A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks
Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN). In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN) which is able to detect and isolate single faulty...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Petroleum University of Technology
2017-01-01
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| Series: | Iranian Journal of Oil & Gas Science and Technology |
| Subjects: | |
| Online Access: | http://ijogst.put.ac.ir/article_44384_1ce8d36de47de45f6ebd2dbe071373af.pdf |
| _version_ | 1818257013328576512 |
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| author | Hamidreza Mousavi Mehdi Shahbazian Nosrat Moradi |
| author_facet | Hamidreza Mousavi Mehdi Shahbazian Nosrat Moradi |
| author_sort | Hamidreza Mousavi |
| collection | DOAJ |
| description | Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN). In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN) which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications. |
| first_indexed | 2024-12-12T17:36:54Z |
| format | Article |
| id | doaj.art-012a4cbc486944d488567b6d1cd2a510 |
| institution | Directory Open Access Journal |
| issn | 2345-2412 2345-2420 |
| language | English |
| last_indexed | 2024-12-12T17:36:54Z |
| publishDate | 2017-01-01 |
| publisher | Petroleum University of Technology |
| record_format | Article |
| series | Iranian Journal of Oil & Gas Science and Technology |
| spelling | doaj.art-012a4cbc486944d488567b6d1cd2a5102022-12-22T00:17:10ZengPetroleum University of TechnologyIranian Journal of Oil & Gas Science and Technology2345-24122345-24202017-01-0161779210.22050/ijogst.2017.4438444384A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural NetworksHamidreza Mousavi0Mehdi Shahbazian1Nosrat Moradi2M.S. Student, Department of Instrumentation & Automation Engineering, Petroleum University of Technology, Ahwaz, Iran.Petroleum university of technologyIranian Offshore Oil CompanyRecently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN). In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN) which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.http://ijogst.put.ac.ir/article_44384_1ce8d36de47de45f6ebd2dbe071373af.pdfsensor faultfault isolationreconstruction algorithmauto-associative neural networksmultiple faults |
| spellingShingle | Hamidreza Mousavi Mehdi Shahbazian Nosrat Moradi A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks Iranian Journal of Oil & Gas Science and Technology sensor fault fault isolation reconstruction algorithm auto-associative neural networks multiple faults |
| title | A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks |
| title_full | A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks |
| title_fullStr | A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks |
| title_full_unstemmed | A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks |
| title_short | A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks |
| title_sort | self reconstructing algorithm for single and multiple sensor fault isolation based on auto associative neural networks |
| topic | sensor fault fault isolation reconstruction algorithm auto-associative neural networks multiple faults |
| url | http://ijogst.put.ac.ir/article_44384_1ce8d36de47de45f6ebd2dbe071373af.pdf |
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