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(1 - 8 of 8)
An intelligent system for multivariate statistical process monitoring and diagnosis
Title
An intelligent system for multivariate statistical process monitoring and diagnosis
Creator
Tatara, E., Cinar, A.
Date
2002-04
Publisher
I S A-THE INSTRUMENTATION SYSTEMS AUTOMATION SOC
Description
A knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real...
Show moreA knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real-time KBS consists of a supervisory system using G2 KBS development software linked with external statistical modules for system identification and sensor fault diagnosis. The various statistical techniques were prototyped in MATLAB, converted to ANSI C code, and linked with the G2 Standard Interface. The KBS automatically performs all operations of data collection, identification, monitoring, and sensor fault diagnosis with little or no input from the user. Navigation throughout the KBS is via menu buttons on each user-accessible screen. Selected process variables are displayed on charts showing the history of the variables over a period of time. Multivariate statistical tests and contribution plots are also shown graphically. The KBS was evaluated using simulation studies with a polymerization reactor through a nonlinear dynamic model. Both normal operation conditions as well as conditions of process disturbances were observed to evaluate the KBS performance. Specific user-defined disturbances were added to the simulation, and the KBS correctly diagnosed both process and sensor faults when present.
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Interpreting ECG data by integrating statistical and artificial intelligence tools
Title
Interpreting ECG data by integrating statistical and artificial intelligence tools
Creator
Tatara, E., Cinar, A.
Date
2002-01
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Description
The use of an automated system integrating data conditioning, statistical methods, and artificial intelligence tools to summarize and...
Show moreThe use of an automated system integrating data conditioning, statistical methods, and artificial intelligence tools to summarize and interpret high-frequency physiological data such as the electrocardiogram is investigated. The development of a methodology and its associated tools for real-time patient monitoring and diagnosis is accomplished by using the commercial programming environments MATLAB and G2, a real-time knowledge-based system (KBS) development shell. Data interpretation and classification is performed by integrating statistical classification methods and knowledge-based techniques with a graphical user interface that provides quick access to the analysis results as well as the original data. A KBS was developed that incorporates various statistical methods with a rule-based decision system to detect abnormal situations, provide preliminary interpretation and diagnosis, and to report these findings to the healthcare provider
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Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations
Title
Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations
Creator
Undey, C., Tatara, E., Cinar, A.
Date
2004-02-19
Publisher
ELSEVIER SCIENCE BV
Description
Supervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality...
Show moreSupervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality control. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide an efficient modeling and supervision framework. A new type of MPLS modeling technique that is especially suitable for online real-time process monitoring and the multivariate monitoring charts are presented. This online process monitoring technique is also extended to include predictions of end-of-batch quality measurements during the progress of a batch run. Process monitoring, quality estimation and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also automated through a generic rule-base for efficient alarm handling. The integrated RTKBS and the implementation of MPLS-based process monitoring and quality control are illustrated using a fed-batch penicillin production benchmark process simulator.
Endnote format citation for DOI:10.1016/j.jbiotec.2003.10.004
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Real-time batch process supervision by integrated knowledge-based systems and multivariate statistical methods
Title
Real-time batch process supervision by integrated knowledge-based systems and multivariate statistical methods
Creator
Undey, C., Tatara, E., Cinar, A.
Date
2003-08
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Description
Real-time supervision of batch operations during the progress of a batch run offers many advantages over end-of-batch quality control. Process...
Show moreReal-time supervision of batch operations during the progress of a batch run offers many advantages over end-of-batch quality control. Process monitoring, quality estimation, and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also automated through a generic rule-base for efficient alarm handling and fault diagnosis. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide a powerful modeling, monitoring, and supervision framework. Online process monitoring techniques are developed and extended to include predictions of end-of-batch quality measurements during the progress of a batch run. The integrated RTKBS and the implementation of MPLS-based process monitoring and quality control are illustrated using a fed-batch penicillin production benchmark process simulator.
Endnote format citation for DOI:10.1016/j.engappai.2003.09.003
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Agent-based control of autocatalytic replicators in networks of reactors
Title
Agent-based control of autocatalytic replicators in networks of reactors
Creator
Tatara, E., Birol, I., Teymour, F., Cinar, A.
Date
2005-03-15
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Description
Spatially distributed systems such as reactor networks hosting multiple autocatalytic species demonstrate a rich spectrum of complex behavior....
Show moreSpatially distributed systems such as reactor networks hosting multiple autocatalytic species demonstrate a rich spectrum of complex behavior. From a control systems perspective, spatially distributed systems offer a difficult control challenge because of their distributed nature, nonlinearity, and high order. Furthermore, manipulation of the network states may require simultaneous control actions in different parts of the system and may need transients through several operating regimes to achieve the desired operation. The lack of accurate and computationally efficient model-based techniques for large, spatially distributed systems results in complications in controlling the system, either in disturbance rejection or changing the operational regimes of the system. A hierarchical, agent-based control structure is presented whereby local control objectives may be changed in order to achieve the global control objective. The performance of the control system is demonstrated for several global objectives. The challenge posed is to control the spatial distribution of autocatalytic species in a network of five reactors hosting two species using the interaction flow rates as the manipulated variables. The multi-agent control system is able to effectively explore the parameter space of the network and intelligently manipulate the network flow rates such that the desired spatial distribution of species is achieved.
Endnote format citation for DOI:10.1016/j.compchemeng.2004.09.022
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Static and dynamic behavior of autocatalytic replicators in reactor networks
Title
Static and dynamic behavior of autocatalytic replicators in reactor networks
Creator
Tatara, E., Birol, I., Teymour, F., Cinar, A.
Date
2004-07-07
Publisher
AMER CHEMICAL SOC
Description
The static and dynamic behavior of the autocatalytic reaction R + 2P --> 3P with decay P --> D is studied in networks of coupled continuous...
Show moreThe static and dynamic behavior of the autocatalytic reaction R + 2P --> 3P with decay P --> D is studied in networks of coupled continuous stirred tank reactors (CSTRs). Numerical bifurcation studies of the system are performed, resulting in rich steady-state bifurcation structures with multiple steady states and isolas. The heterogeneity of the networks is influenced by the number of reactors as well as the network topology. It is shown that the number of steady states of the network increases with heterogeneity, thereby allowing those autocatalytic species to exist in the network that would normally not exist in the homogeneous environment of a single CSTR. Spatial patterns of stable steady states are evident in reactor networks. Dynamic simulation studies are performed to illustrate the transition from one stable state configuration to another or from stable steady states to periodic regimes.
Endnote format citation for DOI:10.1021/ie030802d
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Measuring complexity in reactor networks with cubic autocatalytic reactions
Title
Measuring complexity in reactor networks with cubic autocatalytic reactions
Creator
Tatara, E., Birol, I., Cinar, A., Teymour, F.
Date
2005-04-13
Publisher
AMER CHEMICAL SOC
Description
Systems with high steady-state multiplicity and rich dynamic behavior are difficult to investigate using conventional reductionist methods. A...
Show moreSystems with high steady-state multiplicity and rich dynamic behavior are difficult to investigate using conventional reductionist methods. A network of more than five reactors hosting cubic autocatalytic reactions may potentially have more than 101 steady states and many distinct dynamic regimes, all for the same parameter set. This paper discusses how the static complexity of such systems can be measured to give a holistic picture. To achieve this, stochastic simulations were performed to statistically determine the bifurcation structure of the system, and the gathered information is summarized using a measure akin to fractal dimension. With this measure, the growth of static complexity is investigated as a function of the network size.
Endnote format citation for DOI:10.1021/ie049246t
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Batch process monitoring and its application to polymerization systems
Title
Batch process monitoring and its application to polymerization systems
Creator
Undey, C., Ertunc, S., Tatara, E., Teymour, F., Cinar, A.
Date
2004-01
Publisher
WILEY-V C H VERLAG GMBH
Description
Slight changes in raw material properties or operating conditions during critical periods of operation of batch and semi-batch polymerization...
Show moreSlight changes in raw material properties or operating conditions during critical periods of operation of batch and semi-batch polymerization reactors may have a strong influence on reaction mechanism and impact final product quality. Online process monitoring, fault detection, fault diagnosis, and product quality prediction in real-time ensure safe reactor operation and warn operators about excursions from normal operation that may lead to deterioration in product properties. Multivariate statistical process monitoring and quality prediction using multiway principal components analysis and multiway partial least squares have been successful in detecting abnormalities in process operation and product quality. When abnormal process operation is detected, fault diagnosis tools are used to determine the source cause of the deviation. Illustrative case studies are presented via simulated polyvinyl acetate polymerization.
Endnote format citation for DOI:10.1002/masy.200450210
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