Data Reconciliation and Gross Error Detection in Constrained Data Sets of Nonlinear Systems PDF Download
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Author: Richard Oscar Adame
Publisher:
ISBN:
Category : Error-correcting codes (Information theory)
Languages : en
Pages : 228
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Book Description
Author: Richard Oscar Adame
Publisher:
ISBN:
Category : Error-correcting codes (Information theory)
Languages : en
Pages : 228
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Book Description
Author: Shankar Narasimhan
Publisher: Elsevier
ISBN: 0080503713
Category : Business & Economics
Languages : en
Pages : 425
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Book Description
This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustively explained.Data errors can cause big problems in any process plant or refinery. Process measurements can be correupted by power supply flucutations, network transmission and signla conversion noise, analog input filtering, changes in ambient conditions, instrument malfunctioning, miscalibration, and the wear and corrosion of sensors, among other factors. Here's a book that helps you detect, analyze, solve, and avoid the data acquisition problems that can rob plants of peak performance. This indispensable volume provides crucial insights into data reconciliation and gorss error detection techniques that are essential fro optimal process control and information systems. This book is an invaluable tool for engineers and managers faced with the selection and implementation of data reconciliation software, or for those developing such software. For industrial personnel and students, Data Reconciliation and Gross Error Detection is the ultimate reference.
Author: Carlos Manuel Valero
Publisher:
ISBN:
Category : Error-correcting codes (Information theory)
Languages : en
Pages : 146
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Book Description
Author: Hashem Alighardashi
Publisher:
ISBN:
Category : Errors, Scientific
Languages : en
Pages : 0
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Book Description
The intensive competitive nature of the world market, the growing significance of quality products, and the increasing importance and the number of safety and environmental issues and regulations, respectively, have increased the need for fast and low-cost changes in chemical processes to enhance their performance. Any possible changes and modifications in a system in order to control, optimize, evaluate the behavior of the process, or achieve the maximal performance of the system require clear understanding and knowledge of its actual state. This information is obtained by processing a data set - collecting it, ameliorating its accuracy, and storing/using it for further analysis. It should be emphasized that in today's highly competitive world market, increasing the accuracy of measurements by resolving even small errors can result in substantial improvements in plant efficiency and economy. Industrial process measurements play a significant role in online optimization, process monitoring, identification, and control. These measurements are used to make decisions which potentially influence product quality, plant safety, and profitability. Nonetheless, they are inherently contaminated by errors, which may be random and/or systematic/gross errors, due to sensor accuracy, improper instrumentation, poor calibration, process leak, and so on. The objective of data reconciliation and gross error detection is the estimation of the true states and the detection of any faults in the instruments which could seriously degrade the performance of the system. Data reconciliation techniques deal with the problem of improving the accuracy of raw process measurements and their application allows optimal adjustment of measurement values to satisfy material and energy constraints. These methods also make possible estimation of the unmeasured variables. However, data reconciliation approaches do not always provide valid estimates of the actual states, and the presence of gross errors in the measurements significantly affect the accuracy levels that can be accomplished using reconciliation. Therefore, the main focus of this work is to develop a framework to obtain the accurate estimates of reconciled values while reducing the impact of gross errors. In reality, operating conditions under which a process works change with different circumstances. Therefore, it is vital to develop a model that is capable of identifying and switching between operating regions. To this end, a method is proposed for simultaneous gross error detection and rectification of a data set which contains different operating regions. First, the data set is divided into several clusters based on the number of operating regions. Then, the same operation, i.e., data rectification is performed on each operating region. It must be noted that all of the proposed approaches in this thesis do not require to preset the parameters of the error distribution model, rather they are determined as part of the solution. They are also applicable to problems with both linear and nonlinear constraints, in addition to the ability to determine the magnitude of gross errors. Furthermore, these methods/approaches detect partial gross errors, so it is not required to assume that gross errors exist in the entire data set. Finally, the performance of the proposed methods is verified through various simulation studies and realistic examples.
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Author: Shankar Narasimhan
Publisher:
ISBN: 9781615836574
Category : Automatic data collection systems
Languages : en
Pages : 406
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Book Description
: Introduction. Measurement Errors and Error Reduction Techniques. Steady State Data Reconciliation for Bilinear Systems. Nonlinear Steady State Data Reconciliation. Data Reconciliation in Dynamic Systems. Introduction to Gross Error Detection. Multiple Gross Error Identification Strategies for Steady State Processes. Gross Error Detection in Dynamic Processes. Design of Sensor Networks. Industrial Applications of Data Reconciliation and Gross Error Detection Technologies. Appendix A: Basic concepts of linear algebra. Appendix B: Basic concepts of Graph Theory. Appendix C: Statistical Hypotheses Testing.
Author: Ramesh Kanakasabapathy
Publisher:
ISBN:
Category : Error-correcting codes (Information theory)
Languages : en
Pages : 424
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Book Description
Author: Rita Maria de Brito Alves
Publisher: Elsevier
ISBN: 0080963277
Category : Science
Languages : en
Pages : 1229
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Book Description
The 10th International Symposium on Process Systems Engineering, PSE’09, will be held in Salvador-Bahia, Brazil, on August 16–20, 2009. The special focus of PSE 2009 is Sustainability, Energy, and Engineering. PSE 2009 is the tenth in the triennial series of international symposia on process systems engineering initiated in 1982. The meeting brings together the worldwide PSE community of researchers and practitioners who are involved in the creation and application of computing-based methodologies for planning, design, operation, control and maintenance of chemical and petrochemical process industries. PSE’09 will look at how PSE methods and tools can support sustainable resource systems, emerging technologies in the areas of green engineering, and environmentally conscious design of industrial processes. - sustainable resource systems - emerging technologies in the areas of green engineering - environmentally conscious design of industrial processes
Author: Anton A. Kiss
Publisher: Elsevier
ISBN: 0128186356
Category : Computers
Languages : en
Pages : 1892
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Book Description
The 29th European Symposium on Computer Aided Process Engineering, contains the papers presented at the 29th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Eindhoven, The Netherlands, from June 16-19, 2019. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. Presents findings and discussions from the 29th European Symposium of Computer Aided Process Engineering (ESCAPE) event
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 568
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Book Description
Author: Rita Maria de Brito Alves
Publisher: Elsevier
ISBN: 0444534350
Category : Science
Languages : en
Pages : 1229
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Book Description
The 10th International Symposium on Process Systems Engineering, PSE'09, will be held in Salvador-Bahia, Brazil on August 16-20, 2009. The special focus of PSE 2009 is Sustainability, Energy and Engineering. PSE 2009 is the tenth in the triennial series of international symposia on process systems engineering initiated in 1982. The meeting is brings together the worldwide PSE community of researchers and practitioners who are involved in the creation and application of computing-based methodologies for planning, design, operation, control and maintenance of chemical and petrochemical process industries. PSE'09 will look at how the PSE methods and tools can support sustainable resource systems and emerging technologies in the areas of green engineering: environmentally conscious design of industrial processes. PSE methods and tools support: - sustainable resource systems - emerging technologies in the areas of green engineering - environmentally conscious design of industrial processes
