BIM 模型相似度计算方法

针对从业者不论是想从本地模型库还是线上共享网站获取所需的BIM 模型只能靠 逐个查找、人工识读的方法,而模型的数量越来越多,获取符合需求的模型需要花费大量的时 间和人力的问题,提出了一种构件级BIM 模型相似度计算方法。从模型的构件出发,以BIM 通用交互格式工业基础类(IFC)文件作数据源,以通用数据标准IFC 2×3 为数据基础,首先提取 模型中构件的几何信息、语义信息等,并利用改进的方向包围盒(OBB)碰撞检测算法查找相连 构件;然后以构件为顶点、构件间连接关系为边将BIM 模型构建为邻接图模型,并用图编辑距 离算法计算邻接图模型的编辑距离;最后即可计算出不同模型之间的相似度。该方法以构件级 BIM 模型的相似度为依据可以大大提升BIM 模型的检索速度与准确率。     

构件库语义描述和检索技术研究

传统的构件库描述和检索方法无法对构件的语义关系进行描述,阻碍了用户对构件的应用。采用本体论的方法建立构件属性的描述模型,实现构件查询基于本体的语义扩展。给出构件属性与用户需求之间相似度的计算方法,帮助用户迅速准确找到需要的构件。     

基于属性相似性度量的 BIM 构件聚类

近年来,随着建筑信息模型(BIM)构件库资源在互联网上迅猛增长,对大量 BIM 构件资源的聚类和检索应用变得日益迫切。现有方法还缺乏对 BIM 构件所承载的领域信息提取, 基于 BIM 构件所承载的领域信息,对 BIM 构件库资源开展聚类研究：①针对 BIM 构件,提出 了一种基于属性信息量的 BIM 构件相似性度量算法,以充分利用 BIM 构件属性信息。通过与 传统的Tversky相似性度量算法以及几何形状相似匹配算法相比,其在相似性度量上效果更好。 ②基于 BIM 构件间的相似性度量算法,提出了一种 BIM 构件库聚类方法。并在 BIMSeek 检索 引擎中集成了 BIM 构件的关键字检索功能以及分类器查看功能,为用户提供更丰富的检索和查 看方式。通过与传统的 K-medoids 和 AP 聚类算法相比,其聚类方法效果更好。     

基于粒子群算法的三维CAD模型相似性计算

为了更加准确地度量两个模型之间的形状差异,提出了一种基于粒子群的模型相似性计算方法。利用面的组成边数来构造面相似度矩阵,通过粒子群算法对该矩阵进行搜索,得到了两个模型之间的最优面匹配序列。根据这个最优面匹配序列,从面相似度矩阵中提取对应的面相似性值。通过累积面之间的相似性来计算模型之间的整体相似性。以此为基础来度量模型之间的差异。实验结果表明：该方法能够准确地度量两个模型之间的相似程度。     

装配式建筑自上而下设计信息协同与模型构建

为顺应国家建筑产业化、智能化发展的政策引导,针对当前装配式建筑专业信息缺乏关联、模 型利用不充分、数据传递效率低下等问题,提出基于建筑信息模型(BIM)技术的自上而下设计方法。以装配式 建筑的设计阶段为切入点,详细阐述了基于 BIM 技术的装配式建筑自上而下设计流程。结合装配式建筑的标 准化构件设计和组装特点,提出一种基于自上而下设计的装配模型,并从层级和专业 2 个角度描述了模型的架 构。针对各专业模型传递时的数据信息标准化、一致性问题,通过工业基础类(IFC)标准对装配模型进行实体和 属性集的扩展,提出基于 IFC 标准的各专业、各阶段的自上而下设计信息协同。经实例验证了 IFC 扩展装配模 型的自上而下设计可行性,为装配式建筑的协同设计提供了有益的方法借鉴。     

基于本体相似度的构件查询算法研究

为了解决语义网环境下构件查询的查全查准率问题,本文提出了基于本体相似度构件查询算法。首先介绍了本体的形式化定义和构件的刻面描述方法,用本体语言(OWL)对构件本体进行形式化的描述;然后针对本体的概念相似度理论和构件刻面匹配度公式存在的不足,用构件本体的概念相似度代替公式中的匹配度,对构件刻面匹配度公式进行改进和分析,提出了本体相似度构件查询算法;算法通过计算查询树和构件树各子刻面本体概念的RDF描述相似度和RDF图结构相似度,再由构件本体相似度匹配公式进行相似度的比较,检索出相似度高的构件。实验结果表明,该算法具有理想的查全查准率。     

针对构件测试本体的语义相似度计算方法

为了提高构件测试信息的检索效率,针对现有本体语义相似度计算方法作用于构件测试本体时容易出现漏检的问题,提出一种结合本体概念和属性的综合语义相似度计算方法。该方法首先结合概念的结构、层次、子代节点个数和祖先节点个数等因素计算概念相似度;然后,结合属性的概念相似度和数据类型相似度计算属性相似度;最后,综合概念相似度和属性相似度计算本体的语义相似度。实验表明该方法可以有效应用于构件测试领域及其他领域的信息检索。     

基于遗传算法的建筑构件位置分布建模仿真

建筑构件位置分布建模存在可用度较低,建模时间较长,总造价较高的问题,为提高建筑物的整体质量,节约建筑成本,增强建筑结构的适用性,提出基于遗传算法的建筑构件位置分布建模方法,单层建筑主体构件以建筑主体构件横截面的轮廓曲线为基础,由单层建筑主体经过复制生成多层建筑主体完成建筑主体构件建模.通过分析建筑构件的组成,将遗传算法应用在建筑构件位置分布建模中,在适应度函数构建方面增加了对称度、均匀度的度量,对建筑构件位置分布建模过程中控制的变量实施操作,求得全局最优解,优化建筑构件位置分布建模.实验结果表明:该方法可用度高,建筑构件位置分布效果高达90％,符合国家规定建筑构件的最大荷载的标准,建模时间最短,总建模时间仅用92秒,总造价较低.     

基于构件的Web系统前馈神经网络可靠性模型

对基于构件结构复杂度较高的Web系统进行可靠性评估时,基于状态或基于路径的软件可靠性评估模型计算复杂度较高,鲁棒性不足。为此,提出了一种计算复杂度低、鲁棒性强的基于构件的前馈神经网络可靠性模型CBPRM。CBPRM将Web系统中各构件的可靠性作为前馈神经网络输入,并基于构件可靠性敏感度对神经元进行动态优化,Web系统可靠性评估由前馈神经网络输出实现。理论分析和实验结果表明,在基于构件结构复杂度较高的Web系统可靠性评估中,CBPRM的计算复杂度低于对比模型,并可确保可靠性评估精度。     

BIM 技术在装配式建筑预制构件生产阶段的应用

为了能够对 BIM 技术在装配式建筑预制构件生产阶段的应用研究现状有较为系统 清晰的掌握,在大量文献阅读的基础上,对装配式建筑预制构件生产过程及工艺流程进行梳理。 首先结合文献的统计分析,对 BIM 相关信息技术在预制构件生产阶段的应用进行介绍,并对预 制构件生产阶段信息交付研究现状进行系统归纳。最后对国内外相关研究存在的差距进行总结, 并提出相应研究建议。通过 BIM 为代表的信息技术在装配式建筑构件生产阶段的应用分析总 结,明确目前预制构件生产阶段信息化管理领域现存的挑战和瓶颈,并针对性的提出 BIM 技术 在这方面未来的发展方向。     

基于IFC标准的楼层平面尺寸标注自动生成方法研究

在 BIM 协同应用中,二维信息在模型空间布置和构件平面尺寸表达等方面具有重 要作用。由于当前不同专业模型难以集成后统一标注,采用 IFC 标准表达二维信息可有效解决 这一问题。为提高 BIM 构件定位与尺寸的查看效率,提出基于 IFC 标准的二维尺寸标注自动生 成方法。首先研究被标注对象的几何和空间位置信息的提取、分类、转换和存储机制,由此推 导楼层中所有被标注对象的尺寸标注信息。然后研究 IFC 标准中尺寸标注实体的空间定位和形 状表达机制,生成尺寸标注实体并将其关联到被标注对象。最后通过一个两层楼案例,验证该 方法的正确性。     

面向 Web 的建筑三维模型可视化方法研究

针对当前工业基础类(IFC)标准文件与 WebGL 框架集成方案存在模型语义完整性差及数据互操 性弱等问题,提出一套建筑信息模型(BIM)数据网络可视化实施方案。该方案以 IFC 标准文件作为输入数据源, 首先对 BIM 模型进行重构,并提出基于 IFC 结构树的构件实例层次拆分策略将原始 IFC 文件实施数模分离; 然后,将重构后的 IFC 模型文件向 glTF 格式文件进行转换,并在转换过程中完成几何空间和语义属性的双重 关系映射;最后,提出基于层次包围体(BVH)结构的 BS-AB 场景构件可视性检测算法对建筑构件进行可见性剔 除。实验结果表明：该方法能够显著减少 BIM 模型数据冗余,且高效完成了对复杂 BIM 场景不可见构件的剔 除工作,降低了渲染管线的开销,为基于 IFC 标准与 WebGL 框架集成方案的 BIM 模型数据网络可视化提供了 一种可行的参考方案。     

State of the art in damage information modeling for RC bridges – A literature review

In Germany, bridges have an average age of 40 years. A bridge consumes between 0.4% and 2% of its construction cost per year over its entire life cycle. This means that up to 80% of the construction cost are additionally needed for operation, inspection, maintenance, and destruction. Current practices rely either on paper-based inspections or on abstract specialist software. Every application in the inspection and maintenance sector uses its own data model for structures, inspections, defects, and maintenance. Due to this, data and properties have to be transferred manually, otherwise a converter is necessary for every data exchange between two applications. To overcome this issue, an adequate model standard for inspections, damage, and maintenance is necessary. Modern 3D models may serve as a single source of truth, which has been suggested in the Building Information Modeling (BIM) concept. Further, these models offer a clear visualization of the built infrastructure, and improve not only the planning and construction phases, but also the operation phase of construction projects. BIM is established mostly in the Architecture, Engineering, and Construction (AEC) sector to plan and construct new buildings. Currently, BIM does not cover the whole life cycle of a building, especially not inspection and maintenance. Creating damage models needs the building model first, because a defect is dependent on the building component, its properties and material. Hence, a building information model is necessary to obtain meaningful conclusions from damage information. This paper analyzes the requirements, which arise from practice, and the research that has been done in modeling damage and related information for bridges. With a look at damage categories and use cases related to inspection and maintenance, scientific literature is discussed and synthesized. Finally, research gaps and needs are identified and discussed.     

Formalized knowledge of construction sequencing for visual monitoring of work-in-progress via incomplete point clouds and low-LoD 4D BIMs

Over the last few years, new methods that detect construction progress deviations by comparing laser scanning or image-based point clouds with 4D BIM are developed. To create complete as-built models, these methods require the visual sensors to have proper line-of-sight and field-of-view to building elements. For reporting progress deviations, they also require Building Information Modeling (BIM) and schedule Work-Breakdown-Structure (WBS) with high Level of Development (LoD). While certain logics behind sequences of construction activities can augment 4D BIM with lower LoDs to support making inferences about states of progress under limited visibility, their application in visual monitoring systems has not been explored. To address these limitations, this paper formalizes an ontology that models construction sequencing rationale such as physical relationships among components. It also presents a classification mechanism that integrates this ontology with BIM to infer states of progress for partially and fully occluded components. The ontology and classification mechanism are validated using a Charrette test and by presenting their application together with BIM and as-built data on real-world projects. The results demonstrate the effectiveness and generality of the proposed ontology. It also illustrates how the classification mechanism augments 4D BIM at lower LoDs and WBS to enable visual progress assessment for partially and fully occluded BIM elements and provide detailed operational-level progress information.     

An approach to combine progressively captured point clouds for BIM update

Building information models (BIMs) provide opportunities to serve as an information repository to store and deliver as-built information. Since a building is not always constructed exactly as the design information specifies, there will be discrepancies between a BIM created in the design phase (called as-designed BIM) and the as-built conditions. Point clouds captured by laser scans can be used as a reference to update an as-designed BIM into an as-built BIM (i.e., the BIM that captures the as-built information). Occlusions and construction progress prevent a laser scan performed at a single point in time to capture a complete view of building components. Progressively scanning a building during the construction phase and combining the progressively captured point cloud data together can provide the geometric information missing in the point cloud data captured previously. However, combining all point cloud data will result in large file sizes and might not always guarantee additional building component information. This paper provides the details of an approach developed to help engineers decide on which progressively captured point cloud data to combine in order to get more geometric information and eliminate large file sizes due to redundant point clouds.     

基于BIM与知识图谱的智能化审图系统设计与实现

针对传统建筑审图存在的人工依赖性强、数据难融合共享和审查内容可视化水平低等问题,提出一种基于BIM与知识图谱的建筑智能审图方法;首先,利用知识图谱技术将繁杂的建筑规范文本数据关联为结构化知识,建立知识与数据间的语义联系;其次,鉴于BIM模型的多源异构特性,提出基于IFC的建筑数据信息提取整合,为后续建筑智能化审图实现提供数据基础;最后基于HTML5网络框架和人工智能技术设计开发了具有三维可视化、跨平台等功能的建筑智能审图系统,实现了建筑模型网页端显示及可交互操作、审图内容可视化展示、规范条文对应显示等功能;经实际建筑项目实验测试,该系统有效实现了被审建筑模型的智能化审图,并自动检测出不符合规范的建筑模型构件,一定程度上提升建筑行业智能化审图水平。     

基于 AISI 网络的 BIM 三维重建方法研究

自动从点云数据生成建筑信息模型(BIM)一直是建筑自动化领域的研究热点。基于 传统算法的建筑自动三维重建的缺点包括人工设计特征,识别过程复杂,应用场景有限等。随 着三维机器学习领域的不断成熟,处理点云便有了新的手段。通过引入实例分割中的 ASIS 网 络框架对点云进行处理,即从扫描点云场景中自动分割和分类建筑构建元素并得到实例分割矩 阵。接着,基于包围盒假设从得到的实例分割矩阵中提取建筑构件外轮廓参数,并将外轮廓参 数和分割的语义分类结果作为 BIM 建模的构件参数。最后,将这些提取的构件参数输入到自制 的 IFC 生成器中,自动生成基于工业基础类(IFC)标准的 BIM 模型。实验表明,利用无噪点点 云方法,可实现基于曼哈顿世界假设下的室内单房间的三维重建。     

Clash context representation and change component prediction based on graph convolutional network in MEP disciplines

Clash management, including clash detection and resolution, is critical for construction project success. While clash detection has been automatically conducted by Building Information Modeling (BIM) tools, the clash resolution process is still being conducted manually. This process includes predicting clash change components and determining change methods. Previous studies predict clash change components based on single clash features while ignoring the interdependency between building components and clashes. This paper proposes to use a graph convolutional network (GCN) to improve clash change component prediction by considering the interdependency nature of building components. Instead of assuming each clash is independent, the GCN model uses a component dependency graph as the input to determine whether to make changes to a particular component based on both 1) its features and 2) its impacts on related components, which is transferred through the spatial dependency structure. To further decide what kind of spatial dependency is more informative for clash change component prediction, this study compares different dependency settings. We experiment on the BIM model of a real-world project and then use the Kruskal-Wallis test to compare model accuracy in different settings. The result shows that integrating dependency information into consideration can significantly improve model prediction accuracy, and the clash relation is the most critical factor for clash change component prediction.