Fault detection and isolation for complex system
Fault Detection and Isolation (FDI) is a method to monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A two wheel robot is used as a complex system in this study. The aim of the research is to construct and desi...
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| creator | Jing, Chan Shi Bayuaji, Luhur Samad, R. Mustafa, M. Abdullah, N. R. H. Zain, Z. M. Pebrianti, Dwi |
| description | Fault Detection and Isolation (FDI) is a method to monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A two wheel robot is used as a complex system in this study. The aim of the research is to construct and design a Fault Detection and Isolation algorithm. The proposed method for the fault identification is using hybrid technique that combines Kalman filter and Artificial Neural Network (ANN). The Kalman filter is able to recognize the data from the sensors of the system and indicate the fault of the system in the sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. Additionally, Artificial Neural Network (ANN) is another algorithm used to determine the type of fault and isolate the fault in the system. |
| doi_str_mv | 10.1063/1.4993392 |
| format | Conference Proceeding |
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R. H. ; Zain, Z. M. ; Pebrianti, Dwi</creator><contributor>Shibatomi, Kazutaka ; Jaafar, Mariatti ; Musa, Mohd Kusairay ; Razak, Khairunisak Abdul ; Hussain, Zuhailawati ; Kian, Tan Wai</contributor><creatorcontrib>Jing, Chan Shi ; Bayuaji, Luhur ; Samad, R. ; Mustafa, M. ; Abdullah, N. R. H. ; Zain, Z. M. ; Pebrianti, Dwi ; Shibatomi, Kazutaka ; Jaafar, Mariatti ; Musa, Mohd Kusairay ; Razak, Khairunisak Abdul ; Hussain, Zuhailawati ; Kian, Tan Wai</creatorcontrib><description>Fault Detection and Isolation (FDI) is a method to monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A two wheel robot is used as a complex system in this study. The aim of the research is to construct and design a Fault Detection and Isolation algorithm. The proposed method for the fault identification is using hybrid technique that combines Kalman filter and Artificial Neural Network (ANN). The Kalman filter is able to recognize the data from the sensors of the system and indicate the fault of the system in the sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. Additionally, Artificial Neural Network (ANN) is another algorithm used to determine the type of fault and isolate the fault in the system.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/1.4993392</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Algorithms ; Artificial neural networks ; Complex systems ; Error detection ; Fault detection ; Kalman filters ; MIMO (control systems) ; Neural networks ; Nonlinear systems</subject><ispartof>AIP conference proceedings, 2017, Vol.1865 (1)</ispartof><rights>Author(s)</rights><rights>2017 Author(s). 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Additionally, Artificial Neural Network (ANN) is another algorithm used to determine the type of fault and isolate the fault in the system.</description><subject>Algorithms</subject><subject>Artificial neural networks</subject><subject>Complex systems</subject><subject>Error detection</subject><subject>Fault detection</subject><subject>Kalman filters</subject><subject>MIMO (control systems)</subject><subject>Neural networks</subject><subject>Nonlinear systems</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2017</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNp9kE1LAzEQhoMoWKsH_8GCN2FrJl-bHKXYKhS8KHgL2XzAlt3NusmK_ffWtuDN0zDwvO8MD0K3gBeABX2ABVOKUkXO0Aw4h7ISIM7RDGPFSsLoxyW6SmmLMVFVJWcIr8zU5sL57G1uYl-Y3hVNiq05bCGOhY3d0PrvIu1S9t01ugimTf7mNOfoffX0tnwuN6_rl-XjprRE0VwaJ2pDqBcseBW4MS4ozqWltVFcUs6dwhw8tqQC66mEQKFSltWcOFCS0zm6O_YOY_ycfMp6G6ex35_UBEBgKRmGPXV_pJJt8uFlPYxNZ8ad_oqjBn2yoQcX_oMB6199fwH6A5LLYHk</recordid><startdate>20170721</startdate><enddate>20170721</enddate><creator>Jing, Chan Shi</creator><creator>Bayuaji, Luhur</creator><creator>Samad, R.</creator><creator>Mustafa, M.</creator><creator>Abdullah, N. 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M.</au><au>Pebrianti, Dwi</au><au>Shibatomi, Kazutaka</au><au>Jaafar, Mariatti</au><au>Musa, Mohd Kusairay</au><au>Razak, Khairunisak Abdul</au><au>Hussain, Zuhailawati</au><au>Kian, Tan Wai</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Fault detection and isolation for complex system</atitle><btitle>AIP conference proceedings</btitle><date>2017-07-21</date><risdate>2017</risdate><volume>1865</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>Fault Detection and Isolation (FDI) is a method to monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A two wheel robot is used as a complex system in this study. The aim of the research is to construct and design a Fault Detection and Isolation algorithm. The proposed method for the fault identification is using hybrid technique that combines Kalman filter and Artificial Neural Network (ANN). The Kalman filter is able to recognize the data from the sensors of the system and indicate the fault of the system in the sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. Additionally, Artificial Neural Network (ANN) is another algorithm used to determine the type of fault and isolate the fault in the system.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/1.4993392</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0094-243X |
| ispartof | AIP conference proceedings, 2017, Vol.1865 (1) |
| issn | 0094-243X 1551-7616 |
| language | eng |
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| source | AIP Journals Complete |
| subjects | Algorithms Artificial neural networks Complex systems Error detection Fault detection Kalman filters MIMO (control systems) Neural networks Nonlinear systems |
| title | Fault detection and isolation for complex system |
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