摘要
化工生产中出现的异常事件往往导致系统出现故障,甚至发生重大事故,因此,建立预测和诊断异常事件的监控系统对生产过程的有效和稳定操作具有重要的意义。为此提出了一类赋时模糊Petri网(tFPN)模型,用于化工过程异常事件的预测与诊断,tFPN的变迁与产生式规则的可信度和时间相关联,可自动进行模糊推理。建立了基于tFPN的异常事件综合监控方案,并以聚丙烯反应为例进行了详细讨论。
One of the critical problems in the operation of chemical process is occurrence of abnormal events. Therefore a process monitoring system that can detect and diagnose abnormal events is important for effective and stable operation of chemical process. A new type of timed fuzzy Petri net （tFPN） approach to prognostication and diagnosis of abnormal events was proposed in this paper. In tFPN, a timing factor was associated with the transition and the degree of truth of rule, with which the reliabilities and appearing times of abnormal events could be inferred automatically. The procedures of abnormal events monitoring based on tFPN models were presented in detail. Finally, the proposed techniques and solutions were demonstrated through a polypropylene reactor case study, which showed promising results by prognostication of abnormal events and diagnosis of root causes.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2008年第7期1808-1811,共4页
CIESC Journal
基金
北京市重点学科基金项目(XK100100435)~~
