Researching on HAZOP Information Standardization Based on Knowledge Ontology
Dong Qiang Gao, Yao Xiao, Beike Zhang, Xiaohan Chen · 2019
The results of most traditional HAZOP analysis were recorded in documents. However, due to the large amount of data and the various formats of HAZOP analysis documents, the analysis data of the predecessors cannot be shared and reused. In order to solve this problem, the paper proposes a method to transform HAZOP analysis documents into knowledge ontology, which makes knowledge easy to store and share. We use the method to identify the content of the document, and then use the word segmentation tool ICTCLAS5.0 to process Chinese documents, including Chinese word segmentation, part-of-speech tagging and deletion of stop words, then the key information is extracted according to the IEC-61882 international standard and store it in the OWL document. Finally, we use Protégé software to intuitively manage OWL documents and validate knowledge. The final result shows that the method can well express the knowledge of HAZOP analysis and realize the integration, sharing and reuse of HAZOP analysis data.