Research on ontology-based construction risk knowledge base development in deep foundation pit excavation

Abstract

Facing the massive amount of risk management data for deep foundation pit excavation (DFPE) construction, how to store and utilize these data to prevent the occurrence of risk events is an urgent problem that needs to be solved. The goal of this research is to build an ontology knowledge base aimed at standardizing and formalizing risk knowledge in the field of DFPE construction risk. The ontology knowledge base can promote construction risk identification and reduce the occurrence of risk events. A six-step method was applied to define the ontology classes and class hierarchy, determine objects and related data attributes. Ontology instances were created to further evaluate the integrity, correctness and consistency of the developed knowledge base. The case studies showed that through the formalization of knowledge and establishment of rule libraries, rule reasoning could intelligently identify potential risk events and provide risk prevention measures. This research contributed a new perspective to resolve problems of access and integration knowledge and information in DFPE risk management work. By structuring and standardizing knowledge and information, the ontology-based risk knowledge base can facilitate knowledge transfer, sharing and reuse among different project participants. The ontology knowledge base can provide decision support for managers to protect the on-site workers, building structures and the surrounding environments.

Keywords

• deep foundation pit
• construction risk management
• ontology
• knowledge base