Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy
This paper focuses on the use of artificial neural network (ANN) to detect and diagnose fault in process plant. In this work, the ANN uses two layers of hierarchical diagnostic strategy. The first layer diagnoses the node where the fault originated and the second layer classifies the type of faults...
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| Format: | Article |
| Language: | English English |
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Penerbit Universiti Teknologi Malaysia
2007
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| Online Access: | http://umpir.ump.edu.my/id/eprint/6783/1/Process_Fault_Detection.pdf http://umpir.ump.edu.my/id/eprint/6783/4/fkksa-2007-rizza-Process%20Fault%20Detection.pdf |
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| author | Mohamad Rizza, Othman Mohamad Wijayanuddin, Ali Mohd Zaki, Kamsah |
| author_facet | Mohamad Rizza, Othman Mohamad Wijayanuddin, Ali Mohd Zaki, Kamsah |
| author_sort | Mohamad Rizza, Othman |
| collection | UMP |
| description | This paper focuses on the use of artificial neural network (ANN) to detect and diagnose fault in process plant. In this work, the ANN uses two layers of hierarchical diagnostic strategy. The first layer diagnoses the node where the fault originated and the second layer classifies the type of faults or malfunctions occurred on that particular node. The architecture of the ANN model is founded on a multilayer feed forward network and used back propagation algorithm as the training scheme. In order to find the most suitable configuration of ANN, a topology analysis is conducted. The effectiveness of the method is demonstrated by using a fatty acid fractionation column. Results show that the system is successful in detecting original single and transient fault introduced within the process plant model. |
| first_indexed | 2024-03-06T11:47:29Z |
| format | Article |
| id | UMPir6783 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T11:47:29Z |
| publishDate | 2007 |
| publisher | Penerbit Universiti Teknologi Malaysia |
| record_format | dspace |
| spelling | UMPir67832018-03-09T07:20:29Z http://umpir.ump.edu.my/id/eprint/6783/ Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy Mohamad Rizza, Othman Mohamad Wijayanuddin, Ali Mohd Zaki, Kamsah TP Chemical technology This paper focuses on the use of artificial neural network (ANN) to detect and diagnose fault in process plant. In this work, the ANN uses two layers of hierarchical diagnostic strategy. The first layer diagnoses the node where the fault originated and the second layer classifies the type of faults or malfunctions occurred on that particular node. The architecture of the ANN model is founded on a multilayer feed forward network and used back propagation algorithm as the training scheme. In order to find the most suitable configuration of ANN, a topology analysis is conducted. The effectiveness of the method is demonstrated by using a fatty acid fractionation column. Results show that the system is successful in detecting original single and transient fault introduced within the process plant model. Penerbit Universiti Teknologi Malaysia 2007 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6783/1/Process_Fault_Detection.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/6783/4/fkksa-2007-rizza-Process%20Fault%20Detection.pdf Mohamad Rizza, Othman and Mohamad Wijayanuddin, Ali and Mohd Zaki, Kamsah (2007) Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy. Jurnal Teknologi (Sciences and Engineering), 46. pp. 11-26. ISSN 0127-9696 (print); 2180-3722 (online). (Published) http://www.jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/301/291 |
| spellingShingle | TP Chemical technology Mohamad Rizza, Othman Mohamad Wijayanuddin, Ali Mohd Zaki, Kamsah Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy |
| title | Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy |
| title_full | Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy |
| title_fullStr | Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy |
| title_full_unstemmed | Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy |
| title_short | Process Fault Detection Using Hierarchical Artificial Neural Network Diagnostic Strategy |
| title_sort | process fault detection using hierarchical artificial neural network diagnostic strategy |
| topic | TP Chemical technology |
| url | http://umpir.ump.edu.my/id/eprint/6783/1/Process_Fault_Detection.pdf http://umpir.ump.edu.my/id/eprint/6783/4/fkksa-2007-rizza-Process%20Fault%20Detection.pdf |
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