Automated continuous construction progress monitoring using multiple workplace real time 3D scans

In recent years, exponential growth has been detected in research efforts focused on automated construction progress monitoring. Despite various data acquisition methods and approaches, the success is limited. This paper proposes a new method, where changes are constantly perceived and as-built model continuously updated during the construction process, instead of periodical scanning of the whole building under construction. It turned out that low precision 3D scanning devices, which are closely observing active workplaces, are sufficient for correct identification of the built elements. Such scanning devices are small enough to fit onto workers’ protective helmets and on the applied machinery. In this way, workers capture all workplaces inside and outside of the building in real time and record partial point clouds, their locations, and time stamps. The partial point clouds are then registered and merged into a complete 4D as-built point cloud of a building under construction. Identification of as-designed BIM elements within the 4D as-built point cloud then results in the 4D as-built BIM. Finally, the comparison of the 4D as-built BIM and the 4D as-designed BIM enables identification of the differences between both models and thus the deviations from the time schedule. The differences are reported in virtual real-time, which enables more efficient project management.     

基于BIM的钢筋骨架语义设计点云自动生成算法

当前预制构配件钢筋骨架质量检查主要依靠人工,存在效率低、容易出错的问题。建筑信息模 型(BIM)、三维重建等技术为改进预制构配件钢筋骨架质量检查方法提供可能。运用这些技术时,有必要由钢 筋骨架 BIM 模型生成可区分每根钢筋的点云。为此,提出了语义设计点云的概念,并构建了基于 BIM 的钢筋 骨架语义设计点云自动生成算法。该算法首先从钢筋骨架 BIM 模型中提取每根钢筋并分别存储于不同的文件, 然后对每根钢筋所在文件进行格式转换,接着生成每根钢筋的语义设计点云,最后基于每根钢筋的语义设计点 云生成钢筋骨架语义设计点云。分别用简单钢筋骨架和复杂钢筋骨架对基于 BIM 的钢筋骨架语义设计点云自 动生成算法进行实验验证,结果表明,该算法能够自动并快速地生成准确的钢筋骨架语义设计点云。      

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.     

Developing final as-built BIM model management system for owners during project closeout: A case study

To apply final as-built BIM models to facility management (FM) during the operation phase, it is important for owners to obtain an accurate, final as-built model from the general contractors (GCs) following project closeout. Confirming the accuracy of the final as-built BIM model is one of the most important works executed by owners to meet the accuracy requirement of final as-built models for FM. However, many practical problems arise relating to the management of final as-built models such as final as-built model mismatch, the lack of available final as-built models, and the entry of incorrect non-geometric information into the final as-built models. To solve these practical problems, this study develops a Final As-built BIM Model Management (FABMM) system for owners to handle final as-built BIM model inspection, modification, and confirmation (BMIMC) work beyond project closeout. The proposed approach and system can be used to manage the status and results of BMIMC management work for the final as-built BIM model to be performed. The proposed approach and system were applied in a case study in a selected building in Taiwan to verify and demonstrate its practical effectiveness. This study identifies the benefits, limitations, and conclusions of the FABMM system, and presents suggestions for its further application.     

A cloud approach to unified lifecycle data management in architecture,engineering, construction and facilities management: Integrating BIMs and SNS

The problem of data integration throughout the lifecycle of a construction project among multiple collaborative enterprises remains unsolved due to the dynamics and fragmented nature of the construction industry. This study presents a novel cloud approach that, focusing on China’s special construction requirements, proposes a series of as-built BIM (building information modeling) tools and a self-organised application model that correlates project engineering data and project management data through a seamless BIM and BSNS (business social networking services) federation. To achieve a logically centralised single-source data structure, a unified data model is constructed that integrates two categories of heterogeneous databases through the adoption of handlers. Based on these models, key technical mechanisms that are critical to the successful management of large amounts of data are proposed and implemented, including permission, data manipulation and file version control. Specifically, a dynamic Generalised List series is proposed to address the sophisticated construction file versioning issue. The proposed cloud has been successfully used in real applications in China. This research work can enable data sharing not only by individuals and project teams but also by enterprises in a consistent and sustainable way throughout the life of a construction project. This system will reduce costs for construction firms by providing effective and efficient means and guides to complex project management, and by facilitating the conversion of project data into enterprise-owned properties.     

Plane-based registration of construction laser scans with 3D/4D building models

With the development of building information modelling (BIM) and terrestrial laser scanning (TLS) in the architecture, engineering, construction and facility management (AEC/FM) industry, the registration of site laser scans and project 3D (BIM) models in a common coordinate system is becoming critical to effective project control. The co-registration of 3D datasets is normally performed in two steps: coarse registration followed by fine registration. Focusing on the coarse registration, model-scan registration has been well investigated in the past, but it is shown in this article that the context of the AEC/FM industry presents specific (1) constraints that make fully-automated registration very complex and often ill-posed, and (2) advantages that can be leveraged to develop simpler yet effective registration methods.This paper thus presents a novel semi-automated plane-based registration system for coarse registration of laser scanned 3D point clouds with project 3D models in the context of the AEC/FM industry. The system is based on the extraction of planes from the laser scanned point cloud and project 3D/4D model. Planes are automatically extracted from the 3D/4D model. For the point cloud data, two methods are investigated. The first one is fully automated, and the second is a semi-automated but effective one-click RANSAC-supported extraction method. In both cases, planes are then manually but intuitively matched by the user. Experiments, which compare the proposed system to software packages commonly used in the AEC/FM industry, demonstrate that at least as good registration quality can be achieved by the proposed system, in a simpler and faster way. It is concluded that, in the AEC/FM context, the proposed plane-based registration system is a compelling alternative to standard point-based registration techniques.     

基于云技术的 BIM 架构研究与实践综述

随着建筑信息模型(BIM)在建筑全生命期中得到越来越广泛的应用,建筑工程项目 的复杂性日益增长,相应的数据量也呈爆炸性增长,如何高效地支持 BIM 应用成为建筑行业面 临的重大挑战。云计算和大数据技术,尽管出现时间不长,但是已被广泛地认为能较为有效地 解决 BIM 应用面临的诸多问题,已经在学术和工业界得到了快速的接纳。为此,梳理了现有的 基于云技术的 BIM (“Cloud-BIM”)文献与实践,将现有的 Cloud-BIM 应用架构主要归纳为 3 个 层次： ､ 数据层 服务层和应用层,并针对 3 个层次上的现有研究与实践分别进行探讨和阐述, 指出不同层次上的主要研究进展和应用障碍。最后总结并展望 Cloud-BIM 架构研究与实践的热 门领域、亟待解决的问题和可能的方向,为进一步开展此研究和应用提供参考。     

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。     

Towards automatic generation of as-built BIM: 3D building facade modeling and material recognition from images

As-built building information model(BIM) is an urgent need of the architecture, engineering, construction and facilities management(AEC/FM) community. However, its creation procedure is still labor-intensive and far from maturity. Taking advantage of prevalence of digital cameras and the development of advanced computer vision technology, the paper proposes to reconstruct a building facade and recognize its surface materials from images taken from various points of view. These can serve as initial steps towards automatic generation of as-built BIM. Specifically, 3D point clouds are generated from multiple images using structure from motion method and then segmented into planar components, which are further recognized as different structural components through knowledge based reasoning. Windows are detected through a multilayered complementary strategy by combining detection results from every semantic layer. A novel machine learning based 3D material recognition strategy is presented. Binary classifiers are trained through support vector machines. Material type at a given 3D location is predicted by all its corresponding 2D feature points.Experimental results from three existing buildings validate the proposed system.     

Cloud-to-BIM-to-FEM: Structural simulation with accurate historic BIM from laser scans

The complexity of historic constructions, with irregular geometry, inhomogeneous materials, variable morphology, alterations and damages, poses numerous challenges in the digital modeling and simulation of structural performances under different types of actions. Although recent developments in Building Information Modeling have introduced advanced simulation capabilities, the numerical characterization of historic buildings is still a challenging task for the lack of reliable procedures for structural simulation.This paper presents an innovative two-step methodology (Cloud-to-BIM-to-FEM) able to convert a historic BIM into a finite element model for structural simulation. The generation of the BIM (Cloud-to-BIM) is carried out with an accurate survey that integrates geometrical aspects, diagnostic analysis based on destructive and non-destructive inspections, material information, element interconnections, and architectural and structural considerations. The BIM is then turned into a finite element model (BIM-to-FEM) with a geometric rationalization which preserves irregularities and anomalies, such as verticality deviation and variable thickness. After setting material properties, loads, and boundary conditions, the structural simulation is run with a detailed model that respects the uniqueness and authenticity of the historic building, without the typical excessive geometric simplifications of the shape.A real case study is illustrated and discussed to prove that a rigorous Cloud-to-BIM-to-FEM workflow allows the generation of an accurate historic BIM from a set of laser scanning point clouds. Structural simulation was carried out with a 3D mesh derived from the BIM in order to take into consideration the geometrical irregularity of a castle. Here, the advantages and disadvantages of the proposed approach are illustrated and discussed.     

BIM技术在古建筑保护中的应用研究

传统测绘方法获取的二维图纸难以满足现有古建筑修缮和保护的要求,本文采用三维激光扫描技术与BIM结合,通过对点云数据的处理可以高效的建立高精度的古建筑三维立体模型,使古建筑三维模型结构化及数据信息化,便于古建筑的数字化存档,为古建筑的修缮和保护提供数据支持。     

Extracting structural components of concrete buildings from laser scanning point clouds from construction sites

In construction projects, inspection of structural components mostly relies on classical measurements obtained by measuring tapes, levelling, or total stations. With those methods, only a few points on the structure can be measured, and the resulting inspection may not fully reflect the actual, detailed condition of the complete object. Laser scanning is an emerging remote sensing technology to accurately and quickly capture surfaces of structures in high details. However, because of the complex, massive point cloud data acquired at a construction project, in practice, data processing is still manual work with computer aided programs. To improve upon current workflows, this paper proposes a method to automatically extract point clouds of individual surfaces of structural components of a concrete building, which subsequently can be used to inspect construction quality based on geometric information of the surfaces. The proposed method explores both spatial point cloud information and contextual knowledge of structures (e.g., orientation or shape) derived from building design specifications and practice. For extracting point clouds of surfaces of each structural component, the proposed method consists of 4 consecutive steps for extracting: (1) floors, ceiling slabs, and walls, (2) columns, and (3) primary and (4) secondary beams. Each step consists of two ingredients: (i) rough extracting the candidate points of the component and (ii) fine filtering of the surface points of the components via cell-based and voxel-based region growing segmentation (CRG and VRG) incorporating contextual knowledge of the structural members. Experimental tests on two different types of concrete buildings showed that the proposed method successfully extracts the structural elements, in which the completeness, correctness, and quality from the point-based evaluation are larger than 96.0%, 96.9%, and 92.0%, respectively. Moreover, the evaluation based on a shape similarity showed that the extracted floor, ceiling slab and wall overlap to the ground truth more than 92.5%.     

Continuous global optimization in surface reconstruction from an oriented point cloud

We introduce a continuous global optimization method to the field of surface reconstruction from discrete noisy cloud of points with weak information on orientation. The proposed method uses an energy functional combining flux-based data-fit measures and a regularization term. A continuous convex relaxation scheme assures the global minima of the geometric surface functional. The reconstructed surface is implicitly represented by the binary segmentation of vertices of a 3D uniform grid and a triangulated surface can be obtained by extracting an appropriate isosurface. Unlike the discrete graph-cut solution, the continuous global optimization entails advantages like memory requirements, reduction of metrication errors for geometric quantities, and allowing globally optimal surface reconstruction at higher grid resolutions. We demonstrate the performance of the proposed method on several oriented point clouds captured by laser scanners. Experimental results confirm that our approach is robust to noise, large holes and non-uniform sampling density under the condition of very coarse orientation information.     

BIM 空间关系数据的云存储与检索方法研究

随着工程项目体量的增大,模型中存在的空间关系更加复杂多样化,现有的建筑 信息模型(BIM)数据存储和检索方式无法满足使用要求。为了提高 BIM 中大量空间关系数据的 存储和检索效率,通过集成 BIM 与云计算技术,提出了一种 BIM 分布式负载均衡集群方案, 在此基础上利用弹性搜索框架(Elastic Search)和图数据库Neo4j实现了IFC空间关系数据的云存 储和检索,为海量 BIM 空间关系数据提供一种高效快速的云存储和检索方法。     

空地融合的城市道路基础设施数字化技术研究

城市道路基础设施三维模型的重构,在城市道路BIM应用与数字化领域具有重大意义;针对城市交通基础设施数字化重构的需求,对车载激光扫描与无人机倾斜摄影采集技术进行综合运用,提出一套从信息采集、空地点云配准、点云分割到三维重构的完整技术方法;首先使用车载激光扫描技术和无人机倾斜摄影技术对交通基础设施信息进行采集,并使用运动恢复结构算法(SfM,structure from motion)生成基础设施空地点云;其次使用迭代最近点法(ICP,iterative closest point)对空地点云进行精配准,然后利用基于PointNet网络的方法对融合点云进行语义分割;最后对分割出的交通基础设施对象进行三维重构;提出的空地融合的城市交通基础设施数字化技术能够高效地实现交通基础设施重构,为城市交通基础设施数字化提供基础、为后续交通专业领域的应用研究提供便利.     

BIM 与云、大数据、物联网等技术的 集成应用现状与未来

近年来,云计算、大数据、物联网等技术不断涌现,并与建设工程中建筑信息模 型(BIM)技术的应用不断融合,越来越受到研究人员的关注。然而,这些技术尚未形成面向建 设项目的统一集成应用框架。通过广泛的文献调研发现,云、大数据、物联网与 BIM 技术缺一 不可,只有将其充分集成才能共同发挥价值,服务建设项目建设、管理。在此基础上,研究建 立了各项技术的统一集成应用框架。同时,从理论和应用两方面对有关技术与 BIM 技术集成的 研究与应用现状进行了综述,梳理了各项关键技术及软件系统研发现状,对已有工程应用进行 了总结。最后,对研究中存在的瓶颈与挑战进行了分析,指出未来仍需在基础理论方法、多技 术融合等方面开展深入研究。     

基于BIM技术的建筑建模与成本控制

本论文根据潍坊市寒亭区农村住宅F9C住宅楼,建筑面积195.5 m2,使用面积169.7 m2,根据住宅图纸建立模型、通过建筑建模解决问题、运用BIM建模发现的问题。建立模型当中屋顶的绘制和玻璃斜板的绘制是难点,出于图纸设计和整体美观的考虑,改变部分墙体、楼板和玻璃斜板的坡度,使屋顶更加美观,优化了玻璃斜板的施工方法。由于BIM建模处于施工阶段的前一项工作,能够全面地体现整体建筑,做好数据信息和几何信息的控制,同时可以监控施工中工程信息的变化的同时更改信息实时记录,弥补了传统成本控制中事前控制和事中控制的缺失,不仅对图纸设计进行改良避免了施工过程的损失,还对工期和质量的控制保障有所提高。对于BIM这个新兴产品,在国内没有被广泛的接受,原因不单单包括大部分人对BIM的陌生和只有少数人拥有BIM技术,还包括计算机技术的提升和投资方不愿意对该业务资金的投入,BIM在国内发展缓慢。经过时间累计,BIM对工程成本控制的优点会被越来越多的人看到,也将会带动建筑业的发展。     

Scan-to-BIM for ‘secondary’ building components

Works dealing with Scan-to-BIM have, to date, principally focused on 'structural' components such as floors, ceilings and walls (with doors and windows). But the control of new facilities and the production of their corresponding as-is BIM models requires the identification and inspection of numerous other building components and objects, e.g. MEP components, such as plugs, switches, ducts, and signs. In this paper, we present a new 6D-based (XYZ + RGB) approach that processes dense coloured 3D points provided by terrestrial laser scanners in order to recognize the aforementioned smaller objects that are commonly located on walls. This paper focuses on the recognition of objects such as sockets, switches, signs, extinguishers and others. After segmenting the point clouds corresponding to the walls of a building, a set of candidate objects are detected independently in the colour and geometric spaces, and an original consensus procedure integrates both results in order to infer recognition. Finally, the recognized object is positioned and inserted in the as-is semantically-rich 3D model, or BIM model. The assessment of the method has been carried out in simulated scenarios under virtual scanning providing high recognition rates and precise positioning results. Experimental tests in real indoors using our MoPAD (Mobile Platform for Autonomous Digitization) platform have also yielded promising results.     

基于BIM+Cesium三维可视化校园系统的设计与实现

构建具备“三维可视化”、“信息化”、“数字化”特征的校园平台是智慧校园建设的基础点,现有校园平台大多使用传统建模工具融合C/S架构的GIS平台搭建,缺乏模型信息统一整合、趋于平面化且可视化水平较低、不具备跨平台等问题;BIM技术因其数据整合模式有效提高了建筑业信息化水平,文章结合BIM技术二三维信息整合及WebGIS-Cesium框架免插件、可跨平台的优点,以本校作为建模原型借助Revit软件建模及二次开发、文件流等技术,基于B/S架构开发兼备可视化、信息化及跨平台能力的校园平台,实现了地图显示模块、建筑物信息查询模块、空间GIS模块、地物对应查询模块及其子功能;通过测试,设计的系统工作可靠可行,满足校园平台需求。     

基于层次分析法的BIM 内容库网站评价研究

随着计算机信息技术在建筑行业的应用不断普及,建筑信息模型(BIM)已经成为建 筑行业先进且实用的技术,在工程建设领域发挥着重要的作用。BIM 内容库是用来对建筑信息 模型中的构件进行存储和管理的数据系统,是为构建工程设施的BIM 模型提供最底层的构件资 源支撑。国内外现有的BIM 内容库普遍存在构件组织混乱、资源利用率低下的问题,学术界对 BIM 内容库的组织和利用的相关研究也很匮乏。通过对BIM 内容库相关网站进行了调查,运用 层次分析法对BIM 内容库网站进行评价研究,建立BIM 内容库网站的评价标准,寻找出最优 的BIM 内容库组织结构,为BIM 内容库网站建设提供理论基础和应用指导。