最后,提出了一种空间特征提取方法,对模型参数进行了修剪,采用一种自适应学习率退火方法进行了梯度优化,以避免模型陷入局部最优。研究结果表明:通过对多个轴承故障数据集进行对比分析可知,MDIDSC在轴承故障诊断方面的准确率和稳定性明显优于其他方法,MDIDSC的最高测试准确率为100%,平均测试准确率为99.07%;同时,在测试集中的最大损失和平均损失分别为0.1345和0.0841;该结果表明MDIDSC在轴承故障诊断方面具有一定的优越性。

基于医养结合模式的双心养护在老年冠心病患者中的应用价值

目的观察医养结合模式下双心养护对老年冠心病患者心功能、情绪状态的影响。方法收集2020年1月—2023年1月丰县人民医院老年冠心病患者80例进行前瞻性研究,随机数字表法分为观察组(n=40)与对照组(n=40),分别行基于医养结合模式的双心养护与常规护理。比较两组护理前后心功能指标、情绪状态、并发症情况及对不同模式护理的满意度。结果护理前心功能指标组间差异均无统计学意义(P>0.05),护理后观察组LVEF高于对照组,LVEDV、LVESV低于对照组(均P<0.05)。情绪状态方面,抑郁-焦虑-压力量表21(DASS-21)各项评分护理前组间比较无统计学差异(P>0.05),护理后均降低,观察组低于对照组(P<0.05)。观察组并发症发生率5.00%,低于对照组的20.00%(P<0.05);护理满意度比较,观察组(97.50%)高于对照组(80.00%)(P<0.05)。结论医养结合模式的双心养护,可改善老年冠心病患者心功能及情绪状态,并减少并发症。