基于PDC的廠級振蕩根源定位研究
發(fā)布時間：2018-11-03 20:13
【摘要】：過程工業(yè)既是能源、各種原材料的生產(chǎn)者,同時也是能源的主要消耗者,節(jié)能降耗對提高企業(yè)的經(jīng)濟效益和促進國家低碳環(huán)保戰(zhàn)略的施行有重大的意義。過程工業(yè)中由于控制回路參數(shù)調(diào)校不當,閥門粘滯,過程非線性,控制系統(tǒng)設計低劣,外部輸入干擾等原因,往往導致了整個過程系統(tǒng)的廠級范圍大規(guī)模的振蕩。及時評估多回路控制系統(tǒng)性能,檢測系統(tǒng)中的過程干擾及異常工況,從而準確定位并診斷引發(fā)振蕩的根源,并對故障源進行維護修理,確保企業(yè)產(chǎn)品的質(zhì)量和生產(chǎn)效率,是目前過程工業(yè)中關注的主要問題之一 本課題以偏有向相干分析PDC(Partial directed coherence)為基礎,針對過程工業(yè)中采集和存儲的大量過程歷史數(shù)據(jù),提出了新的基于PDC的廠級振蕩根源定位方法。該方法通過傳統(tǒng)功率譜圖和頻譜ICA(Independent Component Analysis)算法來篩選數(shù)據(jù),然后對篩選數(shù)據(jù)進行偏有向相干分析,對過程變量間波動傳播方向和強度大小進行辨識,同時構建變量間的PDC因果關系圖,最后應用DFS/BFS的權值閾值搜索算法和過程先驗知識對因果關系圖進行化簡,刪除次要因果關系分支,直觀辨識波動傳播路徑。 本課題中,利用該方法對基于SIMULINK的仿真案例數(shù)據(jù),以及EASTMAN化工廠、上海某氯堿廠工業(yè)歷史數(shù)據(jù)進行分析,進行廠級振蕩根源定位,結果表明,這一套根源定位方案是切實可行的。
[Abstract]:Process industry is not only the producer of energy and raw materials, but also the main consumer of energy. Energy saving and reducing consumption are of great significance to improve the economic efficiency of enterprises and promote the implementation of national low-carbon environmental protection strategy. Due to improper adjustment of control circuit parameters, valve stickiness, process nonlinearity, poor design of control system, external input interference and so on, large scale oscillation of the whole process system is often caused. Evaluate the performance of the multi-loop control system in time, detect the process interference and abnormal working condition in the system, and accurately locate and diagnose the source of the oscillation, and carry on the maintenance and repair to the fault source to ensure the quality and production efficiency of the enterprise product. It is one of the most important problems in process industry at present. Based on the partial directed coherence analysis (PDC (Partial directed coherence), a large number of process history data are collected and stored in the process industry. A new method based on PDC is proposed to locate the source of plant oscillation. In this method, the traditional power spectrum and spectrum ICA (Independent Component Analysis) algorithm are used to screen the data, and then the biased coherent analysis is carried out to identify the direction and intensity of the wave propagation between the process variables. At the same time, the PDC causality graph between variables is constructed. Finally, the weight threshold search algorithm of DFS/BFS and the process prior knowledge are used to simplify the causality graph, to delete the secondary causality branch, and to identify the wave propagation path intuitively. In this paper, the simulation case data based on SIMULINK and the industrial historical data of EASTMAN chemical plant and a chlor-alkali plant in Shanghai are analyzed, and the source of the oscillation is located. The results show that, This solution is feasible.
【學位授予單位】：華東理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TH165.3
本文編號：2308898
[Abstract]:Process industry is not only the producer of energy and raw materials, but also the main consumer of energy. Energy saving and reducing consumption are of great significance to improve the economic efficiency of enterprises and promote the implementation of national low-carbon environmental protection strategy. Due to improper adjustment of control circuit parameters, valve stickiness, process nonlinearity, poor design of control system, external input interference and so on, large scale oscillation of the whole process system is often caused. Evaluate the performance of the multi-loop control system in time, detect the process interference and abnormal working condition in the system, and accurately locate and diagnose the source of the oscillation, and carry on the maintenance and repair to the fault source to ensure the quality and production efficiency of the enterprise product. It is one of the most important problems in process industry at present. Based on the partial directed coherence analysis (PDC (Partial directed coherence), a large number of process history data are collected and stored in the process industry. A new method based on PDC is proposed to locate the source of plant oscillation. In this method, the traditional power spectrum and spectrum ICA (Independent Component Analysis) algorithm are used to screen the data, and then the biased coherent analysis is carried out to identify the direction and intensity of the wave propagation between the process variables. At the same time, the PDC causality graph between variables is constructed. Finally, the weight threshold search algorithm of DFS/BFS and the process prior knowledge are used to simplify the causality graph, to delete the secondary causality branch, and to identify the wave propagation path intuitively. In this paper, the simulation case data based on SIMULINK and the industrial historical data of EASTMAN chemical plant and a chlor-alkali plant in Shanghai are analyzed, and the source of the oscillation is located. The results show that, This solution is feasible.
【學位授予單位】：華東理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TH165.3
【參考文獻】
相關期刊論文 前5條
1 孫金明,左信,季德偉,陳育昆;PID控制器性能評價[J];化工自動化及儀表;2004年05期
2 夏春明;吳欽;鄭建榮;;基于格蘭杰因果檢驗的過程波動路徑及根源識別分析[J];華東理工大學學報(自然科學版);2010年01期
3 陳耀,羅曉,孫優(yōu)賢;過程控制工程中的若干問題討論[J];基礎自動化;2002年02期
4 王印松;張彩;;基于設定值響應的PI控制系統(tǒng)性能評估[J];控制工程;2007年01期
5 張旭昶,胡立生;模型預測控制的性能監(jiān)視[J];機電一體化;2004年04期
，本文編號：2308898
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