From cast10-request@bevo.che.wisc.edu Tue Mar 14 14:08:18 2000 Received: (from slist@localhost) by bevo.che.wisc.edu (8.9.1/8.9.1) id OAA13946; Tue, 14 Mar 2000 14:08:18 -0600 (CST) Resent-Date: Tue, 14 Mar 2000 14:08:18 -0600 (CST) MIME-Version: 1.0 Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Message-ID: <14542.39985.237388.643694@bahaha.che.wisc.edu> Date: Tue, 14 Mar 2000 14:08:17 -0600 (CST) From: Shankara Narasimhan To: cast10@bevo.che.wisc.edu Subject: CAST: Re new book X-CAST-Category: education book 2000-09 Resent-Message-ID: <"RtD_OtVXT5F.A.JGC.ywpz4"@bevo.che.wisc.edu> Resent-From: cast10@bevo.che.wisc.edu X-Mailing-List: X-Loop: cast10@bevo.che.wisc.edu Precedence: list Resent-Sender: cast10-request@bevo.che.wisc.edu Sender: cast10-request@bevo.che.wisc.edu Errors-To: cast10-request@bevo.che.wisc.edu ----------------------------------------------------------------- NOTE: Past postings on the CAST10 Email List are archived on the World Wide Web at http://www.che.wisc.edu/cast10 ----------------------------------------------------------------- DATA RECONCILIATION AND GROSS ERROR DETECTION: An Intelligent Use of Process Data Shankar Narasimhan Cornelius Jordache Department of Chemical Engineering Simulation Sciences Inc. Indian Institute of Technology, Madras Houston, Texas, USA INDIA GULF HEMISPHERE Control Systems and Instrumentation 350 pages ISBN 0-88415-255-3 Data acquisition systems provide exhaustive information for process engineers. However it is the quality of the data that determine the extent of increased process efficiency. Plant measurements are inevitably corrupted by random fluctuations in the process power supply and ambient conditions. Furthermore, due to miscalibration and hostile process environments, sensors develop offset errors and biases. The techniques of data reconciliation and gross error detection have been developed over the last four decades to improve the accuracy of data by reducing the extent of both random errors and biases in measurements. During the last decade, they have been widely applied in refineries, petrochemical plants, and mineral processing industries. This book provides a systematic and comprehensive treatment of data reconciliation and gross error detection techniques. Simple examples are used to introduce the different concepts and industrial case studies are used to highlight the application potential of these techniques. Related topics such as data filtering and the impact of measurement selection on data reconciliation are also exhaustively explained. The theoretical treatment of the techniques described in this book will be of immense value to researchers. Process and control engineers will be able to utilise this text as a practical guide to the proper selection and application of data reconciliation and gross error detection techniques. The book will also be useful as a supplementary reference for an undergraduate/graduate level course in chemical process instrumentation and control in which basic concepts can be taught or as a text for a full graduate level course in these topics. CONTENTS Chapter 1: The Importance of Data Reconciliation and Gross Error Detection Chapter 2: Measurement Errors and Error Reduction Techniques Chapter 3: Linear Steady State Data Reconciliation Chapter 4: Steady State Data Reconciliation for Bilinear Systems Chapter 5: Nonlinear Steady State Data Reconciliation Chapter 6: Data Reconciliation in Dynamic Systems Chapter 7: Introduction to Gross Error Detection Chapter 8: Multiple Gross Error Identification Strategies for Steady State Processes Chapter 9: Gross Error Detection in Linear Dynamic Processes Chapter 10: Design of Sensor Networks Chapter 11: Industrial Applications of Data Reconciliation and Gross Error Detection Technologies Appendix A: Basic Concepts of Linear Algebra Appendix B: Graph Theory Fundamentals Appendix C: Fundamentals of Probability and Statistics Professor Shankar Narasimhan Department of Chemical Engineering Indian Institute of Technology, Madras INDIA E-mail: naras@acer.iitm.ernet.in Dr. Cornelius Jordache Simulation Sciences, Inc. 2500 City West Blvd. Houston, TX 77042 E-mail: cjordache@simsci.com