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作 者:李琳琳 李莎莎 DING Steven Xianchun 彭鑫[4] 彭开香[1,2] LI Lin-Lin;LI Sha-Sha;DING Steven Xianchun;PENG Xin;PENG Kai-Xiang(School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,China;Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education,University of Science and Technology Beijing,Beijing 100083,China;Institute for Automatic Control and Complex Systems,University of Duisburg-Essen,Duisburg 47057,Germany;Key Laboratory of Smart Manufacturing in Energy Chemical Process,Ministry of Education,East China University of Science and Technology,Shanghai 200237,China)
机构地区:[1]北京科技大学自动化学院,中国北京100083 [2]北京科技大学工业过程知识自动化教育部重点实验室,中国北京100083 [3]德国杜伊斯堡−埃森大学自动控制与复杂系统研究所,德国杜伊斯堡47057 [4]华东理工大学能源化工过程智能制造教育部重点实验室,中国上海200237
出 处:《自动化学报》2023年第9期1928-1940,共13页Acta Automatica Sinica
基 金:国家自然科学基金(62073029,U21A20483,62003140);北京市自然科学基金(4202045);中央高校基本业务费(FRF-TP-20-012A3)资助。
摘 要:针对复杂工业系统对性能衰退的容忍度低等问题,提出基于系统性能预测的一类反馈控制系统过程监测方法,通过黎曼度量对控制性能衰退程度进行预测与监测,并给出发生故障的类型,以提升过程监测系统的实时性与准确性.首先,利用系统的实时数据,计算系统性能衰退的预测指标;其次,利用黎曼度量对系统性能衰退程度进行预测与监测,并利用随机算法给出对应的阈值来诊断系统性能衰退;最后,通过计算各类引发系统性能衰退的故障的性能预测指标集合的中心和阈值,实现故障的实时定位.所提出的方法通过三容水箱仿真实验平台进行验证.Associated with the issue that the industrial processes have low tolerance in performance degradation,a performance monitoring and diagnosis scheme for a class of feedback control systems is developed based on system performance prediction.The Riemannian metric is then adopted to predict and monitor the degree of the control performance degradation,and classify the fault type,so as to improve the real-time ability and accuracy of the performance monitoring systems.Firstly,a prediction indicator is introduced to predict the system performance degradation using online process data.Then,the Riemannian metric is implemented to predict and monitor the degree of the control performance degradation,and the randomized algorithm is adopted to set the threshold for diagnosing the performance degradation.Finally,by computing the center and threshold for the performance predictor set caused by all the possible faults,the fault localization can be achieved.The effectiveness of the proposed method is verified by a case study on a three-tank system.
分 类 号:TP273[自动化与计算机技术—检测技术与自动化装置]
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