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面向系统层级的复杂工业过程全息故障诊断 被引量:7

System-levels-based holographic fault diagnosis for complex industrial processes
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摘要 复杂工业过程具有长流程、系统层级多、故障潜在分布空间范围较广的特点,是当前故障诊断领域的热门研究方向。首先,对主流故障诊断技术进行了分类和概述;其次,采用定量与定性相结合思路,提出了面向系统层级的复杂工业过程全息故障诊断框架,为复杂工业全流程的过程监测提供一整套技术和解决方案。相比于目前的故障诊断方法,该框架不仅包括故障检测和故障辨识,还包括故障根源诊断、故障传播路径识别、故障的定量诊断与评估,可有效解决复杂工业过程系统的综合故障诊断问题,实用性强,能够有效地减少或避免故障发生、保证产品的质量、提高企业的生产效率与生产安全;最后对故障诊断技术的发展趋势和亟待解决的问题进行了展望。 Complex industrial process has long processes,many system levels and a wide range of potential fault distribution space,which is a hotspot in the current fault diagnosis field.Firstly,the current mainstream fault diagnosis methods in process monitoring are classified and summarized.Secondly,this study adopts the combination of quantitative and qualitative,which is based on data and knowledge.A system-level holographic fault diagnosis framework for complex industrial process is proposed,which provides a complete set of techniques and solutions for process monitoring in complex industrial plant-wide process.Compared with current fault diagnosis methods,the framework not only includes fault detection and fault identification,but also includes root cause diagnosis,fault propagation path identification,quantitative fault diagnosis and evaluation.It is quite a practical method for process systems,which can effectively reduce or avoid the fault occurrence,guarantee the quality of the product,and improve the production efficiency and safety of enterprises.Finally,the development trend of fault diagnosis technology and problems to be solved are prospected.
作者 彭开香 张传放 马亮 董洁 焦瑞华 唐鹏 PENG Kaixiang;ZHANG Chuanfang;MA Liang;DONG Jie;JIAO Ruihua;TANG Peng(Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education,School of Automation andElectrical Engineering,University of Science and Technology Beijing,Beijing 100083,China)
出处 《化工学报》 EI CAS CSCD 北大核心 2019年第2期590-598,共9页 CIESC Journal
基金 国家自然科学基金项目(61473033 61773053 61873024)
关键词 过程系统 全流程 故障诊断 故障传播 故障评估 生产 安全 process systems plant-wide process fault diagnosis fault propagation fault assessment production safety
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