• Fri frakt över 249 kr
  • •
  • Snabba leveranser
  • •
  • Billiga böcker
Kundservice

Du är på sajten för privatpersoner.

Företag, bibliotek eller offentlig verksamhet?

Du handlar på classic.bokus.com, där alla dina funktioner finns intakta.
Till classic.bokus.com
Bokus logotyp. Gå till startsidan.
  • Erbjudanden
  • Nyheter
  • Student
  • Topplistor
  • Barn & ungdom
  • Bokus Play
  • E-böcker
  • Pocketböcker
  • Spel & pussel

10% rabatt på allt med kod: NYSTART10 →

Sidfot

Mina sidor

    Hjälp

    • Kundservice
    • Vanliga frågor och svar
    • Frakt och leverans
    • Retur vid ångerrätt
    • Reklamera vara
    • Betalning
    • Köpvillkor
    • Allmänna villkor
    • Information om webbplatsens tillgänglighet

    Om Bokus

    • Om oss
    • Pressrum
    • För studenter
    • För företag
    • För bibliotek och offentlig verksamhet
    • För leverantörer
    • Hållbarhet

    Populärt

    • Aktuella erbjudanden
    • Presentkort
    • Studentlitteratur
    • Nya böcker
    • Topplistor
    • Signerade böcker
    • Engelska böcker

    Inspiration

    • Boktips
    • BookTok
    • Populära bokserier
    • Barnbokskaraktärer
    • Populära författare
    Logotyp för Bokus
    Följ oss på Facebook (extern länk)Följ oss på Instagram (extern länk)Följ oss på YouTube (extern länk)Följ oss på TikTok (extern länk)
    bokus @ CookiesAnpassa cookiesIntegritetspolicyKöpvillkor
    Till Citymail hemsida (extern länk)Till Budbee hemsida (extern länk)Till Postnord hemsida (extern länk)Till Schenker hemsida (extern länk)Till Early Bird hemsida (extern länk)Till Walleys hemsida (extern länk)
    1. Naturvetenskap och teknik
    2. Teknik och industri
    3. Elektronik och kommunikationer

    Data-Driven Fault Detection and Reasoning for Industrial Monitoring

    AvJing Wang,Jinglin Zhou

    Inbunden, Engelska, 2022

    Del 3 i serien Intelligent Control and Learning Systems

    547 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Fler format och utgåvor

    Häftad

    439 kr

    Beskrivning

    This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.

    Produktinformation

    • Utgivningsdatum:2022-01-04
    • Mått:155 x 235 x 25 mm
    • Vikt:564 g
    • Format:Inbunden
    • Språk:Engelska
    • Serie:Intelligent Control and Learning Systems
    • Antal sidor:264
    • Förlag:Springer Verlag, Singapore
    • ISBN:9789811680434

    Utforska kategorier

    • Elektronik och kommunikationer inom Naturvetenskap och teknik
    • Teknik: allmänt inom Naturvetenskap och teknik
    • Artificiell intelligens inom Data och IT

    Mer om författaren

    Jing Wang received the B.S. degree in Industry Automation and the Ph.D. degree in Control Theory and Control Engineering from the Northeastern University, in 1994 and 1998, respectively. She was a professor with the College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China, from 1999 to 2020, and a visiting professor at University of Delaware, USA, in 2014. Now she is a professor with School of Electrical and Control Engineering, North China University of Technology, Beijing, China. Her research interest is oriented to different aspects, including modeling, optimization, advance control, process monitoring, and fault diagnosis for complex industrial process; industrial artificial intelligence based on analysis and learning from big data.Jinglin Zhou received the B.Eng., M.Sc., and Ph.D. degrees from Daqing Petroleum Institute, Hunan University, Changsha, China, and the Institute of Automation, Chinese Academyof Sciences, Beijing, China, in 1999, 2002, and 2005, respectively. He was Academic Visitor with the Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK. He is currently Professor with the College of Information Science and Technology, Beijing University of Chemical Technology, Beijing. His current research interests include stochastic distribution control, fault detection and diagnosis, variable structure control, and their applications.Xiaolu Chen received the Ph.D. degree in Control Science and Engineering from Beijing University of Chemical Technology in 2021. She was a joint PhD student at the University of Duisburg Essen, Duisburg, Germany, from 2019 to 2020. Now she is a postdoctoral fellow at Peking University, Beijing, China.  Her major is  control science and engineering.  Her research interests include modelling and fault diagnosis of complex industrial processes, data causality analysis, and intelligent learning algorithms.

    Innehållsförteckning

    • Introduction.- Basic Statistical Fault Detection Problems.- Principal Component Analysis.- Canonical Variate Analysis.- Partial Least Squares Regression.- Fisher Discriminant Analysis.- Canonical Variate Analysis.- Fault Classification based on Local Linear Embedding.- Fault Classification based on Fisher Discriminant Analysis.- Quality-Related Global-Local Partial Least Square Projection Monitoring.- Locality-Preserving Partial Least-Squares Statistical Quality Monitoring.- Locally Linear Embedding Orthogonal Projection to Latent Structure (LLEPLS).- Bayesian Causal Network for Discrete Systems.- Probability Causal Network for Continuous Systems.- Dual Robustness Projection to Latent Structure Method based on the L_1 Norm.