A referential scheme for modeling and identifying spatial attributes of entities in constructed facilities

This paper presents a referential scheme for representing and identifying the spatial extent of physical entities of constructed facilities, such as buildings and offshore structures. Using the basic operations of a non-manifold geometric modeler, a set of high-level algebraic operations is defined. The scheme and its algebra are used for modeling the spatial attributes of a facility entity at two levels: primary and secondary. The primary representation uniquely captures an entity's spatial attributes at the skeletal level and is used mainly for identifying discipline-independent topological relationships of that entity with others. Secondary representations, on the other hand, are used to provide an entity's discipline-specific geometric attributes. The topological relationships and geometric attributes of facility entities thus need not be explicitly stored, but can be computed on demand by the underlying non-manifold modeler.     

锻压机液压缸计算机辅助变结构设计系统

本文分析了目前液压缸设计方法的不足,提出了一种开发ＣＡＤ软件的新方法－计算机辅助变结构设计方法,同时综合一体化设计、智能化设计和用户化设计方法,以液压缸设计为对象,研究开发了应用软件“锻压机液压缸计算机辅助变结构设计系统”。该软件产品已交付厂方使用,反应良好。     

AR-based deep learning for real-time inspection of cable brackets in aircraft

In the process of aircraft assembly, there exist numerous and ubiquitous cable brackets that shall be installed on frames and subsequently need to be manually verified with CAD models. Such a task is usually performed by special operators, hence is time-consuming, labor-intensive, and error-prone. In order to save the inspection time and increase the reliability of results, many researchers attempt to develop intelligent inspection systems using robotic, AR, or AI technologies. However, there is no comprehensive method to achieve enough portability, intelligence, efficiency, and accuracy while providing intuitive task assistance for inspectors in real time. In this paper, a combined AR+AI system is introduced to assist brackets inspection in a more intelligent yet efficient manner. Especially, AR-based Mask R-CNN is proposed by skillfully integrating markerless AR into deep learning-based instance segmentation to generate more accurate and fewer region proposals, and thus alleviates the computation load of the deep learning program. Based on this, brackets segmentation can be performed robustly and efficiently on mobile devices such as smartphones or tablets. By using the proposed system, CAD model checking can be automatically performed between the segmented physical brackets and the corresponding virtual brackets rendered by AR in real time. Furthermore, the inspection results can be directly projected on the corresponding physical brackets for the convenience of maintenance. To verify the feasibility of the proposed method, experiments are carried out on a full-scale mock-up of C919 aircraft main landing gear cabin. The experimental results indicate that the inspection accuracy is up to 97.1%. Finally, the system has been deployed in the real C919 aircraft final-assembly workshop. The preliminary evaluation reveals that the proposed real-time AR-assisted intelligent inspection approach is effective and promising for large-scale industrial applications.     

Improving robustness of industrial object detection by automatic generation of synthetic images from CAD models

Object detection (OD) is used for visual quality control in factories. Images that compose training datasets are often collected directly from the production line and labeled with bounding boxes manually. Such data represent well the inference context but might lack diversity, implying a risk of overfitting. To address this issue, we propose a dataset construction method based on an automated pipeline, which receives a CAD model of an object and returns a set of realistic synthetic labeled images (code publicly available). Our approach can be easily used by non-expert users and is relevant for industrial applications, where CAD models are widely available. We performed experiments to compare the use of datasets obtained by the two different ways—collecting and labeling real images or applying the proposed automated pipeline—in the classification of five different industrial parts. To ensure that both approaches can be used without deep learning expertise, all training parameters were kept fixed during these experiments. In our results, both methods were successful for some objects but failed for others. However, we have shown that the combined use of real and synthetic images led to better results. This finding has the potential to make industrial OD models more robust to poor data collection and labeling errors, without increasing the difficulty of the training process.     

A marker-less assembly stage recognition method based on corner feature

Fast and robust product assembly stage recognition is a key step in human–machine cooperative assembly. To solve the recognition problem of similar adjacent assembly stages, a marker-less assembly stage recognition method is proposed based on corner feature between an assembling product and a digital model. Considering the geometric features of mechanical products, a corner identification method is proposed based on the circumferential angle difference (CADF). Then a corner matching method based on distance constraint is studied for ICP registration to realize the point cloud registration between the product and digital model. Based on the registration relationship, a similarity algorithm based on proximity point proportion is used to calculate the similarity between models and the input assembling product. The model with the greatest similarity is taken as the stage recognition result. In experiments on four group assembling products, the average stage recognition accuracy is 96.15%, which indicates that the proposed method can solve the stage recognition problem. The corner identification method based on the CADF outperforms the Harris-3D corner detection method in the efficiency of assembly stage recognition.     

A distortion measure to validate and generate curved high‐order meshes on CAD surfaces with independence of parameterization

A framework to validate and generate curved nodal high‐order meshes on Computer‐Aided Design (CAD) surfaces is presented. The proposed framework is of major interest to generate meshes suitable for thin‐shell and 3D finite element analysis with unstructured high‐order methods. First, we define a distortion (quality) measure for high‐order meshes on parameterized surfaces that we prove to be independent of the surface parameterization. Second, we derive a smoothing and untangling procedure based on the minimization of a regularization of the proposed distortion measure. The minimization is performed in terms of the parametric coordinates of the nodes to enforce that the nodes slide on the surfaces. Moreover, the proposed algorithm repairs invalid curved meshes (untangling), deals with arbitrary polynomial degrees (high‐order), and handles with low‐quality CAD parameterizations (independence of parameterization). Third, we use the optimization procedure to generate curved nodal high‐order surface meshes by means of an a posteriori approach. Given a linear mesh, we increase the polynomial degree of the elements, curve them to match the geometry, and optimize the location of the nodes to ensure mesh validity. Finally, we present several examples to demonstrate the features of the optimization procedure, and to illustrate the surface mesh generation process. Copyright © 2015 John Wiley & Sons, Ltd.     

基于FME的CAD与GIS数据转换研究

将地图数据转变为GIS数据的本质在于把CAD数据转变为GIS数据,CAD软件属于常用的作图软件,与GIS软件相比,两者在管理特征、储存数据、定义图元等方面都存在一定的差异。受到多种内外部因素的影响,当前仍缺乏统一空间的数据参考标准,导致CAD信息在转化为GIS信息的过程中仍存在多种质量问题。研究人员应从此方面入手,不断发展GIS技术。本文从FME的角度出发,重点探究CAD与GIS数据转换方式。     

国产服装CAD的应用推广探析

分析了我国服装ＣＡＤ应用的现状,探讨了服装ＣＡＤ在我国应用的市场潜力和应用前景,并针对当前存在的主要问题,提出了国产服装ＣＡＤ的应用推广策略     

CAD/CAM系统中进度管理解决方案的研究及应用

提出了在ＣＡＤ／ＣＡＭ系统中的进度管理问题的解决方案,论述了进度管理系统的数据结构、系统构成和在设计时需注意的问题,并介绍了该方案在日本新泻铁工所横滨工厂热交换器ＣＡＤ／ＣＡＭ系统上的应用情况。     

可视化供配电CAD系统的研究开发

基于科学可视化,对象建模,面向对象的软件开发技术,在解决了图形系统快速开发的几个关键技术,对象关联实现方法及电网中电气元件潜在拓扑描述等问题的基础上,开发了功能较烷 备的实用化供配电ＣＡＤ及管理系统软件。同时,通过开放数据库互联技术实现了图形系统、计算接口与数据管理系统的集成,解决了动态扩充功能,对开发专业领域ＣＡＤ软件具有借鉴作用。