WO2008042809A3 - Multivariate detection of abnormal conditions in a process plant - Google Patents

Multivariate detection of abnormal conditions in a process plant

Info

Publication number
WO2008042809A3
WO2008042809A3 PCT/US2007/079988 US2007079988W WO2008042809A3 WO 2008042809 A3 WO2008042809 A3 WO 2008042809A3 US 2007079988 W US2007079988 W US 2007079988W WO 2008042809 A3 WO2008042809 A3 WO 2008042809A3
Authority
WO
Grant status
Application
Patent type
Prior art keywords
process
line
operation
data
abnormal
Prior art date
Application number
PCT/US2007/079988
Other languages
French (fr)
Other versions
WO2008042809A2 (en )
Inventor
Nikola Samardzija
Ahmad Ali Hamad
Original Assignee
Fisher Rosemount Systems Inc
Nikola Samardzija
Ahmad Ali Hamad
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

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Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G05B23/0245Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a qualitative model, e.g. rule based; if-then decisions
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0208Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system
    • G05B23/021Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system adopting a different treatment of each operating region or a different mode of the monitored system, e.g. transient modes; different operating configurations of monitored system
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/024Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S715/00Data processing: presentation processing of document, operator interface processing, and screen saver display processing
    • Y10S715/961Operator interface with visual structure or function dictated by intended use
    • Y10S715/965Operator interface with visual structure or function dictated by intended use for process control and configuration

Abstract

Methods and systems to detect abnormal operations in a process of a process plant include collecting on-line process data. The collected on-line process data is generated from a plurality of dependent and independent process variables of the process, such as a coker heater. A plurality of multivariate statistical models of the operation of the process are generated using corresponding sets of the process data. Each model is a measure of the operation of the process when the process is on-line at different times, and al least one model is a measure of the operation of the process when the process is on-line and operating normally. The models are executed to generate outputs corresponding to loading value metrics of a corresponding dependent process variable, and the loading value metrics are utilized to detect abnormal operations of the process.
PCT/US2007/079988 2006-09-29 2007-09-28 Multivariate detection of abnormal conditions in a process plant WO2008042809A3 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US82763106 true 2006-09-29 2006-09-29
US60/827,631 2006-09-29

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2009530657A JP2010522905A (en) 2006-09-29 2007-09-28 Multivariate detection of an abnormal state in the process plant
EP20070843552 EP2064604A2 (en) 2006-09-29 2007-09-28 Multivariate detection of abnormal conditions in a process plant

Publications (2)

Publication Number Publication Date
WO2008042809A2 true WO2008042809A2 (en) 2008-04-10
WO2008042809A3 true true WO2008042809A3 (en) 2008-08-07

Family

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Family Applications (3)

Application Number Title Priority Date Filing Date
PCT/US2007/079919 WO2008042786A3 (en) 2006-09-29 2007-09-28 Multivariate detection of transient regions in a process control system
PCT/US2007/079986 WO2008042807A3 (en) 2006-09-29 2007-09-28 Statistical signatures used with multivariate analysis for steady-state deteection in a process
PCT/US2007/079988 WO2008042809A3 (en) 2006-09-29 2007-09-28 Multivariate detection of abnormal conditions in a process plant

Family Applications Before (2)

Application Number Title Priority Date Filing Date
PCT/US2007/079919 WO2008042786A3 (en) 2006-09-29 2007-09-28 Multivariate detection of transient regions in a process control system
PCT/US2007/079986 WO2008042807A3 (en) 2006-09-29 2007-09-28 Statistical signatures used with multivariate analysis for steady-state deteection in a process

Country Status (5)

Country Link
US (7) US8014880B2 (en)
EP (7) EP2067087A2 (en)
JP (7) JP2010506258A (en)
CN (7) CN101617279A (en)
WO (3) WO2008042786A3 (en)

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