Performance Assessment for Process Monitoring and Fault Detection Methods (Record no. 59121)

000 -LEADER
fixed length control field 03458nam a22005055i 4500
001 - CONTROL NUMBER
control field 978-3-658-15971-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112555.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 161004s2016 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783658159719
-- 978-3-658-15971-9
082 04 - CLASSIFICATION NUMBER
Call Number 005.55
100 1# - AUTHOR NAME
Author Zhang, Kai.
245 10 - TITLE STATEMENT
Title Performance Assessment for Process Monitoring and Fault Detection Methods
300 ## - PHYSICAL DESCRIPTION
Number of Pages XXI, 153 p. 55 illus.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Assessing the performance of T2 and Q fault detection statistics -- Proposing a new performance evaluation index called expected detection delay (EDD) -- Assessing the performance of different PM-FD methods using EDD when applied to detecting different types of faults -- Assessing the state-space-based PM-FD methods when applied to a real hot strip mill process.
520 ## - SUMMARY, ETC.
Summary, etc The objective of Kai Zhang and his research is to assess the existing process monitoring and fault detection (PM-FD) methods. His aim is to provide suggestions and guidance for choosing appropriate PM-FD methods, because the performance assessment study for PM-FD methods has become an area of interest in both academics and industry. The author first compares basic FD statistics, and then assesses different PM-FD methods to monitor the key performance indicators of static processes, steady-state dynamic processes and general dynamic processes including transient states. He validates the theoretical developments using both benchmark and real industrial processes. Contents Assessing the performance of T2 and Q fault detection statistics Proposing a new performance evaluation index called expected detection delay (EDD) Assessing the performance of different PM-FD methods using EDD when applied to detecting different types of faults Assessing the state-space-based PM-FD methods when applied to a real hot strip mill process Target Groups Scientists and students in the field of process control and statistical quality control Electrical engineers, chemical engineers, hot strip steel mill engineers About the Author Kai Zhang has just finished his PhD defense. His research area covers multivariate statistical process monitoring (PM) methods, data-driven fault detection (FD) methods and performance evaluation for PM-FD methods.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-658-15971-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Wiesbaden :
-- Springer Fachmedien Wiesbaden :
-- Imprint: Springer Vieweg,
-- 2016.
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-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Chemical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical statistics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- System theory.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Probability and Statistics in Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial Chemistry/Chemical Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Systems Theory, Control.
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-- ZDB-2-SCS

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