| 000 | 02231nam a2200241 a 4500 | ||
|---|---|---|---|
| 001 | vtls000075732 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204541.0 | ||
| 008 | 131025t2013 my da f abm 000 0 eng d | ||
| 020 | _aTHE0002025(Local) | ||
| 039 | 9 |
_a201905131608 _byusri _y201310251352 _znabilah |
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| 040 | _aUMP | ||
| 090 | _aQA278.5 .A35 2013 rs Bc. | ||
| 100 | 0 | _aNur Afifah Hassan | |
| 245 | 1 | 0 |
_aEnhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process / _cNur Afifah Hassan |
| 260 |
_aKuantan, Pahang : _bUMP, _c2013 |
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| 300 |
_axvi, 62 p. : _bill. ; _c30 cm. + _e1 CD-ROM |
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| 502 | _aProject paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang – 2013 | ||
| 504 | _aBibliography : p. 56-58 | ||
| 520 | 3 | _aThis research is about enhancement of PCA-based fault detection system through utilizing dissimilarity matrix. Nowadays, the chemical process industry is highly based on the non-linear relationships between measured variables. However, the conventional PCA-based MSPC is no longer effective because it only valid for the linear relationships between measured variables. Due in order to solve this problem, the technique of dissimilarity matrix is used in multivariate statistical process control as alternative technique which models the non-linear process and can improve the process monitoring performance. The conventional PCA system was run and the dissimilarity system was developed and lastly the monitoring performance in each technique were compared and analysed to achieve aims of this research. This research is to be done by using Matlab software. The findings of this study are illustrated in the form of Hotelling’s T2 and Squared Prediction Errors (SPE) monitoring statistics to be analysed. As a conclusion, the dissimilarity system is comparable to the conventional method. Thus can be the other alternative ways in the process monitoring performance. Finally, it is recommended to use data from other chemical processing systems for more concrete justification of the new technique. | |
| 650 | 0 | _aPrincipal components analysis | |
| 999 |
_aVIRTUA40 _c3970 _d3976 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992 | ||