典型特种设备事故预测预警方法研究  

Research on prediction and prevention methods for typical special equipment accidents

作　　者：姚雪佳 曹逻炜 张硕 邵珊珊[1,2] YAO Xuejia;CAO Luowei;ZHANG Shuo;SHAO Shanshan(National Market Supervision Key Laboratory(Special Equipment Safety and Energy Conservation),Beijing 100191,China)

机构地区：[1]国家市场监管重点实验室(特种设备安全与节能),北京100191 [2]中国特种设备检测研究院总局科技成果转化基地,北京100029

出　　处：《工业安全与环保》2024年第11期42-46,共5页Industrial Safety and Environmental Protection

基　　金：国家重点研发计划项目(2022YFF0607404)。

摘　　要：特种设备事故预测预警结果是制定事故预防措施的重要依据,对特种设备安全保障具有重大意义。综合前人的研究成果,将特种设备事故预测方法研究分为2类:基于案例推理的事故预测和基于机器学习的事故预测。基于案例推理的事故预测方面,回顾了案例推理方法的基本思想及原理,并对具有代表性的特种设备事故预测研究进行了归纳总结;基于机器学习的事故预测方面,介绍了方法基本原理和典型研究成果案例,对不同算法模型在特种设备事故预测领域应用结果的准确性和稳定性方面进行了分析。最后,对特种设备事故预测研究目前的不足及未来发展方向进行了总结。The prediction and early warning results of special equipment accidents are an important basis for accident prevention measures and have signification implications for the safety of special equipment.Based on previous research,the study classifies the investigation of specialized equipment accident prediction methods into two main categories:case-based reasoning and machine learning.For case-based reasoning,it outlines the basic principles and summarizes notable research in predicting specialized equipment accidents.For machine learning,it introduces basic principles and typical research examples,analyzing the accuracy and reliability of different algorithm models used in accident prediction.Finally,it concludes by summarizing current shortcomings and suggesting future research directions in specialized equipment accident prediction.

关 键 词：特种设备 事故预测 案例推理 机器学习 模型融合 

分 类 号：X924.2[环境科学与工程—安全科学]