000 02337nam a2200253 a 4500
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003 KUKTEM
005 20251114204548.0
008 131007t2012 my da f m 000 0 eng d
020 _aTHE0002018(Local)
039 9 _a201905131606
_byusri
_c201311141158
_dnabilah
_c201310231014
_dnabilah
_y201310071259
_znabilah
040 _aUMP
090 _aQA278 .S68 2012 rs Bc.
100 0 _aSouven Jawa Steward Gima
245 1 0 _aMultivariate statistical process monitoring based on dissimilarity matrix /
_cSouven Jawa anak Steward Gima
260 _aKuantan, Pahang :
_bUMP,
_c2012
300 _axiii, 49 p. :
_bill. ;
_c30 cm. +
_e1 CD-ROM
502 _aProject paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang – 2012
504 _aBibliography : p. 35-37
520 3 _aThis thesis mainly deals with the development of new technique in process monitoring which integrates dissimilarity matrix together with the traditional technique which is the conventional Principal Component Analysis (cPCA). From previous research, it is concluded that the cPCA technique itself is not effective when the process variables of the particular process is non-linearly correlated. Specifically, the cPCA cannot detect a change of correlation among process variables as long as the monitored indexes are inside the control limits. The new technique which is dissimilarity integrated with PCAbased Multivariate Statistical Process Monitoring (MSPM), was developed by using Matlab. By using the software, two runs are executed which are based on the traditional technique and the new technique respectively. The data used is based on the simulation of CSTR system and two faults are tested with both abrupt and incipient types of faults are taken into account. The final results are projected in form of Hotelling’s T2 and Squared Prediction Error (SPE) monitoring statistics to be analyzed. Significantly, the cPCA can detect fault introduced into the system earlier if compared to the new technique specifically for incipient faults. Nevertheless, both methods are able to perform fault detection equally well for abrupt faults.
650 0 _aMultivariate anlaysis
650 0 _aPrincipal component analysis
999 _aVIRTUA40
_c4157
_d4163
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992