Data-Driven Fault Detection for Industrial Processes (Record no. 79242)

000 -LEADER
fixed length control field 03601nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-658-16756-1
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801221043.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 170102s2017 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783658167561
-- 978-3-658-16756-1
082 04 - CLASSIFICATION NUMBER
Call Number 629.8312
082 04 - CLASSIFICATION NUMBER
Call Number 003
100 1# - AUTHOR NAME
Author Chen, Zhiwen.
245 10 - TITLE STATEMENT
Title Data-Driven Fault Detection for Industrial Processes
Sub Title Canonical Correlation Analysis and Projection Based Methods /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIX, 112 p. 39 illus.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 A New Index for Performance Evaluation of FD Methods -- CCA-based FD Method for the Monitoring of Stationary Processes -- Projection-based FD Method for the Monitoring of Dynamic Processes -- Benchmark Study and Real-Time Implementation. .
520 ## - SUMMARY, ETC.
Summary, etc Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed. Contents A New Index for Performance Evaluation of FD Methods CCA-based FD Method for the Monitoring of Stationary Processes Projection-based FD Method for the Monitoring of Dynamic Processes Benchmark Study and Real-Time Implementation Target Groups Researchers and students in the field of process control and statistical hypothesis testing Research and development engineers in the process industry About the Author Zhiwen Chen’s research interests include multivariate statistical process monitoring, model-based and data-driven fault diagnosis as well as their application to industrial processes. He is currently working at the School of Information Science and Engineering at Central South University, China.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-658-16756-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Wiesbaden :
-- Springer Fachmedien Wiesbaden :
-- Imprint: Springer Vieweg,
-- 2017.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
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-- rdacarrier
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering mathematics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering—Data processing.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control and Systems Theory.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical and Computational Engineering Applications.
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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