本文为芬兰LAB大学（作者：Kosavchenko Daria）的硕士论文，共66页。

在过去的两个世纪里，科学技术的进步在质和量上都有了很大的飞跃，它不能不影响大多数科学学科的发展、学习方法和技术。目前建筑信息建模在建筑业得到了广泛的应用。随着技术、经济和竞争的发展，逆向工程正成为研究对象结构和功能的先进方法。这种方法使用最现代的获取物体空间信息的方法，可以返回丢失或不存在的关于研究对象的综合信息。

这项工作的实质是研究基于三维扫描数据的逆向工程、创建三维模型的方法，以及使用Tekla插件实现这一过程的自动化。该开发是通过Visualstudio在C中使用Tekla Open API进行的。Tekla openapi为第三方应用程序提供了一个接口，以便与Tekla结构中的模型和绘图对象交互。在研究的结果中，确定了从人工建模到自动建模的几种点云设计方法。这项研究是自动化将点云转换为结构模型的过程的开端。总的来说，这种方法显示了BIM建模过程的改进，并将在未来的应用中发挥作用。

Over the past two centuries, scientific and technological progress has made such a large qualitative and quantitative leap that it could not but affect the development, methods and techniques of studying and learning most scientific disciplines. Now building information modeling is widely used in the construction industry. With the development of technology, economics, and competition in the world, reverse engineering is becoming an advanced method for studying objects of their structure, construction, and functioning. This method, using the most modern methods of obtaining spatial information about the object, allows returning the lost or not existing, comprehensive information about the subject of research. The essence of this work is to study reverse engineering based on threedimensional scanning data, methods for creating three-dimensional models, and automation of this process using Tekla plug-ins. The development was carried out using Tekla Open API in C# using Visual Studio. The Tekla Open API provides an interface for third-party applications to interact with model and drawing objects in Tekla Structures. In the result of the research, several methods of designing from the point cloud were identified, from manual modelling to automatic one. This study is the beginning of a path in automating the process of converting a point cloud into structural models. In general, this approach shows improvement of BIM modelling processes and will be useful in future use.

1.       引言

2. BIM建筑信息建模

3. 从点云进行建模

4. 人工BIM几何

5. 自动BIM

6. 在Tekla中自动化设计BIM几何

7. 未来发展

8. 结论

附录1 RANSAC算法描述

附录2 泊松解

附录3 Mesh Triangle类算法结构

附录4 k-NN分类算法结构

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