This paper aims at developing a Historical Building Information Modelling methodology for supporting the diagnosis phase in historical constructions. To this end, the work evaluates the capacity of HBIM for integrating all the data generated during the pre-diagnosis and previous tests, including the data coming from point cloud clustering methods. According to this, we propose different families with low Level of Detail (LoD) and high Level of Information (LoI), including strategies for integrating the data of point cloud clustering methods. This proposal is applied to a case study in the Fortress of Almeida (Portugal), demonstrating the viability of the approach for the diagnosis of historical constructions. Future works will be focused on improving the integration of the 3D point clouds features by using convex-hull methods as well as integrating the results of clustering approaches based on artificial intelligence.

本文旨在开发一种历史建筑信息建模方法，以支持历史建筑的诊断阶段。为此，该工作评估了 HBIM 整合预诊断和先前测试期间生成的所有数据的能力，包括来自点云聚类方法的数据。据此，我们提出了具有低细节水平（LoD）和高信息水平（LoI）的不同系列，包括整合点云聚类方法数据的策略。该建议应用于阿尔梅达堡垒（葡萄牙）的案例研究，证明了诊断历史建筑的方法的可行性。