Discovery of a variable broad absorption line in the BL Lac object PKS B0138-097

We report the discovery of a broad absorption line （BAL） of - 10^4 km s^-1 in width in the previously known BL Lac object PKS 0138-097, which we tentatively identified as an Mg II BAL. This is the first detection of a BAL, which is sometimes seen in powerful quasars with high accretion rates, in a BL Lac object. The BAL was clearly detected in its spectra spanning two epochs at a high luminosity state taken in the Sloan Digital Sky Survey （SDSS）, while it disappeared in three SDSS spectra taken at a low luminosity state. The BAL and its variability pattern were also found in its historical multi-epoch spectra in the literature, but have been overlooked previously. In its high resolution radio maps, PKS 0138-097 shows a core plus a one- sided parsec-scale jet. The BAL variability can be interpreted as follows： The optical emission is dominated by the core in a high state and by the jet in a low state and the BAL material is located between the core and jet so that the BAL appears only when the core is shining. Our discovery suggests that outflows may also be produced in active galactic nuclei at a low accreting state.

Conversion of Object Oriented System into Software Product Line with Delta Modeling Abstract Behavioral Specification

This article contains a system conversion from object oriented design into Software Product Line (SPL) using delta modeling of Abstract Behavioral Specification (ABS). ABS is a modeling language which targets system with high level of variety and supports SPL development with delta modeling. The case study of this thesis is a digital library system called Library Automation and Digital Archive (LONTAR). Originally, LONTAR only uses SOAP-based web service. With ABS, LONTAR will be converted into SPL and implement another web service called REST. The motivation of this conversion of LONTAR from object oriented into SPL is because it is easier to develop system with ABS than using regular object oriented. Product definition in ABS is relatively easier than creating a new subclass and do customization to make it works well.

面向流程制造的数字孪生车间可视化监控系统研究

为了解决流程制造过程监控实时性差、准确性不足的问题,在数字孪生技术迅速发展且与制造业结合愈发紧密的背景下,提出基于生产要素数据、生产工艺流程与多工序设备实体对象的数字孪生车间可视化监控系统架构。从要素、状态、运行逻辑等多个维度对多工序耦合生产线实体对象进行孪生建模,基于OPC UA统一架构的数据采集传输,虚拟车间的实时驱动等关键技术,实现了流程制造设备状态、生产要素工艺全流程三维可视化监控。基于某流程制造企业制丝生产试验线开展了应用验证,为提升流程制造过程中全生产要素的预见性、联动性、自治性提供了方法和实现途径。

3D reconstruction of complex curved objects from line drawings

An active research topic in computer vision and graphics is developing algorithms that can reconstruct the 3D surface of curved objects from line drawings. There are a number of algorithms have been dedicated to solve this problem, but they can＇t solve this problem when the geometric structure of a curved object becomes complex. This paper proposes a novel approach to reconstructing a complex curved 3D object from single 2D line drawings. Our approach has three steps： （1） decomposing a complex line drawing into several simpler line drawings and transforming them into polyhedron; （2） reconstructing the 3D wireframe of curved object from these simpler line drawings and generating the curved faces; （3） combining the 3D objects into the complete objects. A number of examples are given to demonstrate the ability of our approach to successfully perform reconstruction of curved objects which are more complex than previous methods.

Labeling Line Drawings with Hidden-Part-Drawn of Planar Object with Trihedral Vertices

Although line drawings consist of only line segments on a plane, they convey much information about the three-dimensional object structures. For a computer interpreting line drawings, some intelligent mechanism is required to extract three-dimensional information from the two-dimensional line drawings. In this paper, a new labeling theory and method are proposed for the two-dimensional line drawing with hidden-part-draw of a three-dimensional planar object with trihedral vertices. Some rules for labeling line drawing are established. There are 24 kinds of possible junctions for line drawing with hidden-part-draw, in which there are 8 possible Y and 16 W junctions. The three problems are solved that Sugihara＇s line drawing labeling technique exists. By analyzing the projections of the holes in manifold planar object, we have put forward a labeling method for the line drawing. Our labeling theory and method can discriminate between correct and incorrect hidden-part-draw natural line drawings. The hidden-part-draw natural line drawings can be labeled correctly by our labeling theory and method, whereas the labeling theory of Sugihara can only label the hidden-part-draw unnatural line drawings in which some visible lines must be drawn as hidden lines, and some invisible lines must be drawn as continuous lines.

融合多尺度特征的YOLOv8裂缝缺陷检测算法

针对井壁裂缝背景复杂,纵横比差异大,导致检测效率低、漏检等问题,提出了一种融合多尺度特征的裂缝缺陷检测模型EDG-YOLO。设计特征提取模块EIRBlock(efficient inverted residual block),并构建C2fEIR增强主干网络对井壁浅层裂缝特征信息的提取能力。在颈部融合CSP_EDRAN(CSP efficient dilated reparam aggregation network)实现对裂缝特征信息的复用,促进浅层与深层语义信息之间的交互。嵌入DAM(dual attention module)注意力机制,增强井壁裂缝特征的表达能力。构建轻量级检测头GDetect,借助GSConv模块进一步轻量化网络。在自制井壁裂缝数据集上的实验结果表明,与YOLOv8相比,EDG-YOLO的平均检测精度达到87.4%,提高了2.3个百分点,模型的参数量和计算量分别降低了33%和47%,单幅图像推理时间为13.2 ms,满足井下场景的实时检测需求。

Recovering the Shape of Planar Object Depicted by a Line Drawing under Axonometric Projection

A new approach is proposed for automatically creating B-rep models of a three-dimensional planar object from a line drawing depicting the object under orthographically axonometric projection. A new line parameterization that satisfies the uniqueness, boundedness and uniformness for representing lines in 2D and 3D space is given. According to the location relation between lines and planes of object depicted by the line drawing, some constraints about object’s 3D information are produced and a linear system based on those constraints is established. 3D information of a planar body can be obtained by solving the linear system. It is proved that, during the processing, there existed at least four degrees of freedom. It is more convenient to use information about lines and planes instead of points and planes for computer vision and intelligent CAD systems to interpret line drawings of planar objects.

Locating the position of objects in non-line-of-sight based on time delay estimation

Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface（diffuser）.It has very important significance in indirect access to an object or dangerous object detection, such as medical treatment and rescue. An approach to locating the positions of hidden objects is proposed based on time delay estimation. The time delays between the received signals and the source signal can be obtained by correlation analysis, and then the positions of hidden objects will be located. Compared with earlier systems and methods, the proposed approach has some modifications and provides significant improvements, such as quick data acquisition, simple system structure and low cost, and can locate the positions of hidden objects as well： this technology lays a good foundation for developing a practical system that can be used in real applications.

Efficient Object Localization Scheme Based on Vanishing Line in Road Image for Autonomous Vehicles

This paper proposes an efficient object localization method based on a vanishing line. The proposed method can be much improved in time efficiency since it requires scanning only vanishing line area. It requires the time complexity of O(n) while the existing sliding window method requires the time complexity O(n2) for detecting all objects in the entire image. In addition, the range of detection area can be also remarkably reduced when compared with the sliding window method. As a result, the total range and times for searching in the proposed method can be significantly reduced by considering together the distance and position of the object. The experiment on the proposed method is performed with the virtual road data set known as SYNTHIA, and the competitive results are obtained.

改进YOLOv7的输电线路变尺度目标检测

针对输电线路无人机巡检图像中小目标检测精度低下的问题,提出一种改进型YOLOv7的输电线路变尺度多目标的检测方案。方案首次将基于YOLO7的目标检测模型应用到输电线路目标检测中,引入Transformer注意力工作机制,使用g^(n)Conv代替高效聚合网络中的卷积层提取巡检图像特征,经过RFPN网络将不同分辨率特征进行融合后,分别进行不同尺度目标的预测,提高对小目标的检测精度,达到了93.68%的平均检测精度,也可以检测到被遮挡的目标,具有一定的泛化能力。结果表明,上述模型能够有效检测出巡检图像中的防震锤和绝缘子,为后续故障诊断提供了理论依据。

汽车整车多级生产线协同排序优化方法

为满足汽车整车生产线不同工艺车间对车身序列的不同需求,提高汽车生产线多工艺车间的协同生产能力并降低生产成本,提出一种面向汽车整车多级生产线的协同排序优化方法。分析了汽车生产过程中不同工艺车间对车身序列的不同需求,在考虑焊接车间车型更换次数、涂装车间颜色更换次数、总装车间总超载和空闲时间、总装车间物料消耗均衡等传统优化目标的基础上,搭建了缓冲区重排序成本的目标函数,并以此构建了汽车整车多级生产线协同排序多目标优化模型,然后采用基于启发式出入站规则的第三代非支配排序遗传算法对模型进行优化求解。最后通过某公司的实际生产案例,验证了所提模型和方法的有效性。

面向水土生态系统服务协同的土地利用模拟

针对水土生态系统服务功能的相关成果难以应用到实际土地利用规划中的问题。本研究以黄土高原为研究区,使用K-means聚类算法在小流域尺度上划分土地利用结构,结合InVEST模型探究土地利用结构对水土生态系统服务功能的影响。以阳泉市为典型区,设置多情景,结合多目标优化算法和PLUS模型进行未来土地利用模拟。结果表明:在小流域尺度上,黄土高原的土地利用结构可以划分为6类。农地结构、林地结构、农地-草地结构、草地结构、农地-林地-草地结构、裸地结构,最优土地利用占比分别是0.6—0.7,0.5,0.45/0.4(农地/草地),0.75—0.85,0.15/0.4/0.25—0.35(农地/林地/草地)。各土地利用结构中生态系统服务之间的约束曲线基本上是驼峰型、凹波、半凹波和凸波。从未来的土地利用数量上看,3种情景下水域和灌木面积均处于较低水平。其中,对照情景中城建用地面积最大,基准情景次之,协同情景最小。3种情景下,阳泉市均以城市建设为中心,向外依次为耕地、草地和林地的层次分布特征。土地利用的发展过程中各种土地类型之间存在替代规律,即城市建设倾向于取代耕地和草地,草地则可能取代林地和耕地,而林地则可能与草地发生替代关系。研究成果对黄土高原土地利用规划有重要参考价值。

基于多重注意力和特征对齐的销钉缺陷检测方法

电网规模的快速扩张对输电线路的检测维护提出更高的要求,智能高效的自动化电力巡检图像识别算法作为提高检测维护的手段,已经成为目前研究的重要方向之一。为实现巡检图像中销钉缺陷目标的准确识别,文章提出一种基于多重注意力和特征对齐的销钉缺陷检测方法。首先,构建基于可变形注意力的可变形检测变压器(deformable detection transformer,Deformable-DETR)框架,解决现有识别算法中无法通过卷积神经网络进行像素点轮廓-环境关系建模的问题;之后,提出区域注意力特征提取模块,解决由可变形注意力带来的特征粒度不足的问题;为丰富目标物体特征质量,提出基于注意力的候选框特征对齐模块和约束函数;最后,选取华中地区某电力公司的航拍图像数据验证算法性能。结果表明,所提算法总体性能相比于现有的卷积算法提升5.4%,总体平均检测精度达到90.5%。

基于先验知识辅助聚类的粗-精输电线路多金具检测

为了解决输电线路多金具检测任务中存在的小目标和密集遮挡问题并充分利用金具高分辨率航拍图像的信息优势,提出基于先验知识辅助聚类的粗-精输电线路多金具检测方法。首先,通过粗检测模块实现对输电线路高分辨率航拍图像的初步感知。接着,通过先验知识指导结构场景子区域选取模块中聚类算法半径的确定,以自适应聚类出合适的子区域。最后,设计精检测模块充分利用高分辨率航拍图像中的关键信息,进行金具的精确感知,并融合粗检测结果以实现由粗到精的金具识别。经实验证明,基于先验知识辅助聚类的粗-精输电线路多金具检测模型比之基线模型准确率提高了11.3%,对其中小目标金具和密集遮挡金具检测准确率的提高尤为明显。

云边端协作的架空线路鸟巢检测与定位算法研究

针对云端单一集中数据处理时效性低、架空线路上鸟巢检测精度不高、模型对边缘计算设备算力高消耗以及目标定位不准确的问题,提出了一种基于云边端协作的架空线路鸟巢检测与定位算法。该算法通过云、终、边缘3端的协作,解决了云端集中处理效率低的问题,并通过云边数据可视化协作解决由于角度及光线引起的图像不清晰问题。为了提高架空线路鸟巢检测的精度,该算法在YOLOv5x模型基础上进行了优化。首先,通过将主干特征提取网络中的C3模块替换为C2f模块,并在最后一层加入SE(squeeze and excitation)注意力模块,以提升模型对小目标的检测能力。其次,将激活函数替换为Mish函数,解决训练梯度饱和导致神经元停止学习的问题。为了降低模型对边缘计算设备算力的消耗,对改进后的模型进行剪枝微调以降低模型参数规模。基于此优化模型,提出了三维目标定位算法,结合GIS(geographic information system)系统对定位结果进行修正,实现了对检测目标的精准定位。实验数据显示,改进后的模型平均精度均值达到93.25%,比原YOLOv5x模型提升了3.44%,优化后的模型剪枝率达到45%。检测目标经过三维空间建模计算并通过位置修正能够定位到相应的杆塔,有效指导工作人员快速准确排除隐患。

融合高效注意力的多尺度输电线路部件检测

针对在高分辨率输电线路图像中,不同种类部件尺度跨越大,难以被均衡检测的问题,提出一种融合高效注意力的多尺度输电线路部件检测算法。在YOLO v5目标检测算法中,设计添加高效注意力模块ECBAM提高算法特征提取能力。根据输电线路部件的特征分布统计,使用滑动窗口对高分辨率输电线路图像进行切片,并对切片前后的图像分别使用改进后的YOLO v5算法训练模型。将两个模型的检测结果进行集成,得到多尺度输电线路部件检测结果。在公开的PLAD架空输电线路图像数据集上,该模型的检测性能远超现有目标检测模型,Precision可达83.2%,Recall可达92.8%,相比数据集原作者提出的模型,mAP值提升了1.6个百分点,达到了90.8%,且能检测出未在原始数据集上标注出的隐蔽目标,验证了在高分辨率图像中检测多尺度输电线路部件的有效性。

基于深度学习的输电通道入侵物体识别方法研究

针对输电通道在线监测过程中入侵物体大小差异巨大、部分图像对比度低等问题,结合异物图像的特征,提出了一种基于目标检测算法的输电通道入侵物体识别方法。采集输电通道入侵物体图像,利用Retinex算法对输入图像进行增强。在目标识别部分,采用改进的EfficientDet算法作为主体,对算法中锚框的长宽比采用K-means聚类算法进行优化,同时在损失函数中加入了梯度均衡机制。实验结果表明,改进后的算法将mAP值从83.72%提升至87.12%,在入侵物体识别任务上有着优异的性能。

TFD-YOLOv8:一种用于输电线路的异物检测方法

基于无人机航拍图像的异物检测是输电线路智能巡检中的重要环节。YOLO目标检测算法精度高、速度快,是目前的主流算法。但在进行输电线路异物检测时,由于异物目标尺度多变、特征不显著,易出现误检、漏检等问题,提出一种用于输电线路异物检测的YOLOv8模型(TFD-YOLOv8)。首先,在YOLOv8颈部网络构建双分支下采样模块,截留下采样过程中易丢失的尺度相关细节信息,实现语义信息和细节信息的高效融合,提升不同尺度特征图的信息一致性。然后,在主干网络插入混合增强注意力模块,同时提取图像的全局和局部特征,分别生成空间注意力和通道注意力,得到一个包含局部信息、全局信息、空间信息和通道信息的混合增强注意力,增强网络对目标关键特征的捕捉能力。实验结果表明,与基线模型相比,本文方法的平均检测精度提升了6.7%,准确率和召回率分别提升了12.9%和5.1%,与多个现有目标检测方法相比,该方法在检测精度和复杂度上均具有优势。

接触网侵限异物检测与挂网异物清除技术综述

随着高速铁路大规模成网运行,接触网分布范围日益扩大,异物挂网引发的安全事故逐渐增多,成为影响高速列车行车安全的重要因素之一。目前,针对接触网侵限异物的检测与挂网异物的清除方法研究颇少,而电力系统输电线路异物检测、清除的研究成果颇丰。详细综述了接触网侵限异物检测技术的原理、方法以及在铁路领域的应用,重点分析了不同方法的适用场景和优缺点。同时,借鉴电力系统领域异物清除技术研究,重点探讨了挂网异物清除技术的原理、特点,以及在接触网清异的可能性及局限性,结合接触网的特点和运维需求,从远距离实时检测、远距离快速清除以及检测清除装置的小型化与轻量化3个方面,探讨了接触网异物检测清除技术未来的发展方向。

基于改进NSGA-Ⅱ算法的考虑人机系数生产线平衡多目标优化研究

在现代制造加工生产线中,生产设备是制造业生产的重要组成部分。设备的充分利用对于生产需求的匹配度产生直接影响。文章参考“人机系数”的概念,构建了考虑生产线平衡率、平滑指数和人机系数的多目标优化函数问题,采用了改进的自适应NSGA-Ⅱ算法来求解该模型。研究结果表明,在满足客户节拍要求的前提下,调整人机系数可以提高生产线平衡率,降低平滑指数以及生产成本;通过数值算例验证了相比于传统NSGA-Ⅱ算法,改进的自适应NSGA-Ⅱ算法能寻找出质量较高、覆盖更广的近似Pareto解集,为决策者提供选择。证明了本研究方法的有效性和实用性,该研究为现代制造加工生产线提供了一种有效的优化方法,并为其他类似行业提供了借鉴。