Capturing Connectivity and Causality in Complex Industrial Processes (SpringerBriefs in Applied Sciences and Technology)
暫譯: 捕捉複雜工業過程中的連接性與因果關係 (SpringerBriefs 應用科學與技術系列)
Fan Yang
- 出版商: Springer
- 出版日期: 2014-04-10
- 售價: $2,420
- 貴賓價: 9.5 折 $2,299
- 語言: 英文
- 頁數: 108
- 裝訂: Paperback
- ISBN: 3319053795
- ISBN-13: 9783319053790
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商品描述
This brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways:
· from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and
· from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian networks can be used to identify pair-wise relationships and network topology.
These methods rely on the notion of information fusion whereby process operating data is combined with qualitative process knowledge, to give a holistic picture of the system.
商品描述(中文翻譯)
這篇簡報回顧了現代工業過程、生物系統和社會系統中相互關係的概念。具體而言,探討了複雜系統內部及其元素之間的連接性和因果性;這些概念在分析和影響機制、結構特性及其動態行為方面具有重要意義,特別是在故障診斷和危害分析中。工業過程中的故障檢測和隔離關注於根本原因和故障傳播,簡報顯示,過程的連接性和因果性信息可以通過兩種方式捕捉:
· 從過程知識:基於第一原則的結構模型可以與從標準格式描述的過程流程圖中獲得的鄰接/可達性矩陣或拓撲模型合併;以及
· 從過程數據:可以使用交叉相關分析、Granger因果關係及其擴展、頻域方法、信息理論方法和貝葉斯網絡來識別成對關係和網絡拓撲。
這些方法依賴於信息融合的概念,即將過程操作數據與定性過程知識結合,以提供系統的整體圖像。