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Extensions to the data reconciliation procedure
Bibliogaphy: leaves 148-155.
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| Format: | Thesis |
| Language: | English |
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Department of Mechanical Engineering
2014
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| _version_ | 1867613196246843392 |
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| access_status_str | Open Access |
| author | Seager, Mark Thomas |
| author2 | Swartz, C L E |
| author_browse | Seager, Mark Thomas Swartz, C L E |
| author_facet | Swartz, C L E Seager, Mark Thomas |
| author_sort | Seager, Mark Thomas |
| collection | Thesis |
| description | Bibliogaphy: leaves 148-155. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/9255 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:17.361Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Department of Mechanical Engineering |
| publisherStr | Department of Mechanical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/9255 Extensions to the data reconciliation procedure Seager, Mark Thomas Swartz, C L E Engineering Bibliogaphy: leaves 148-155. Data reconciliation is a method of improving the quality of data obtained from automated measurements in chemical plants. All measuring instruments are subject to error. These measurement errors degrade the quality of the data, resulting in inconsistencies in the material and energy balance calculations. Since important decisions are based on the measurements it is essential that the most accurate data possible, be presented. Data reconciliation attempts to minimize these measurement errors by fitting all the measurements to a least-squares model, constrained by the material and energy balance equations. The resulting set of reconciled measurements do not cause any inconsistencies in the balance equations and contain minimum measurement error. Two types of measurement error can occur; random noise and gross errors. If gross errors exist in the measurements they must be identified and removed before data reconciliation is applied to the system. The presence of gross errors invalidates the statistical basis of data reconciliation and corrupts the results obtained. Gross error detection is traditionally performed using statistical tests coupled with serial elimination search algorithms. The statistical 'tests are based on either the measurement adjustment performed by data reconciliation or the balance equations' residuals. A by-product of data reconciliation, obtained with very little additional effort, is the classification of the system variables. Unmeasured variables may be classified as either observable or unobservable. An unmeasured variable is said to be unobservable if a feasible change in its value is possible without being detected by the measurement instruments. Unmeasured variables which are not unobservable are observable. Measured variables may be classified as either redundant, nonredundant or having a specified degree of redundancy. Nonredundant variables are those which upon deletion of the corresponding measurements, become unobservable. The remaining measured variables are redundant. Measured variables with a degree of redundancy equal to one, are redundant variables that retain their redundancy in the event of a failure in any one of the remaining measurement instruments. 2014-11-05T17:35:38Z 2014-11-05T17:35:38Z 1996 Master Thesis Masters MSc http://hdl.handle.net/11427/9255 eng application/pdf Department of Mechanical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Engineering Seager, Mark Thomas Extensions to the data reconciliation procedure |
| thesis_degree_str | Master's |
| title | Extensions to the data reconciliation procedure |
| title_full | Extensions to the data reconciliation procedure |
| title_fullStr | Extensions to the data reconciliation procedure |
| title_full_unstemmed | Extensions to the data reconciliation procedure |
| title_short | Extensions to the data reconciliation procedure |
| title_sort | extensions to the data reconciliation procedure |
| topic | Engineering |
| url | http://hdl.handle.net/11427/9255 |
| work_keys_str_mv | AT seagermarkthomas extensionstothedatareconciliationprocedure |