Intelligent Diagnosis and Prognosis of Industrial Networked Systems (Hardcover)

In an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications.

Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications.

The book includes portable tool sets for many industrial applications, including:

• Forecasting machine tool wear in industrial cutting machines
• Reduction of sensors and features for industrial fault detection and isolation (FDI)
• Identification of critical resonant modes in mechatronic systems for system design of R&D
• Probabilistic small-signal stability in large-scale interconnected power systems
• Discrete event command and control for military applications

The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.

在競爭激烈的時代，工廠運營效率必須最大化，機器故障導致的停機時間變得更加昂貴。為了降低運營成本並增加收入，各行業迫切需要預測工業機器、流程和系統的故障進展和剩餘壽命。一位工程師在主軸馬達上安裝聲學感測器，希望在不停止銑削過程的情況下知道滾珠軸承何時會磨損。一位研究傳感器網絡的科學家想知道哪些傳感器是多餘的，可以剪除以節省操作和計算開銷。這些情景說明了在工程應用中需要新的統一觀點的需求。

《智能工業網絡系統的診斷和預測》提出了可以應用於現實工程系統的線性數學工具集。該書概述了智能工業網絡系統的診斷和預測所需的向量、矩陣和線性系統理論的基礎知識。在此基礎上，它開發了自動化的數學機械和正式的決策軟件工具，用於實際應用。

該書包括許多工業應用的便攜工具集，包括：

- 預測工業切割機床的磨損
- 減少工業故障檢測和隔離（FDI）的傳感器和特徵
- 確定機電系統中的關鍵共振模式，用於研發系統設計
- 大型互聯電力系統中的概率小信號穩定性
- 軍事應用的離散事件指揮和控制

該書還提出了智能診斷和預測在節能製造、生命周期評估和系統架構方面的未來發展方向。以簡潔易懂的風格撰寫，它提供了數學嚴謹但不複雜的工具。作為學術界、研究界和工業界的橋樑，這本參考書為工程師和管理人員在設備維護方面做出決策提供了專業知識，同時也適用於該領域的研究人員和學生。