364 Pages
by
CRC Press
362 Pages
by
CRC Press
Also available as eBook on:
This in-depth presentation of current analytical methods for optimal design, selection, and evaluation of instrumentation for process plants is clear, concise, and systematic-providing a valuable tool for improving quality, costs, safety, loss prevention, and production accounting. The author concentrates on determining the optimal set of measured variables and selecting the accuracy and reliability of the corresponding instruments. The goal is to observe and diagnose single and multiple process faults and to obtain sufficiently accurate and reliable estimates of variables of interest while filtering bad data caused by possible instrument malfunction.
1. Plant Data Management o Introduction o Plant Information and Operations Management o Model-Based Monitoring o Quality of Data
2. Instrumentation Design Goals o Introduction o Measured and Key Variables o Selection of Monitoring Variables o Selection of Key Variables in Control o Selection of Measured Variables for Fault Diagnosis o Instrumentation Design Goals o Upgrading of Instrumentation
3. Instrumentation o Introduction o Flow Rate Instrumentation o Level Measurement o Temperature Measurement o Pressure Measurement o Density Measurement o On-Line Process Analyzers o Transmission and Transformation of Signals
4. Errors in Measurement o Introduction o Instrument Properties o Measurement Quality o Sensitivity and Speed of Response o Hysteresis and Dead Band o Calibration Curves o Accuracy of Different Instruments
5. Variable Classification o Introduction o Model o Measurement Equation o Graphs and Flowsheets o Connectivity of Systems o Observability o Redundancy o Linear Systems o Canonical Representation of Linear Systems o System Degree of Redundancy o Quantification of Observability and Redundancy o Graphs and Canonical Matrices o Nonlinear Systems
6. Design and Upgrade of Nonredundant and Redundant Sensor Networks o Introduction o Upgrade and/or Design Goals o Design for Estimability o Design for Estimability Efficiency o Compulsory Measurements and the Upgrade Case o Sensor Networks for Bilinear Systems
7. Data Reconciliation o Data Reconciliation o Background o Linear Data Reconciliation o Steady-State Linear Data Reconciliation o Nonlinear Steady-State Data Reconciliation o Dynamic Data Reconciliation
8. Design of Accurate Sensor Networks o Introduction o Cost-Optimal Design o Multiple Instruments and Hardware Redundancy o Maximum Precision Models o Generalized Maximum Precision Model o Relation Between Sensor Network Models o Solution Procedures for Linear Systems o Parameter Estimation in Nonlinear Systems
9. Precision Upgrade of Sensor Networks o Introduction o Upgrade Options o Cost Benefit Analysis o Upgrade Models Based on Addition of Sensors o Model for Resource Reallocation o Generalized Model for Resource Reallocation and Upgrade
10. Reliability of Nonrepairable Sensor Networks o Introduction o Sensor Service Availability o Sensor Service Reliability o Failure Density and Failure Rate o Markovian Model o Mean Time to Failure o Estimation Availability and Reliability of Variables o Determination of Estimation of Reliability o Estimation Reliability in Nonredundant Systems o Availability, Reliability and Degree of Estimability o System Availability and Reliability
11. Design of Reliable Linear Nonrepairable Sensor Networks o Introduction o Nonredundant Networks Featuring Maximum Reliability o Redundant Networks Featuring Maximum Reliability and Hardware Redundancy o Redundant and Restricted Networks
12. Design of Reliable Bilinear Nonrepairable Sensor Networks o Introduction o Bilinear Multicomponent Systems o Energy Networks
13. Design of Reliable and Cost-Efficient Nonrepairable Sensor Networks o Introduction o Minimum Cost Model o Minimum Number of Sensors Model o Solution Procedure o Relation to Other Models o Limitations of Previous Models o Generalized Maximum Reliability Model
14. Design of Repairable Sensor Networks o Introduction o Failure Intensity o Repair Intensity o Expected Number of Repairs o Maintenance and Total Cost o Residual Precision o Minimum Cost Model
15. Design of Robust Sensor Networks o Introduction o Origin of Gross Errors o Gross Error Handling o Test for Gross Error Presence o Gross Error Detection in Dynamic Data o Reconciliation o Inaccuracy in Gross Error Detection o Multiple Gross Error Identification o Gross Error Size Estimation o Sensor Network Error Detectability o Sensor Network Gross Error Resilience o Robust Sensor Networks o Minimum Cost Model for Robust Networks
16. Genetic Algorithms o Introduction o Genetic Algorithms
17. Design of Sensors for Process Fault Diagnosis o Introduction o Fault Detection, Diagnosis and Alarms o Fault Observability o Fault Resolution o Sensor Network Design o Sensor Location for Fault Observability o Sensor Location for Fault Resolution Index
2. Instrumentation Design Goals o Introduction o Measured and Key Variables o Selection of Monitoring Variables o Selection of Key Variables in Control o Selection of Measured Variables for Fault Diagnosis o Instrumentation Design Goals o Upgrading of Instrumentation
3. Instrumentation o Introduction o Flow Rate Instrumentation o Level Measurement o Temperature Measurement o Pressure Measurement o Density Measurement o On-Line Process Analyzers o Transmission and Transformation of Signals
4. Errors in Measurement o Introduction o Instrument Properties o Measurement Quality o Sensitivity and Speed of Response o Hysteresis and Dead Band o Calibration Curves o Accuracy of Different Instruments
5. Variable Classification o Introduction o Model o Measurement Equation o Graphs and Flowsheets o Connectivity of Systems o Observability o Redundancy o Linear Systems o Canonical Representation of Linear Systems o System Degree of Redundancy o Quantification of Observability and Redundancy o Graphs and Canonical Matrices o Nonlinear Systems
6. Design and Upgrade of Nonredundant and Redundant Sensor Networks o Introduction o Upgrade and/or Design Goals o Design for Estimability o Design for Estimability Efficiency o Compulsory Measurements and the Upgrade Case o Sensor Networks for Bilinear Systems
7. Data Reconciliation o Data Reconciliation o Background o Linear Data Reconciliation o Steady-State Linear Data Reconciliation o Nonlinear Steady-State Data Reconciliation o Dynamic Data Reconciliation
8. Design of Accurate Sensor Networks o Introduction o Cost-Optimal Design o Multiple Instruments and Hardware Redundancy o Maximum Precision Models o Generalized Maximum Precision Model o Relation Between Sensor Network Models o Solution Procedures for Linear Systems o Parameter Estimation in Nonlinear Systems
9. Precision Upgrade of Sensor Networks o Introduction o Upgrade Options o Cost Benefit Analysis o Upgrade Models Based on Addition of Sensors o Model for Resource Reallocation o Generalized Model for Resource Reallocation and Upgrade
10. Reliability of Nonrepairable Sensor Networks o Introduction o Sensor Service Availability o Sensor Service Reliability o Failure Density and Failure Rate o Markovian Model o Mean Time to Failure o Estimation Availability and Reliability of Variables o Determination of Estimation of Reliability o Estimation Reliability in Nonredundant Systems o Availability, Reliability and Degree of Estimability o System Availability and Reliability
11. Design of Reliable Linear Nonrepairable Sensor Networks o Introduction o Nonredundant Networks Featuring Maximum Reliability o Redundant Networks Featuring Maximum Reliability and Hardware Redundancy o Redundant and Restricted Networks
12. Design of Reliable Bilinear Nonrepairable Sensor Networks o Introduction o Bilinear Multicomponent Systems o Energy Networks
13. Design of Reliable and Cost-Efficient Nonrepairable Sensor Networks o Introduction o Minimum Cost Model o Minimum Number of Sensors Model o Solution Procedure o Relation to Other Models o Limitations of Previous Models o Generalized Maximum Reliability Model
14. Design of Repairable Sensor Networks o Introduction o Failure Intensity o Repair Intensity o Expected Number of Repairs o Maintenance and Total Cost o Residual Precision o Minimum Cost Model
15. Design of Robust Sensor Networks o Introduction o Origin of Gross Errors o Gross Error Handling o Test for Gross Error Presence o Gross Error Detection in Dynamic Data o Reconciliation o Inaccuracy in Gross Error Detection o Multiple Gross Error Identification o Gross Error Size Estimation o Sensor Network Error Detectability o Sensor Network Gross Error Resilience o Robust Sensor Networks o Minimum Cost Model for Robust Networks
16. Genetic Algorithms o Introduction o Genetic Algorithms
17. Design of Sensors for Process Fault Diagnosis o Introduction o Fault Detection, Diagnosis and Alarms o Fault Observability o Fault Resolution o Sensor Network Design o Sensor Location for Fault Observability o Sensor Location for Fault Resolution Index
Biography
Miguel J. Bagajewicz
