2023, 15(6): 32-38. doi: 10.16670/j.cnki.cn11-5823/tu.2023.06.06
基于本体的建筑工程质量隐患信息知识建模
| 1. | 华中科技大学 土木与水利工程学院, 湖北 武汉 430074 |
| 2. | 中国铁道科学研究院集团有限公司电子计算技术研究所 北京 100081 |
Ontology-based Knowledge Modeling of Quality Hazard Information in Construction Projects
| 1. | Huazhong University of Science and Technology, School of Civil and Hydraulic Engineering, Wuhan 430074, China |
| 2. | Institute of Computing Technologies, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China |
引用本文:
钟雪妍, 沈罗昕, 潘杏, 向然, 郝蕊, 钟波涛. 基于本体的建筑工程质量隐患信息知识建模[J]. 土木建筑工程信息技术,
2023, 15(6): 32-38.
doi: 10.16670/j.cnki.cn11-5823/tu.2023.06.06
Citation:
Xueyan Zhong, Luoxin Shen, Xing Pan, Ran Xiang, Lei Hao, Botao Zhang. Ontology-based Knowledge Modeling of Quality Hazard Information in Construction Projects[J]. Journal of Information Technologyin Civil Engineering and Architecture,
2023, 15(6): 32-38.
doi: 10.16670/j.cnki.cn11-5823/tu.2023.06.06
摘要:在传统的项目管理模式中，工程人员都是通过核对监理单位提供的质量隐患整改单中的质量问题信息和建筑工程施工质量验收规范，来确定项目工程施工质量是否达标。为了提高工程信息审查效率，本文提出了一种基于本体的建筑工程质量隐患整改单信息审查知识模型。研究过程主要分为四步：第一，分析建筑工程施工质量验收规范中的词义元素和语义表达；第二，分析质量隐患整改单中的质量问题信息并建立知识模板和语义信息图；第三，参考已有的建筑工程质量验收规范知识模型，建立QII-QHDRFOntology知识模型；第四，完成建模后，将该模型应用于实际案例以验证其可行性和有效性。验证结果表明，本文建立的QII-QHDRFOntology知识模型能够成功审查实际工程质量隐患整改单中的质量问题信息。
Abstract: Construction quality management methods need to be improved as the construction industry develops and the scale of construction expands. The traditional quality review involves manually checking the quality issues in the quality rectification forms provided by the supervisors and the codes of construction quality acceptance, which determines whether the construction quality is qualified. However, the traditional method is not only time-consuming and labor-intensive, but also may lead to errors that affect quality control and decision-making. To avoid the above issues by automatic quality review, this paper proposes an ontology-based knowledge model for reviewing information in construction quality hid danger rectification forms. The modeling process comprises four steps: (1) analyzing the lexical elements and semantic relationships in the codes for acceptance of construction quality; (2) establishing knowledge templates and semantic relationship graphs of the quality issues information in quality hid danger rectification form; (3) referring to the existing knowledge model and establishing the QII-QHDRFOntology knowledge model; (4) applying the model to actual cases to evaluate its feasibility and effectiveness. The evaluation results in this paper indicate that the proposed QII-QHDRFOntology knowledge model can effectively review the quality issue information in actual construction quality hazard rectification forms.
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