基于KG-KGCN的某型动力装置风险分析方法

Risk analysis method of a certain type of power plant based on KG-KGCN

针对动力装置危险因素众多、风险数据繁杂且利用率不高等问题,以故障模式、影响及危害性分析等数据为基础,提出基于知识图谱和图神经网络的系统风险分析方法及算法,利用事件的知识完成链接预测,推理出引发事件的原因及影响等,以实现其精准的统计分析。本文以某型发动机为对象,对其进行风险分析和推理。结果表明:该方法有效解决了传统方法存在的表单繁琐、分析单一等问题,结果更加准确和全面,可使分析效率提升60%以上;并可及时开展风险推理和预测,实现从事后分析向主动预防的转变,为动力装置的智能运维提供了有力支持。

Targeting the problems of numerous risk factors,complex risk data and low utilization rate of power plant,and based on the data of failure mode,impact and criticality analysis,a method and algorithm of system risk analysis was proposed using knowledge graph and graph neural network,and the knowledge of events were utilized to complete link prediction and deduce the cause and impact of events,so as to achieve accurate statistical analysis.A certain type of engine was taken as the object to carry out risk analysis and reasoning.Results showed that this method effectively solved the problems of the traditional method,such as cumbersome forms and single analysis,the results were more accurate and comprehensive,and the analysis efficiency can be improved by more than 60%;and it can carry out risk reasoning and prediction in time,and realize the transformation from post analysis to active prevention,providing a strong support for the intelligent operation and maintenance of power plants.