Effects of multiple shapes for steady flow with transformer oil+Fe_(3)O_(4)+TiO_(2) between two stretchable rotating disks

In this study,we examine the effects of various shapes of nanoparticles in a steady flow of hybrid nanofluids between two stretchable rotating disks.The steady flow of hybrid nanofluids with transformer oil as the base fluid and Fe_(3)O_(4)+TiO_(2)as the hybrid nanofluid is considered.Several shapes of Fe_(3)O_(4)+TiO_(2)hybrid nanofluids,including sphere,brick,blade,cylinder,and platelet,are studied.Every shape exists in the same volume of a nanoparticle.The leading equations(partial differential equations(PDEs))are transformed to the nonlinear ordinary differential equations(ODEs)with the help of similarity transformations.The system of equations takes the form of ODEs depending on the boundary conditions,whose solutions are computed numerically by the bvp4c MATLAB solver.The outputs are compared with the previous findings,and an intriguing pattern is discovered,such that the tangential velocity is increased for the rotation parameter,while it is decreased by the stretching values because of the lower disk.For the reaction rate parameter,the concentration boundary layer becomes shorter,and the activation energy component increases the rate at which mass transfers come to the higher disk but have the opposite effect on the bottom disk.The ranges of various parameters taken into account are Pr=6.2,Re=2,M=1.0,φ_(1)=φ_(2)=0.03,K=0.5,S=-0.1,Br=0.3,Sc=2.0,α_(1)=0.2,γ=0.1,E_(n)=2.0,and q=1.0,and the rotation factor K is within the range of 0 to 1.

Weak Fault Feature Extraction of the Rotating Machinery Using Flexible Analytic Wavelet Transform and Nonlinear Quantum Permutation Entropy

Addressing the challenges posed by the nonlinear and non-stationary vibrations in rotating machinery,where weak fault characteristic signals hinder accurate fault state representation,we propose a novel feature extraction method that combines the Flexible Analytic Wavelet Transform(FAWT)with Nonlinear Quantum Permutation Entropy.FAWT,leveraging fractional orders and arbitrary scaling and translation factors,exhibits superior translational invariance and adjustable fundamental oscillatory characteristics.This flexibility enables FAWT to provide well-suited wavelet shapes,effectively matching subtle fault components and avoiding performance degradation associated with fixed frequency partitioning and low-oscillation bases in detecting weak faults.In our approach,gearbox vibration signals undergo FAWT to obtain sub-bands.Quantum theory is then introduced into permutation entropy to propose Nonlinear Quantum Permutation Entropy,a feature that more accurately characterizes the operational state of vibration simulation signals.The nonlinear quantum permutation entropy extracted from sub-bands is utilized to characterize the operating state of rotating machinery.A comprehensive analysis of vibration signals from rolling bearings and gearboxes validates the feasibility of the proposed method.Comparative assessments with parameters derived from traditional permutation entropy,sample entropy,wavelet transform(WT),and empirical mode decomposition(EMD)underscore the superior effectiveness of this approach in fault detection and classification for rotating machinery.

Partial Discharge Source Classification and De-Noising in Rotating Machines Using Discrete Wavelet Transform and Directional Coupling Capacitor

This paper introduces a new method to separate PD1 from other disturbing signals present on the high voltage genera-tors and motors. The method is based on combination of a pattern classifier, the Discrete Wavelet Transform (DWT), to de-noise PD and Time-Of-Arrival method to separate PD sources. Furthermore, it will be shown that it can recognize PD sources including rotating machine’s internal and external discharge pulses (e.g. on the bus bar).

基于RT-DETR-Faster的苹果采摘机器人实时目标检测算法

为了解决苹果采摘中目标小,实时性要求高等问题,提出了一种基于RT-DETR的采摘机器人目标检测方法,名为RT-DETR-Faster。首先,采用FasterNet部分卷积替换主干网络的传统卷积,有效提升了模型的运算速度;其次,使用改进的级联注意力编码器替换原始的编码器,使网络更专注于目标区域;最后,引入Faster_Rep融合特征模块,保留更多有效特征并减少计算量。该文在实际的果园图像上进行了实验,结果表明,该文提出的算法与原始的RT-DETR算法相比,FPS提升了34%,帧数达到了47.9,同时准确率更高,适用于苹果采摘机器人的实时目标检测任务。

Magneto-Photo-Thermoelastic Excitation Rotating Semiconductor Medium Based on Moisture Diffusivity

In this research,we focus on the free-surface deformation of a one-dimensional elastic semiconductor medium as a function of magnetic field and moisture diffusivity.The problem aims to analyze the interconnection between plasma and moisture diffusivity processes,as well as thermo-elastic waves.The study examines the photothermoelasticity transport process while considering the impact of moisture diffusivity.By employing Laplace’s transformation technique,we derive the governing equations of the photo-thermo-elastic medium.These equations include the equations for carrier density,elastic waves,moisture transport,heat conduction,and constitutive relationships.Mechanical stresses,thermal conditions,and plasma boundary conditions are used to calculate the fundamental physical parameters in the Laplace domain.By employing numerical techniques,the Laplace transform is inverted to get complete time-domain solutions for the primary physical domains under study.Referencemoisture,thermoelastic,and thermoelectric characteristics are employed in conjunction with a graphical analysis that takes into consideration the effects of applied forces on displacement,moisture concentration,carrier density,stress due to forces,and temperature distribution.

基于旋转去噪Transformer的遥感图像目标端到端检测

提出一种基于旋转去噪Transformer的遥感图像旋转目标端到端检测方法。首先,针对遥感图像滑窗切片时存在目标切断影响网络学习的问题,提出基于密集栅格的遥感图像数据增强方法,提升网络对不完整目标的预测能力。其次,提出旋转去噪Transformer架构的端到端检测网络,采用PVTv2提取多尺度特征,通过Transformer编码器对特征进行聚合与增强,利用Transformer解码器对目标解码,通过分类头和回归头直接实现旋转目标预测,即端到端检测。最后,提出旋转对比去噪学习方法,将去噪学习用于旋转目标检测,加速网络收敛。在2023全国大数据与计算智能挑战赛数据集上,所提方法的m AP达到了98.38%。

基于改进Transformer的复合故障解耦诊断方法

大多复合故障诊断方法视复合故障为一种新的单一故障类型,忽视了内部单一故障的相互作用、故障分析粒度含糊和解释性差.为了解决复合故障难解耦的问题,针对工业环境中复合故障数据极少的情况,提出一种基于改进Transformer的复合故障解耦诊断方法.诊断流程分为预处理、特征提取和故障解耦3个步骤.故障解耦引入Transformer的解码器,利用交叉注意力机制使得每个单一故障标签可以在提取的特征层中,自适应地关注到与故障特征相对应的判别特征区域,进一步预测每个单一故障标签的输出概率以实现复合故障解耦.设计多组复合故障试验与业界先进算法进行对比,以验证方法的有效性.结果表明,所提方法在少量单一故障训练样本和极少量复合故障训练样本情况下,有较高的诊断准确度.当训练集中复合故障样本数仅为5时,复合故障诊断准确度达到88.29%,与其他方法比较更具有显著优势.

年龄 房颤 舒张压对急性缺血性脑卒中rt-PA静脉溶栓后出血转化的影响

目的 探究年龄、房颤和舒张压对急性缺血性脑卒中重组组织型纤溶酶原激活剂(rt-PA)静脉溶栓后发生颅内出血转化的影响因素。方法 采用随机抽样的方法,选取2020年1月至2021年12月蚌埠市第三人民医院卒中中心收治的采用rt-PA静脉溶栓治疗的急性缺血性脑卒中患者92例,根据是否发生颅内出血分为出血组(n=20)和非出血组(n=72)。对两组患者的临床资料进行单因素分析,对存在统计学差异的变量(年龄、房颤和舒张压)进行二元logistic回归,构建临床预测方程,检测方程的区分度和校准度,利用受试者工作特征(ROC)曲线分析影响因素的预测效度,用分层回归分析差异变量舒张压在年龄和是否出血转化间的中介效应。结果 两组患者年龄、房颤和舒张压存在差异,二元logistic回归结果显示,年龄(OR=1.072,95%CI:1.007~1.142)、房颤(OR=12.980,95%CI:1.701~99.026)、舒张压(OR=1.076,95%CI:1.030~1.123)是rt-PA静脉溶栓后颅内出血的危险因素,ROC曲线分析显示,年龄曲线下面积(AUC=0.692,P=0.003,诊断界限值72.5岁)、舒张压(AUC=0.844,P<0.001,诊断界限值82.5 mmHg)和房颤(AUC=0.690,P=0.004)对出血转化有较好的预测效度,中介分析显示,舒张压、房颤在年龄和是否出血转化间起部分中介作用。结论 高舒张压、伴发房颤和老年是急性缺血性脑卒中rt-PA静脉溶栓后颅内出血发生的危险因素,rt-PA静脉溶栓前调整舒张压,针对房颤采取防治措施可能是减少老年人发生溶栓后出血转化的重要手段。

基于RT-Unet的医学图像分割算法

近年来,由于Transformer能够有效地捕获全局上下文信息,在机器视觉领域展现了巨大的应用潜力。然而,它只能获取单尺度的上下文信息,对于细节信息的提取仍然存在一定的局限性。针对此类问题,提出了RT-Unet算法。该算法在RESwin Transformer模块中引入内在的局部归纳偏置,并在位置嵌入与编码模块使用4个连续的卷积层。将卷积与Transformer有效地组合在一起,既可以获得丰富的多尺度特征,又可以关注局部细节信息与远程依赖关系。另外,改用GELU激活函数增加算法的非线性因素,避免训练时出现梯度消失问题。实验采用Synapse腹部多器官分割数据集,结果表明RT-Unet的性能优于ViT,V-Net,U-Net,Swin-Unet和TU-Net等算法,并取得了DSC为79.08%,HD为23.43 mm的分割结果。

Exact Solution of Second Grade Fluid in a Rotating Frame through Porous Media Using Hodograph Transformation Method

In this paper exact solution for a homogenous incompressible, second grade fluid in a rotating frame through porous media has been provided using hodograph-Legendre transformation method. Results are summarised in the form of theorems. Two examples have been taken and streamline patterns are shown for the solutions.

Fault Feature Extraction of Rotating Machinery Based on Wavelet Transformation and Multi-resolution Analysis

This paper expounded in detail the principle of energy spectrum analysis based on discrete wavelet transformation and multiresolution analysis. In the aspect of feature extraction method study, with investigating the feature of impact factor in vibration signals and considering the non-placidity and non-linear of vibration diagnosis signals, the authors import wavelet analysis and fractal theory as the tools of faulty signal feature description. Experimental results proved the validity of this method. To some extent, this method provides a good approach of resolving the wholesome problem of fault feature symptom description.

Analysis of Transforming dq Impedances of Different Converters to A Common Reference Frame in Complex Converter Networks

DQ impedance-based method has been widely used to study the stability of three-phase converter systems.As the dq impedance model of each converter depends on its local dq reference frame,the dq impedance modeling of complex converter networks gets complicated.Because the reference frames of different converters might not fully align,depending on the structure.Thus,in order to find an accurate impedance model of a complex network for stability analysis,converting the impedances of different converters into a common reference frame is required.This paper presents a comprehensive investigation on the transformation of dq impedances to a common reference frame in complex converter networks.Four different methods are introduced and analyzed in a systematic way.Moreover,a rigorous comparison among these approaches is carried out,where the method with the simplest transformation procedure is finally suggested for the modeling of complex converter networks.The performed analysis is verified by injecting two independent small-signal perturbations into the d and the q axis,and doing a point-by-point impedance measurement.

氨基末端脑利钠肽前体与急性缺血性脑卒中患者rt-PA静脉溶栓后出血转化及预后的相关性

目的探究NT-proBNP与缺血性脑卒中(CIS患者)rt-PA静脉溶栓后出血转化及预后的相关性。方法选取2021-10—2022-12于盘锦市中心医院行rt-PA静脉溶栓治疗的60例CIS患者为研究对象。根据rt-PA静脉溶栓治疗后出血及预后情况对患者进行分组,比较组间患者的临床资料、出血转化危险因素、预后不良危险因素、血浆NT-proBNP水平等指标,并分析血浆NT-proBNP水平与患者预后之间的相关性。结果与非出血组相比,出血组患者的基线舒张压、空腹血糖水平、NIHSS评分、NT-proBNP水平和心房颤动史显著升高,TOAST分型、卒中分布差异有统计学意义(均P<0.05)。与预后良好组比较,预后不良组患者的基线NIHSS评分、NT-proBNP、空腹血糖、基线收缩压、高血压史比率显著升高,TOAST分型差异有统计学意义(均P<0.05);CIS患者静脉溶栓治疗后出血转化独立影响因素为NIHSS评分(1.071~1.205)、NT-proBNP(1.432~2.859)及卒中病灶分布情况(1.369~9.874);不良预后独立影响因素为NIHSS评分(1.073~1.206)、NT-proBNP(1.124~1.732)及空腹血糖(0.998~1.323);与其他组相比,未出血组患者的血浆NT-proBNP水平显著下降(P<0.05);NT-proBNP水平与mRS评分呈正向相关。结论氨基末端脑利钠肽前体与急性缺血性脑卒中患者rt-PA静脉溶栓后出血转化及预后之间存在一定的相关性,可作为其评估指标。

急性重症脑梗死患者rt-PA静脉溶栓后出血转化发生状况及影响因素

目的探讨急性重症脑梗死患者重组人组织纤溶酶原激活剂(rt-PA)静脉溶栓后出血转化的发生状况及影响因素。方法回顾性分析102例急性重症脑梗死患者的临床资料,统计rt-PA静脉溶栓后出血转化发生情况,经单因素和多因素Logistic回归分析探讨rt-PA静脉溶栓后发生出血转化的影响因素。结果102例急性重症脑梗死患者rt-PA静脉溶栓后出血转化发生率为18.63%(19/102)。单因素分析和多因素Logistic回归分析显示,合并高血压、有酗酒史及治疗前NIHSS评分高是急性重症脑梗死患者rt-PA静脉溶栓后发生出血转化的危险因素(P<0.05)。结论合并高血压、有酗酒史以及治疗前NIHSS评分高是急性重症脑梗死患者rt-PA静脉溶栓后发生出血转化的危险因素,临床需采取针对性干预措施,以减少溶栓后出血转化的发生。

跃迁系数对旋转Timoshenko梁弯曲振动的影响

在不同梁模型中,轴向力对剪切力的贡献不同,该特性可以使用跃迁系数进行描述.本文讨论了当旋转导致轴向离心力存在时,其跃迁系数对Timoshenko梁弯曲振动的影响.首先推导了含跃迁系数的旋转Timoshenko梁弯曲振动微分方程.然后使用微分变换法(DTM)对弯曲振动微分方程进行求解,得到了系统的固有频率和振型.最后分析了跃迁系数、转速、截面形状、高跨比等参数对系统振动的影响.结果表明,跃迁系数对旋转Timoshenko梁的固有频率和振型均有影响,尤其在高转速、薄壁截面和大高跨比的情况下影响更加显著.

某型雷达天线座旋变轴弯曲故障分析

研究对象为机械扫描的多普勒体制机载雷达,采用平板裂缝天线和伺服传动系统实现雷达的波束扫描。天线座是伺服传动系统的关键组成部分。该型天线座已稳定生产多批次,工艺变更后进行了试生产,首件在随机振动验证试验中出现了方位旋变轴弯曲故障。在分析天线座组成和工作原理的基础上,通过开展仿真分析和试验验证,给出了故障产生的原因和机理,并采取了针对性的改进措施,有效地确保了后续批产天线座的质量稳定,对同类工程问题具有重要的参考价值。

缔合Legendre函数的快速插值计算及其在六边形网格模型重力异常计算中的应用

鉴于局部区域非等纬度分布点的超高阶次球谐综合计算效率较低,本文深入研究了缔合Legendre函数的插值算法,结合模型重力异常求解的展开式,提出了超高阶模型空间重力异常插值快速计算方法,为了验证本文方法在东西狭长分布的点集更具有应用优势,采用球谐旋转变换技术进一步提升了计算效率。试验结果表明,利用2160阶次EGM2008模型计算日本地区同一高度的30303个非等纬度分布的六边形网格点处模型重力异常,插值快速计算方法相比逐点计算,在误差不超±0.005 mGal水平下,计算耗时从3669.41 s缩减到98.05 s,同时经过球谐旋转变换,将南北狭长的日本区域点集旋转为东西狭长分布,使得上述相应计算内容的耗时进一步由98.05 s缩减到19.06 s,计算效率相比最初方法提速比达到近200倍,有效解决了非等纬度分布点的超高阶模型重力异常快速解算的效率难题,且验证了该方法在东西狭长分布的情况下具有更高的提速比。

基于机器视觉的汽车压装衬套偏转角度测量

衬套安装的角度测量对于确保压装过程中汽车悬架与衬套的准确组装十分重要,现有的单目测量方法由于存在相机安装环境受限、测量准确率低的缺点而难以广泛应用。为提高衬套偏转角度的测量准确性,提出了一种基于特征匹配与径向基神经网络的衬套偏转角度测量方法。采用Hessian矩阵优化ORB算法,剔除误匹配对,提高ORB算法匹配性能;采用基准模板匹配策略,解决相机斜视状态下图像特征被遮挡导致的无法匹配问题,并将采集图像的特征点转换至基准模板上;通过引入径向基函数神经网络进行偏转角度软测量,拟合特征点与偏转角度的非线性关系,提高衬套偏转角度测量的精度。实验结果表明,所研究方法可以有效进行偏转角度测量,最大平均相对误差为2.72%,满足衬套偏转角度测量要求,在汽车生产过程中有一定的应用价值。

矩阵初等变换的几何意义

矩阵的初等变换在线性代数中应用十分广泛,以初等行变换为例,分别给出了非退化的初等变换、退化的初等变换的实例与对应的几何图形,在此基础上给出了任意角度的旋转.在教学过程中,通过挖掘初等变换的几何意义,可以使学生建立代数与几何的统一观,促进学生抽象思维与形象思维协调发展.

低转速航空发动机滚动轴承故障深度异常检测方法

针对航空发动机滚动轴承在低转速状态下故障难检测的问题,提出了一种基于Transformer框架的深度支持向量描述方法用于检测低转速滚动轴承的故障。首先,构建了基于Transformer模型的振动特征提取主干网络。然后,将所提取的特征输入一个三层自编码器结构,用于计算网络模型的损失函数。为减少网络计算量,提高训练速度,在预处理中将滚动轴承的振动加速度时域信号通过快速傅里叶变换(FFT)得到的频谱结果作为网络的输入,且仅依靠正常数据完成模型的训练。最后,在带机匣的航空发动机转子试验器和某型真实的航空发动机上分别进行了试验验证。结果表明,所提方法能够准确的实现对低转速滚动轴承故障的检测,且检测精度分别为93%和100%,充分表明该方法具有很好的异常检测能力及应用价值。