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Process monitoring using a combination of data driven techniques and model based data validation

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(1)

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, " + , 1" 1 Abstract 1 1 9 1 1 ,: 1 1 1 " 5 1 , 2 ( 1 *" 9 1 , ( * 1 2 " Keywords ; # < < / / < < $ "

Current methods for process monitoring

) 1 " 9 9 1 1 1 1 " / 1 1 1 1 = • 1 2 1 9 , 1 1 <

(2)

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(3)

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(4)

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(5)

9 , , > 1 " " 1 " 1 9 ADB" 1 , 1 1 9 , 9 "

An industrial case study

5 1 1 (1 , 1 *" 5 1 ( > ' E !', D!'F$ > ''5E 8', D 'F$*" 5 1 1 , , , 9 " 2 , , < 1 1 , & ( 9 , * 1 , 9 1 ( * 1 1 " 5 1 9 1 2 " Methodology 1 1 , , 1 1 1 1 1" ) ! 1 9 " ; 8' 1 1 9 D& 1 '&1 "

(6)

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9 A7B & A'B"

Data processing 5 1 9 1 9 1 1 , 1 1 1 " H 1 1 1 1 1 , ( " " , ''I*"5 , 1 ( " *" ( " " * 9 1 > " $ , 9 , 1 9 1 " 9 = 1 1 > 9 1 9 " 5 1 1 1 9 " 5 1 1 9 1 , 9 , 1

(7)

, " H 2 1 9 = 1 9 , 9 2 1 9 9 11 " @ 9 1 , 9 1 1 1 , ( 1 * 9 1 1 ( 9 , , *" 5 , 9 1 9 9 1 9 1 ( 9 , *" 5 1 , > 9 , 1 9 1 9 ( " *< , 1 1 ( 1 * , 9 " H 1 9 , 1 1 1 1 9 1 1 " > 1 6%!! , , 1 1 1 " !!D 9 9 , 9 1 " 5 9 , " 9 1 1 9 , 9 , , 1 1 , ( "!*" @ 9 '& !G " 5 1 , 9 '"'GDI 9 χ " 5 1 9 1 1 ( 1

(8)

, D 1 * 9 1 11 , 9 1 1 " 5 = 9 , 9 , 1 " H 1 1 1 " )> 9 , 2 9 1 9 1 1 1 1 2 1 1 " - 1 , 1 1 , 1 $ 1 " 5 > 9 , , " 5 >1 'I 9 %" 5 9 > , , " H D 9 : 9 , > 1 , " 5 1 1 , = " 1 > 9 (D'I* " 1, 1, 1 ( 'I* !" , 9 9 ( I*

Results and discussions

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(9)

1 1 > , " $ ,

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1 1 , "

Conclusions and perspectives for future work

5 9 2 1 , , 1 " / , 1 = , 1 , 1 " C 9 1 , 1 " H 1 " 5 1 1 , 1 , 1 1 >1 9 1 1 > , " Acknowledgements 5 : 9 , C # (H"@"#"/"5" ) 1 D'D'* References ABJ" -" 5" " # H 1 9 " 9 #" ( * / 9 5 $ 1 ) ) '' AB " " 1 # -" : " ( * $ 1 ) C &;$ ''6

(10)

A!B " " " 5 ; 5 -" : " ( * $ 1 ) C &;$ ''6 A%B =EE999", 1" 1E; " > G ''8 ADB =EE999" ", E E E) @5 G ''8 A6B ) @5 9 3 "D ( * ) @5 / ''6 A8B K" " L = / 1 ?, D / 1 1 1 / , , 3 $ =G & 78 & 768 AGB- C " 1 2 1 3 @ / 1 ) &J !78&% 77! A7B$" " " J J 9 # " $ ?> 77D" A'BH " @ / # ) 77'

(11)

Figures " # H = , ( 9 , * H =@ 1 1 H != , 1 1 H %= 1 = 1 H D =

(12)

H = , ( 9 , * TIME INDEX_M 1/1 1:0 1/1 1:10 1/1 1:21 1/1 1:32 1/1 1:43 1/1 1:54 1/1 2:5 1/1 2:16 1/1 2:27 1/1 2:38 40 48 56 64 72 80 88 96 104 112 120 Non validatedKPI

(13)

H =@ 1 1 Cooling water flow (T/h) Estimation of cooling water flow (T/h)

0 1 2 3 4 5 6 7 8 9 2 3 4 5 6 7

8 ( Correlation factor : 3,242E-1 ) $

(14)

Validated Efficiency (%) Efficiency Soft Sensor (%)

79 80 81 82 83 84 85 86 87 88 79 80 81 82 83 84 85 86 87

88 ( Correlation factor : 9,987E-1 )

Validated Efficiency (%) Efficiency Soft Sensor (%)

79 80 81 82 83 84 85 86 87 88 79 80 81 82 83 84 85 86 87

88 ( Correlation factor : 9,987E-1 )

(15)

Efficiency (%) Nb. Objects 79 80 81 82 83 84 85 86 0 65 130 195 260 325 390 455 520 585 650 Efficiency (%) Nb. Objects 79 80 81 82 83 84 85 86 0 65 130 195 260 325 390 455 520 585 650 H %= 1 = 1

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yesGAZ_MIX_LHVWT_V < 2927,905no TOP-NODE yes no GAZ_MIX_LHVWT_V > 2745,7349 T2 yes no GAZ_MIX_LHVWT_V < 3439,035 T54 yes no FUM_ECO_T_V > 349,53 T55 yes no C12FUTSOR_V > 195,055 T85 T86 T104 T56 T68 yes no C12FUTSOR_V > 237,015 T3 yes no FUME_COM_T_V > 1388,0701 T40 T41 T42 T4 T19 yesGAZ_MIX_LHVWT_V < 2927,905no TOP-NODE yes no GAZ_MIX_LHVWT_V > 2745,7349 T2 yes no GAZ_MIX_LHVWT_V < 3439,035 T54 yes no FUM_ECO_T_V > 349,53 T55 yes no C12FUTSOR_V > 195,055 T85 T86 T104 T56 T68 yes no C12FUTSOR_V > 237,015 T3 yes no FUME_COM_T_V > 1388,0701 T40 T41 T42 T4 T19 H D =

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