基于人工智能的石化机组故障诊断检测算法  

Review of Fault Diagnosis and Detection Methods for Petrochemical Units Based on Artificial Intelligence

作　　者：房锦发 熊建斌 董湘君 王颀 叶宝玉[2] 苏乃权 路天天 林可锐 FANG Jinfa;XIONG Jianbin;DONG Xiangjun;WANG Qi;YE Baoyu;SU Naiquan;LU Tiantian;LIN Kerui(School of Automation,Guangdong Polytechnic Normal University,Guangzhou Guangdong 510700,China;Aircraft Maintenance Engineering College,Guangzhou Civil Aviation College,Guangzhou Guangdong 510403,China;College of Mechanical and Electrical Engineering,Guangdong University of Petrochemical Technology,Maoming Guangdong 525000,China)

机构地区：[1]广东技术师范大学自动化学院,广东广州510700 [2]广州民航职业技术学院飞机维修工程学院,广东广州510403 [3]广东石油化工学院机电工程学院,广东茂名525000

出　　处：《机床与液压》2024年第18期182-194,共13页Machine Tool & Hydraulics

基　　金：国家自然科学基金-广东省联合基金重点项目(U22A20221);国家自然科学基金面上项目(62073090);中国科学院科技服务网络计划黄埔专项(STS-HP-202202);广东省自然科学基金面上项目(2023A1515011423,2024A1515012090,2023A1515240020);自然资源部海洋环境探测技术与应用重点实验室开放基金项目(MESTA-2022-B001);广东省科技创新战略专项基金项目(PDJH2023B0304,PDJH2024A225)。

摘　　要：石化机组故障诊断对于现代工业系统的可靠性和安全性具有重要意义。人工智能(AI)技术作为工业应用的新兴领域和故障识别的有效解决方案,日益受到学术界和工业界的关注。然而,在不同的运行条件下,人工智能方法面临着巨大的挑战。从理论背景和工业应用两方面对石化机组故障诊断中的人工智能算法进行全面阐述。介绍不同的人工智能算法,包括K近邻、朴素贝叶斯、支持向量机、人工神经网络和深度学习等方法;对AI算法在工业应用中进行了广泛的文献调研;最后,对不同AI算法的优势、局限性、实践启示进行总结,表明了技术进步、多模态数据整合、实时监测预测、算法通用性对提升石化工业效率与可靠性的关键作用,并展望了未来的研究方向与挑战。The fault diagnosis of petrochemical units is of great significance to the reliability and safety of modern industrial systems.Artificial intelligence(AI)technology as an emerging field in industrial applications and an effective solution for fault identification,it has received increasing attention from academia and industry.However,under different operating conditions,the AI approach faces great challenges.The artificial intelligence algorithms in fault diagnosis of petrochemical units were described from two aspects:theoretical background and industrial application.Different artificial intelligence algorithms were introduced,including K-nearest neighbor,naive Bayes,support vector machines,artificial neural networks and deep learning methods.Then,an extensive literature survey of AI algorithms in industrial applications was carried out.Finally,the advantages,limitations and practical enlightenment of different AI algorithms were summarized,indicating the key role of technological progress,multi-modal data integration,real-time monitoring and prediction and algorithm universality in improving the efficiency and reliability of the petrochemical industry,and looking forward to future research directions and challenges.

关 键 词：石化机组 故障诊断 人工智能 检测算法 

分 类 号：TH165.3[机械工程—机械制造及自动化] TP18[自动化与计算机技术—控制理论与控制工程] TP277[自动化与计算机技术—控制科学与工程]