Multi-View Point Clouds Registration without Feature Extraction for Use in Reverse Engineering of CAD Models

For reverse engineering a CAD model, it is necessary to integrate measured points from several views of an object into a common reference frame. Given a rough initial alignment of point cloud in different views with point-normal method, further refinement is achieved by using an improved iterative closest point (ICP) algorithm. Compared with other methods used for mult-view registration, this approach is automatic because no geometric feature, such as line, plane or sphere needs to be extracted from the original point cloud manually. A good initial alignment can be acquired automatically and the registration accuracy and efficiency is proven better than the normal point-point ICP algorithm both experimentally and theoretically.

A Modified SOFM Method for Point Cloud Segmentation in Reverse Engineering

The purpose of reverse engineering is to convert a large point cloud into a CAD model. In reverse engineering, the key issue is segmentation, i.e. studying how to subdivide the point cloud into smaller regions, where each of them can be approximated by a single surface. Segmentation is relatively simple, if regions are bounded by sharp edges and small blends; problems arise when smoothly connected regions need to be separated. In this paper, a modified self-organizing feature map neural network （SOFM） is used to solve segmentation problem. Eight dimensional feature vectors （3-dimensional coordinates, 3-dimensional normal vectors, Gaussian curvature and mean curvature） are taken as input for SOFM. The weighted Euclidean distance measure is used to improve segmentation result. The method not only can deal with regions bounded by sharp edges, but also is very efficient to separating smoothly connected regions. The segmentation method using SOFM is robust to noise, and it operates directly on the point cloud. An examples is given to show the effect of SOFM algorithm.

Research on BIM Model Reshaping Method Based on 3D Point Cloud Recognition

In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.

Three-Dimensional Geometrical Modelling of Wild Boar Head by Reverse Engineering Technology

In this paper, a wild boar head was taken as the bionic research object for the development of new ridgers, a kind of plough. The reverse engineering technology was adopted to obtain the surface geometrical information of the head. Several three-dimensional （3D） point clouds of the head were captured first using a non-touch laser scanner, and an integrated point cloud was generated by aligning these point clouds using UG/Imageware. Then, the digital surface model of the head was rebuilt by means of CATIA. The characteristic curves of the surface model were analyzed. The results show that the average error between the rebuilt surface and the point cloud is -0.431 ram. The max curvature of the ridge on the neb of the head is 0.187 mm^-1, and the max and rain Gauss curvatures on the surface are 0.008 mm^-2 and -0.002 mm^-2. These geometrical information are the essential parameters for biomimetics study of the ridger.

Reverse Engineering, Some Board Games as a Key to the Development of Artificial Intelligence and Construction of Economic Models

Reverse engineering, also called back engineering, is the process of extracting knowledge or designing information from anything： mechanical device electronic components, computer programs, or biological, chemical matters, and--subsequently--analyzing its components. Reverse engineering can be applied for the sake of creating artificial intelligence, e.g. when the used methods are based on very old games, such as Go and chess. Many generations of computers are able to play at the same level as human grandmasters. A computers＇ arrival at that level is due to imitation of human Go or chess play. A particular emphasis shall be placed upon the Go game, known for 5,500 years. Invented in China, it may be classified as the oldest board game, having its ardent enthusiasts until present times. Old physical issues can be easily projected upon the modeling of new economic phenomena and quantum games. The aim of this paper is to discuss the applications of reverse engineering, traditional social games and other domains, such as quantum physics, to the analysis of utterly new social as well as economic phenomena.

Reverse Engineering Closely-Spaced Free-Form Shapes for a Fabric-Over-Body Model

This paper presents a case study of reverse engineering closely-spaced free-form shapes. The raw point cloud data captured from a body scanner was processed to filter most noise and redundancy. They were used to generate meshes through triangulation of points. Upon removal of inconsistencies resulted from residual noise, the clean-up meshes were then used to reconstruct the free-form surfaces that represented a fabric layer and a human body surface. The solid produced between these two surfaces is the fabric-over-body model. It helped generate a FEA (finite-element analysis) mesh with quality checks, such as distortion and stretch, were performed for all the meshed tetrahedral elements. The purpose is to prepare a FEA-ready model for future CFD (computational fluid dynamics) analysis.

DELAUNAY-BASED SURFACE RECONSTRUCTION ALGORITHM IN REVERSE ENGINEERING

Triangulation of scattered points is the first important section duringreverse engineering. New concepts of dynamic circle and closed point are put forward based oncurrent basic method. These new concepts can narrow the extent which triangulation process shouldseek through and optimize the triangles during producing them. Updating the searching edgesdynamically controls progress of triangulation. Intersection judgment between new triangle andproduced triangles is changed into intersection judgment between new triangle and searching edges.Examples illustrate superiorities of this new algorithm.

Aspect-oriented software reverse engineering

To solve the identification and comprehension problem of crosscutting concerns in existing legacy software system, a framework of aspect-oriented software reveme engineering is proposed. An approach on re-modularizing traversal features of legacy system is presented based on various unified modeling language （UML） diagrams. While modeling crosscutting concerns in UML use case diagrams, the non-functional requirements that affect several use case modules can be enveloped into aspect modules with a stereotype mechanism. The recurring message transmission patterns can be re-modularized as aspects in UML sequence diagrams with UML collaborations. Standard UML activity diagram notations are extended and modified by node fusion and addition, which support the graphical composition operation between crosscutting behaviors and primary business roles of concurrent systems. Case study indicates that travernal features of software system can be extracted and re-modularized from various perspectives in aspect-oriented reverse engineering, which improves comprehensibility and maintainability of legacy systems.

Reverse Engineering Based Methodology for Redesigning Contour Milling Tools

Reverse Engineering (RE) involves the use of techniques aimed to retrieve information about manufactured products, not only regarding geometries, but also materials and functionality. Today, even if several RE techniques are known, many of them still leave the object unusable to analyze. Nevertheless, other alternatives to this problem allows for obtaining a Digital or Virtual Model (VM) via the three-dimen- sional scanning. Getting the VM of an item, via scanning or not, can offer many possibilities to digital analysis (FEM). Furthermore, starting from VM, it is possible to achieve the physical reproduction of an element, part or workpiece—in the same or different materials—using Additive Manufacturing (AM) technologies. This enables to improve the product through a redesign process. In this paper, a RE based methodology is proposed for redesigning a tool for contour milling, after comparing different microscopy based techniques, 3D-Scanner tools and CAD-CAGD utilities for generating a Virtual Model of the newly designed mill.

Reconstruction of symmetric models composed of analytic curves and surfaces from point cloud

This paper presents a method to reconstruct symmetric geometric models from point cloud with inherent symmetric structure. Symmetry types commonly found in engineering parts, i.e., translational, reflectional and rotational symmetries are considered. The reconstruction problem is formulated as a constrained optimization, where the objective function is the sum of squared distances of points to the model, and constraints are enforced to keep geometric relationships in the model. First, the explicit representations of symmetric models are presented. Then, by using the concept of parameterized points (where the coor-dinate components are represented as functions rather than constants), the distances of points to symmetric models are deduced. With these distance functions, symmetry information, for both 2D and 3D models, is uniformly represented in the process of reconstruction. The constrained optimization problem is solved by a standard nonlinear optimization method. Owing to the explicit representation of symmetry information, the computational complexity of our method is reduced greatly. Finally, examples are given to demonstrate the application of the proposed method.

Reverse Engineering Activity Diagrams from Object Oriented Code： An MDA-Based Approach

The success of system modernization depends on the existence of technical frameworks for information integration and tool interoperation like the Model Driven Architecture （MDA）. Reverse engineering techniques play a crucial role in system modernization. This paper describes how to reverse engineering activity diagrams from object oriented code in the MDA context focusing on transformations at model and metamodel levels. A framework to reverse engineering MDA models from object oriented code that distinguishes three different abstraction levels linked to models, metamodels and formal specifications, is described. At model level, transformations are based on static and dynamic analysis. At metamodel level, transformations are specified as 0CL （Object Constraint Language） contracts between M0F （Meta Object Facility） metamodels which control the consistency of these transformations. The level of formal specification includes algebraic specifications of MOF metamodels and metamodel-based transformations. This paper analyzes a recovery process of activity diagrams from Java code by applying static and dynamic analysis and shows a formalization of this process in terms of MOF metamodels. The authors validate their approach by using Eclipse Modeling Framework, Ecore metamodels and ATL （Atlas Transformation Language）.

ALGORITHM OF PRETREATMENT ON AUTOMOBILE BODY POINT CLOUD

As point cloud of one whole vehicle body has the traits of large geometric dimension, huge data and rigorous reverse precision, one pretreatment algorithm on automobile body point cloud is put forward. The basic idea of the registration algorithm based on the skeleton points is to construct the skeleton points of the whole vehicle model and the mark points of the separate point cloud, to search the mapped relationship between skeleton points and mark points using congruence triangle method and to match the whole vehicle point cloud using the improved iterative closed point （ICP） algorithm. The data reduction algorithm, based on average square root of distance, condenses data by three steps, computing datasets＇ average square root of distance in sampling cube grid, sorting order according to the value computed from the first step, choosing sampling percentage. The accuracy of the two algorithms above is proved by a registration and reduction example of whole vehicle point cloud of a certain light truck.

FeatureMatching Combining Variable Velocity Model with Reverse Optical Flow

The ORB-SLAM2 based on the constant velocity model is difficult to determine the search window of the reprojection of map points when the objects are in variable velocity motion,which leads to a false matching,with an inaccurate pose estimation or failed tracking.To address the challenge above,a new method of feature point matching is proposed in this paper,which combines the variable velocity model with the reverse optical flow method.First,the constant velocity model is extended to a new variable velocity model,and the expanded variable velocity model is used to provide the initial pixel shifting for the reverse optical flow method.Then the search range of feature points is accurately determined according to the results of the reverse optical flow method,thereby improving the accuracy and reliability of feature matching,with strengthened interframe tracking effects.Finally,we tested on TUM data set based on the RGB-D camera.Experimental results show that this method can reduce the probability of tracking failure and improve localization accuracy on SLAM(Simultaneous Localization and Mapping)systems.Compared with the traditional ORB-SLAM2,the test error of this method on each sequence in the TUM data set is significantly reduced,and the root mean square error is only 63.8%of the original system under the optimal condition.

Personalized Cranium Defects Restoration Technique Based on Reverse Engineering

The purpose of this paper is to overcome the limitations of the traditional cranial defects restoration technique and better satisfy the aesthetic and comfort demands of different patients. An arithmetic profile curve blending technique was used based on a well-proportioned points cloud data obtained by analyzing computer tomography (CT) images of the patients. This technique uses reverse engineering technique to reconstruct a model of the defective cranium, taking all the characteristics of the protruding cranium into consideration to check the form and appropriateness of the restoration and to adjust the surface in real time to obtain the ideal shape. Then, the model is transferred to a multiple-point forming (MPF) pressure machine to produce a titanium alloy restoration model. The system has greater flexibility, shorter production cycles, and lower cost through the use of digital production technology, guarantees the quality of the cranial defects restoration model, reduces the surgical risks, and alleviates the patients’ pain. In addition, an improved contour curved bridge algorithm technique is used to repair any cranium defects on the contour curve to make the contour more complete and closed.

Triangular Mesh Model Reconstruction from Scan Point Clouds Based on Template

For mesh reconstruction problems of point cloud models which have similar topological structure, a rapid and efficient method is presented to reconstruct triangular mesh surface. Based on projections of point cloud slicing that correspond to template sectional curves, the method constructs topological relevant information among discrete points, which makes unorganized points ordering and builds up optimal approximated B-spline curve, resamples every curve according to its curvature distribution and performes triangular mesh division on it. Finally, surface reconstruction is achieved. The experimental results demonstrate that the surface reconstruction is done as the point cloud hole is filled simultaneously.

REVERSE MODELING FOR CONIC BLENDING FEATURE

A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.

MODEL RECONSTRUCTION FROM CLOUD DATA FOR RAPID PROTOTYPE MANUFACTURING

Model reconstruction from points scanned on existing physical objects is much important in a variety of situations such as reverse engineering for mechanical products, computer vision and recovery of biological shapes from two dimensional contours. With the development of measuring equipment, cloud points that contain more details of the object can be obtained conveniently. On the other hand, large quantity of sampled points brings difficulties to model reconstruction method. This paper first presents an algorithm to automatically reduce the number of cloud points under given tolerance. Triangle mesh surface from the simplified data set is reconstructed by the marching cubes algorithm. For various reasons, reconstructed mesh usually contains unwanted holes. An approach to create new triangles is proposed with optimized shape for covering the unexpected holes in triangle meshes. After hole filling, watertight triangle mesh can be directly output in STL format, which is widely used in rapid prototype manufacturing. Practical examples are included to demonstrate the method.

A Reverse-Design Strategy for the Track Error of the Qi Tai Telescope Based on Pointing Accuracy

The Qi Tai Telescope(QTT),which has a 110 m aperture,is planned to be the largest scale steerable tele-scope in the world.Ideally,the telescope’s repeated pointing accuracy error should be less than 2.5 arc seconds(arcsec);thus,the telescope structure must satisfy ultra-high precision requirements.In this pur-suit,the present research envisages a reverse-design method for the track surface to reduce the difficulty of the telescope’s design and manufacture.First,the distribution characteristics of the test data for the track error were verified using the skewness coefficient and kurtosis coefficient methods.According to the distribution characteristics,the azimuth track error was simulated by a two-scale model.The error of the long period and short amplitude was characterized as large-scale and described by a trigonometric function,while the short period and high amplitude error was characterized as small-scale and simulated by a fractal function.Based on the two-scale model,effect of the error on the pointing accuracy was deduced.Subsequently,the relationship between the root mean square(RMS)of the track error and the RMS of the pointing accuracy error of the telescope was deduced.Finally,the allowable RMS value of the track error was derived from the allowable pointing accuracy errors.To validate the effectiveness of the new design method,two typical radio telescopes(the Green Bank Telescope(GBT)and the Large Millimeter Telescope(LMT))were selected as experimental examples.Through comparison,the theoretical calculated values of the pointing accuracy of the telescope were consistent with the measured values,with a maximum error of less than 10%.

AN ENGINEERING MODEL FOR MULTICOMPONENT REVERSIBLE REACTION NETWORK

The treatment of a multicomponent reversible reaction network is extremely complicated because largenumber of rate constants must be precisely determined and because the calculation based on these rateconstants is tedious.In order to reduce the degrees of freedom of the process,the authors propose a methodin which the reactor and the separator are regarded as a whole.Based on this approach,an N-componentreversible reaction system can be dealt with as a two—component system.Consequently,a simple and ac-cessible way of the apparent rate determination is suggested.For fiist-order reactions,an explicit,simplifiedexpression has been derived for both lumped and distributed parameter reaction systems.

基于特征匹配的逆向工程模型重建方法

逆向工程(RE)也称反求工程,以实物、样件、软件(包括图样、程序、技术文件等)或影像(图片、照片等)为对象,应用产品设计方法学、系统工程学、计算机辅助技术方法进行系统分析和研究,探索掌握其关键技术,进而开发出同类或更先进产品。从数据采集、数据处理和模型构建3个阶段给出了RE中的模型重建过程。首先基于特征的点云匹配方法进行数据采集,获取物体表面的点云数据,然后采取降噪、平滑等方式进行预处理,最后通过曲面拟合、曲面特征提取和数据拼接完成实物到模型的建模。同时给出了各阶段的通用方法和实际应用的注意事项。RE可快速准确地确定实物的结构特点、内部构造等信息,并为后续设计提供参考。