摘要
在前序工作 (I)、(II)的基础上 ,应用化工过程测量数据校正系统CPDRS ,选择常减压炼油生产装置 ,以实际测量数据及现场标定数据对本研究提出的数据校正与过失误差侦破新方法、神经网络与过程模拟相结合的新策略等进行了考核分析。着重分析了过失误差侦破能力 ,数据校正值的准确性 ,CPDRS系统的通用性、可靠性。以CPDRS在常减压炼油装置的应用为例 ,介绍了CPDRS系统考核与应用情况。实例考核应用结果表明 ,CPDRS功能齐全 ,使用方便 ,校正结果与标定值相吻合。
On the basis of work in papers (Ⅰ) and (Ⅱ), using the chemical process data reconciliation system (CPDRS), the new technique of data reconciliation and gross error detection proposed and the new strategy combined by artificial neural net and process simulation were examined and analyzed with the actual measurement data and the spot demarcated data obtained from atmospheric and vacuum distillation unit of refinery. The ability of gross error detection, the precision of reconciliation data and the reliability and universal application of CPDRS were analyzed emphatically. As an example, CPDRS was applied and examined in atmospheric and vacuum distillation unit of refinery. The results indicated that CPDRS was of sufficient functions and convenient to be used, the recorciliation data coincided well with the demarcated data.
出处
《青岛科技大学学报（自然科学版）》
CAS
2004年第1期1-7,共7页
Journal of Qingdao University of Science and Technology:Natural Science Edition
基金
青岛市重点科技攻关计划 (G99.R 3
1999 2 0 0 1)
齐鲁石化公司资助
关键词
化工过程
数据校正
过失误差侦破
CPDRS
常减压炼油装置
chemical process
data reconciliation
examination and analysis
atmospheric and vacuum distillation unit of refinery
