Fault Location Identification for Localized Intermittent Connection Problems on CAN Networks

The intermittent connection（IC）of the field-bus in networked manufacturing systems is a common but hard troubleshooting network problem,which may result in system level failures or safety issues.However,there is no online IC location identification method available to detect and locate the position of the problem.To tackle this problem,a novel model based online fault location identification method for localized IC problem is proposed.First,the error event patterns are identified and classified according to different node sources in each error frame.Then generalized zero inflated Poisson process（GZIP）model for each node is established by using time stamped error event sequence.Finally,the location of the IC fault is determined by testing whether the parameters of the fitted stochastic model is statistically significant or not using the confident intervals of the estimated parameters.To illustrate the proposed method,case studies are conducted on a 3-node controller area network（CAN）test-bed,in which IC induced faults are imposed on a network drop cable using computer controlled on-off switches.The experimental results show the parameters of the GZIP model for the problematic node are statistically significant（larger than 0）,and the patterns of the confident intervals of the estimated parameters are directly linked to the problematic node,which agrees with the experimental setup.The proposed online IC location identification method can successfully identify the location of the drop cable on which IC faults occurs on the CAN network.

Parameter identification algorithm for fault location using one terminal data based on frequency domain

This paper presents a novel algorithm of fault location for transmission line.Solving the network spectrum equations for different frequencies the fault can be located accurately by this algorithm with one terminal data of voltage and current,and the identified parameters,such as fault distance, fault resistance,and opposite terminal system resistance and inductance.The algorithm eliminates the influence of the opposite system impedance on the fault location accuracy,which causes the main error in traditional fault location methods using one terminal data.A method of calculating spectrum from sampled data is also proposed.EMTP simulations show the validity and higher accuracy of the fault location algorithm compared to the existing ones based on one terminal data.

CFRP Voids 3D Identification and Location Method Based on the Process of Backscattered Signal

The porosity of carbon fiber reinforced polymer（CFRP） workpiece is tested by ultrasonic in pulse-echo mode.When the ultrasonic frequency is close to the resonant frequency of the workpiece,the resonance will occur along the thickness direction.If the CFRP workpiece contains voids,the resonant frequency will decrease.The result of ultrasonic testing experiment clearly draws the conclusion that the center frequency of the backscattered signal spectrum declines with increasing porosity.Based on the above theory and conclusion,the three-dimensional（3D） voids identification and location method is established.Firstly,the ultrasonic signals are collected and the center frequencies of the backscattered signal spectra are calculated.Then the C-scan of center frequency is generated to identify the voids.At last the B-scan of center frequency for the region containing voids is generated to determine the depth of the voids.The experimental results show that,by using this method,the voids in the CFRP workpiece can be identified and pinpointed.

Single Phase-to-Ground Fault Line Identification and Section Location Method for Non-Effectively Grounded Distribution Systems Based on Signal Injection

A diagnostic signal current trace detecting based single phase-to-ground fault line identifica- tion and section location method for non-effectively grounded distribution systems is presented in this paper.A special diagnostic signal current is injected into the fault distribution system,and then it is detected at the outlet terminals to identify the fault line and at the sectionalizing or branching point along the fault line to locate the fault section.The method has been put into application in actual distribution network and field experience shows that it can identify the fault line and locate the fault section correctly and effectively.

Acoustic emission source location method and experimental verification for structures containing unknown empty areas

Acoustic emission(AE)localization plays an important role in the prediction and control of potential hazardous sources in complex structures.However,existing location methods have less discussion on the presence of unknown empty areas.This paper proposes an AE source location method for structures containing unknown empty areas(SUEA).Firstly,this method identifies the shape,size,and location of empty areas in the unknown region by exciting the active AE sources and using the collected AE arrivals.Then,the unknown AE source can be located considering the identified empty areas.The lead break experiments were performed to verify the effectiveness and accuracy of the proposed method.Five specimens were selected containing empty areas with different positions,shapes,and sizes.Results show the average location accuracy of the SUEA increased by 78%compared to the results of the existing method.It can provide a more accurate solution for locating AE sources in complex structures containing unknown empty areas such as tunnels,bridges,railroads,and caves in practical engineering.

Adaptive restarting method for LCC-HVDC based on principle of fault location by current injection

The existing LCC-HVDC transmission project adopts the fixed-time delay restarting method.This method has disadvantages such as non-selectivity,long restart process,and high probability of restart failure.These issues cause a secondary impact on equipment and system power fluctuation.To solve this problem,an adaptive restarting method based on the principle of fault location by current injection is proposed.First,an additional control strategy is proposed to inject a current detection signal.Second,the propagation law of the current signal in the line is analyzed based on the distributed parameter model of transmission line.Finally,a method for identifying fault properties based on the principle of fault location is proposed.The method fully considers the influence of the long-distance transmission line with earth capacitance and overcomes the influence of the increasing effect of the opposite terminal.Simulation results show that the proposed method can accurately identify the fault properties under various complex fault conditions and subsequently realize the adaptive restarting process.

Genetic Identification of a New Small Grain Dwarf Gene in Rice

The plant material used in the study was rice line 162d, a new small grain dwarf mutant. Polymorphic analysis of 221 SSR loci demonstrated that 162d derived from a semidwarf variety Shuhui 162 through mutation, and 162d and Shuhui 162 were just a pair of near isogenic lines. Genetic analysis of F_1 and F_2 populations suggested that dwarfism in 162d was controlled by a single recessive gene. Phenotypic characteristics of the mutant gene were that plant height was about a quarter of normal height, grain size about a quarter of normal size, leaf was short and broad, and seed setting rate was very low, compared with the near isogenic line Shuhui 162. The mutant gene was sensitive to gibberellin (GA_3) treatment and did not located on the region near the centromere of rice chromosome 5, where dl gene located. Therefore, it was concluded that the mutant gene of 162d was a new small grain dwarf gene in rice.

A Disturbance Source Location Method on the Low Frequency Oscillation With Time-varying Steady-state Points

The low frequency oscillation is a serious threat to security and stability of a power grid.How to locate the disturbance source accurately is an important issue to low frequency oscillation disposal.Existing methods have poor adaptability to the low frequency oscillation with time-varying steady-state points because of the limitations in the location criterion derivation.A disturbance source location method on a low frequency oscillation with good generality is presented in the paper.Firstly,the reasons why the steady-state points are time-varying on a low frequency oscillation are analyzed.Then,based on the energy function construction form,the branch transmission energy is decomposed into state energy,reciprocating energy and dissipation energy by mathematical derivation.The flow direction of the dissipation energy shows the source and destination of the disturbance energy,and the specific location of a disturbance source can be identified according to its flow direction.Meanwhile,to meet the needs of energy calculation,a recognition method on the electrical quantities steady-state points is also presented by using the cubic spline interpolation.Simulation results show the correctness of the derivation and analysis on energy structure in the paper,and the disturbance source can be located accurately according to the dissipation energy.

基于改进YOLO v5的复杂环境下桑树枝干识别定位方法

为实现复杂自然环境下对桑树嫩叶处枝干的识别检测,改变当前桑叶采摘设备作业过程中依赖人工辅助定位的现状,解决识别目标姿态多样和环境复杂导致的低识别率问题,提出一种基于改进YOLO v5模型的桑树枝干识别模型(YOLO v5-mulberry),并结合深度相机构建定位系统。首先,在YOLO v5的骨干网络中加入CBAM(Convolutional block attention module)注意力机制,提高神经网络对桑树枝干的关注度;并增加小目标层使模型可检测4像素×4像素的目标,提高了模型检测小目标的性能;同时使用GIoU损失函数替换原始网络中的IoU损失函数,有效防止了预测框和真实框尺寸较小时无法正确反映预测框及真实框之间位置关系的情况;随后,完成深度图和彩色图的像素对齐,通过坐标系转换获取桑树枝干三维坐标。试验结果表明:YOLO v5-mulberry检测模型的平均精度均值为94.2%,较原模型提高16.9个百分点,置信度也提高12.1%;模型室外检测时应检测目标数53,实际检测目标数为48,检测率为90.57%;桑树嫩叶处枝干三维坐标识别定位系统的定位误差为(9.4985 mm,11.285 mm,19.11 mm),满足使用要求。该研究可实现桑树嫩叶处枝干的识别与定位,有助于推动桑叶智能化采摘机器人研究。

基于多视角信息融合的公路桥梁车辆荷载时空位置识别

针对现有方法在复杂交通场景下难以准确获取桥上车辆荷载时空分布的问题,提出了一种基于多视角信息融合的车辆荷载时空位置识别方法.首先,开发了vadYOLO-StrongSORT模型,可在单视角下同时检测和跟踪车辆;然后,在图像标定和跨视角车辆匹配基础上,采用自适应加权最小二乘法进行多视角信息融合以修正车辆轨迹;最后,结合车辆轨迹和车轴配置,重构车轴荷载的时空位置分布.通过模型试验评估了所提方法在典型交通场景下的性能.结果表明:相较于基于单视角的车辆位置识别方法,多视角信息融合方法在跟踪稳定性、定位精度和抗遮挡性能上有显著提升;变道场景下,所提方法的最高平均定位误差低于2.0 cm,明显优于单视角方法的17.0 cm;多车遮挡场景下,所提方法的车辆捕获率可达100%,而单视角方法最高仅为72.5%;同时,与其他检测跟踪模型相比,vadYOLO-StrongSORT在试验中取得了最高的识别精度.

基于BA-MKELM的微电网故障识别与定位

提出一种基于贝叶斯算法优化多核极限学习机的微电网故障识别和定位方法。针对极限学习机输入参数和隐含层节点数随机选取导致回归能力不足的问题,引入核函数,将多项式与高斯径向基核函数加权组合构成多核极限学习机建立故障识别与定位模型,并采用贝叶斯算法对多核极限学习机相关参数进行优化,进一步提高模型的逼近能力。为了验证所提模型的故障识别与定位性能,选用极限学习机和多核极限学习机分别建立故障诊断模型进行比较分析。实验结果表明,所提方法能够高性能地识别和定位微电网中任何类型的故障,识别和定位精度更高。

基于模型参数辨识的逆变器故障诊断方法

三相逆变器因已广泛应用于现代工业、交通、航空航天等领域,而具有举足轻重的地位。为解决实际应用中三相逆变器的开路故障严重影响系统正常稳定运行的情形,提出一种基于模型参数辨识的逆变器开路故障的检测和定位方法。该方法通过采集逆变器三相输出电流,将三相电流值进行Clarke变化和归一化处理后,构建逆变器参数模型。将快速递归算法与参数模型结合,对逆变器进行实时参数估计,并将估计的参数组成故障诊断向量,对应逆变器的不同类型的21种开关故障可以形成基准向量矩阵库。正常运行时,监测到的向量和基准模型向量之间的欧氏距离接近于0,而当逆变器发生开路故障时,向量间的欧氏距离将迅速超过一个阈值,据此变化可以检测逆变器是否发生开关开路故障的发生。在检测到开路故障后,对故障开关进行精准定位,通过实时对比与基准模型库向量欧拉距离值得到最小距离所对应的故障标签,通过查询故障分类表,可以定位发生开路故障的开关。在半实物仿真平台开展了逆变器故障的实验,验证方法的有效性和准确性。实验展开了对不同负载下,不同类型的三相逆变器开关管开路故障的诊断,实验结果证明了方法能精确地定位到不同的类型的三相逆变器开路故障,同时也对不同负载运行情况下的故障诊断表现出高鲁棒性。

基于地球物理技术圈定沉积变质型富铁矿体:辽宁鞍山齐大山铁矿例析

辽宁鞍山—本溪地区是中国北方最重要的铁矿资源基地之一,区内分布有数量不等的富铁矿体,长期以来对富铁矿成矿理论研究成果丰硕,但针对富铁矿找矿技术方面的研究则相对缺乏。本文以辽宁鞍山齐大山铁矿为研究对象,基于贫铁矿体和富铁矿体的物性参数差异,优选地面高精度磁法和高密度电阻率法,开展齐大山铁矿内富铁矿体的综合地球物理探测研究工作。研究结果显示,地面高精度磁法可以通过16000 nT以上的高磁场强度特征圈出贫铁矿磁异常场内的富铁矿体,而高密度电阻率法则可以精细刻画高磁异常范围内的富铁矿体形态特征和规模;磁铁矿富矿电阻率小于2200Ω·m,以此为约束条件构建地面磁法的正反演模型,可实现对贫铁矿层中富铁矿体的准确识别定位;齐大山铁矿NNW走向断层与NEE横向断层交汇处更易产出厚大富铁矿体。

基于改进灰狼优化算法的结构损伤识别

结合模态柔度矩阵、广义模态柔度矩阵和振型三个识别精度较好的指标,构造新的目标函数求解损伤识别问题。通过Nelson方法求解得到的频率与振型的导数,得到对结构刚度发生变化时更具敏感性的位置,然后在这些位置布置传感器以提取结构信息。针对原有的灰狼算法虽然全局搜索能力强,但是存在局部搜索精度差的问题,本文从初始种群和收敛因子等方面着手,改善灰狼算法的局部搜索能力及收敛速度。最后利用提出的方法,通过识别梁模型及桁架模型中的损伤单元说明本文方法的有效性。

多能互补发电系统故障识别与测距方法

随着大量新能源的接入,使得多端柔性直流系统(modular multilevel converter based multi-terminal direct current, MMC-MTDC)故障特征愈加复杂,快速准确的故障识别与测距是亟需解决的关键难题之一。为此,提出了一种风-光-储-蓄互补发电站经柔性直流输电外送系统故障识别与测距方法。首先,搭建风-光-储-蓄互补发电站经柔直外送系统,在此基础上,提出了一种Teager能量算子能量熵的新方法,利用测量点正负极Teager能量算子能量熵的比值构建故障选极及区段识别判据。接着,针对已识别的故障线路,提出变分模态分解(variational mode decomposition, VMD)与Teager能量算子(teager energy operator, TEO)相结合的故障测距方法。最后,利用PSCAD/EMTDC进行仿真,结果表明所提识别方法可以准确判断故障所在线路,所提测距方法能在故障发生2 ms时间窗内实现故障测距,误差率不超过2.55%,并具有较高的耐过渡电阻能力。

结合出行方式的Trans-BiLSTM移动目标位置预测方法

当前位置预测算法往往忽略用户出行方式的关键作用,并在处理长时间序列依赖问题中效果较差.针对这两个问题,提出了一种结合出行方式的Trans-BiLSTM目标位置预测模型.该模型首先提取轨迹段的运动学特征,然后构建基于XGBoost的出行方式识别算法,筛选影响出行方式的主要特征,和轨迹共同作为预测模型输入.最后为了增强轨迹特征的表征能力,引入Transformer编码器,并结合BiLSTM深度挖掘轨迹的上下文关系.在真实GPS轨迹数据集上进行的位置预测对比实验表明,Trans-BiLSTM模型与常用的LSTM和BiLSTM模型相比,目标位置预测的结果RMSE指标分别提升67.4%和17.7%.

一种用于手机定位的标识卡关键技术

针对现有矿用智能手机大多只具有语音通话、视频拍照、数据传输等功能,没有精确定位、位置坐标显示、消息联动等功能,设计了一种基于UWB技术的用于手机定位的标识卡。该标识卡内置于智能手机,通过低功耗蓝牙(BLE)与智能手机实现双向数据通信;标识卡采用TOF定位算法与UWB基站完成精确定位,获得位置坐标信息,通过低功耗蓝牙(BLE)发送至智能手机,在智能手机APP矿井GIS巷道图上显示当前具体位置坐标。详细介绍了标识卡的矿井巷道位置坐标模型、精确定位算法、消息联动可靠传输机制、低功耗休眠技术等关键技术。测试结果表明:该标识卡的定位精度≤±0.3 m,定位距离可达400 m,消息联动传输时延小于2 s,位置坐标显示准确,休眠电流小于25μA,平均电流满足低功耗设计要求。

基于参数自修正的配电网故障定位数字孪生技术研究

配电网参数受天气条件和负载条件等因素影响会发生变化。由于传感装置安装有限、数据延时传输等因素,无法实时获得配电网准确参数,进而给传统故障定位方法的精度带来影响。针对以上问题,通过建立配电网数字孪生模型,基于配电网数字孪生模型的参数自修正技术,提出了一种定位模型随参数变化动态校正的配电网故障定位方法。同时,搭建了基于数字孪生服务器和实时数字仿真系统(real time digital system, RTDS)的数字孪生平台,实现了配电网实时的物理模型和数字孪生模型的同步运行。在算例仿真中,利用该数字孪生平台,验证了基于数字孪生技术的配电网故障定法方法。结果表明,该方法可在各类系统运行条件下实时修正配电网参数,显著提高配电网故障定位的速度和精度。

基于智能视觉识别的自动控制及多工位裁切制备技术研究

针对智能化鞋机需求,介绍一种应用于制鞋裁切机的智能视觉识别的多工位裁切新技术,通过研究装备智能化视觉识别定位技术,结合以具转盘式新架构的多工位高效自动化裁切工艺,提高裁切装备的控制智能化和裁切自动化程度,解决制鞋设备裁切精度不佳,依靠人工识别,生产效率低和废品率高等产业难题,完成动态裁切的过程不需要面料带停止输送后再裁切,提高加工的流畅性,实现具智能视觉识别功能的多工位高效裁切机新装备的开发和产业化。

基于ACNN的配电网故障识别与定位研究

针对目前配电网故障诊断时存在计算时间长、定位精度低的问题,提出了一种基于自适应卷积神经网络的配电网故障识别与定位模型。通过自适应卷积神经网络训练电力数据特征,从而有效提取配电网电力故障特征信息,并基于全连接层对故障进行分类,从而实现端对端的故障检测。通过双端故障定位模型实现故障精确定位。实验结果表明,与DBN模型相比,所提ACNN模型综合性能更优,检测精度提高7.12%时,模型训练时间减少了42.7%。