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Tested and proven strategy to develop optimal automated processfault analyzers
Process fault analyzers monitor process operations in order toidentify the underlying causes of operational problems. Severaldiagnostic strategies exist for automating process fault analysis; however, automated fault analysis is still not widely used withinthe processing industries due to problems of cost and performanceas well as the difficulty of modeling process behavior at neededlevels of detail.
In response, this book presents the method of minimal evidence(MOME), a model-based diagnostic strategy that facilitates thedevelopment and implementation of optimal automated process faultanalyzers. MOME was created at the University of Delaware by theresearchers who developed the FALCON system, a real-time, onlineprocess fault analyzer. The authors demonstrate how MOME is used todiagnose single and multiple fault situations, determine thestrategic placement of process sensors, and distribute faultanalyzers within large processing systems.
Optimal Automated Process Fault Analysis begins byexploring the need to automate process fault analysis. Next, thebook examines:
* Logic of model-based reasoning as used in MOME
* MOME logic for performing single and multiple faultdiagnoses
* Fuzzy logic algorithms for automating MOME
* Distributing process fault analyzers throughout largeprocessing systems
* Virtual SPC analysis and its use in FALCONEER(TM) IV
* Process state transition logic and its use in FALCONEER(TM)IV
The book concludes with a summary of the lessons learned byemploying FALCONEER(TM) IV in actual process applications, including the benefits of „intelligent supervision“ of processoperations.
With this book as their guide, readers have a powerful new toolfor ensuring the safety and reliability of any chemical processingsystem.
Process fault analyzers monitor process operations in order toidentify the underlying causes of operational problems. Severaldiagnostic strategies exist for automating process fault analysis; however, automated fault analysis is still not widely used withinthe processing industries due to problems of cost and performanceas well as the difficulty of modeling process behavior at neededlevels of detail.
In response, this book presents the method of minimal evidence(MOME), a model-based diagnostic strategy that facilitates thedevelopment and implementation of optimal automated process faultanalyzers. MOME was created at the University of Delaware by theresearchers who developed the FALCON system, a real-time, onlineprocess fault analyzer. The authors demonstrate how MOME is used todiagnose single and multiple fault situations, determine thestrategic placement of process sensors, and distribute faultanalyzers within large processing systems.
Optimal Automated Process Fault Analysis begins byexploring the need to automate process fault analysis. Next, thebook examines:
* Logic of model-based reasoning as used in MOME
* MOME logic for performing single and multiple faultdiagnoses
* Fuzzy logic algorithms for automating MOME
* Distributing process fault analyzers throughout largeprocessing systems
* Virtual SPC analysis and its use in FALCONEER(TM) IV
* Process state transition logic and its use in FALCONEER(TM)IV
The book concludes with a summary of the lessons learned byemploying FALCONEER(TM) IV in actual process applications, including the benefits of „intelligent supervision“ of processoperations.
With this book as their guide, readers have a powerful new toolfor ensuring the safety and reliability of any chemical processingsystem.
