vii
TABLE OF CONTENTS
CHAPTER
1
TITLE
PAGE
TITLE PAGE
i
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENT
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
xii
LIST OF FIGURES
xiv
LIST OF SYMBOLS
xvi
LIST OF ABBREVIATIONS
xx
LIST OF APPENDICES
xxi
INTRODUCTION
1.1 Introduction
1
1.2 Research Background
2
1.3 Objectives of the Research
4
1.4 Scopes of the Research
4
1.5 Contributions of the research
5
1.6 Chapter Summary
5
viii
2
LITERATURE REVIEW
2.1 Introduction
7
2.2 Definitions of Fault, Fault Detection and Fault Diagnosis
8
2.3 Multivariate Statistical Analysis, MSA
9
2.4 Review on Principal Component Analysis, PCA
10
2.4.1
Extension of Principal Component Analysis, PCA
method
2.4.1.1
Multi-Way PCA
2.4.1.2 Multi-Block PCA
15
2.4.1.3 Moving PCA
16
2.4.1.4
17
Dissimilarity, DISSIM
2.4.1.5 Multi-Scale PCA
18
2.4.2 PCA Adopted in Industries
19
2.4.3
20
PCA as Controller
2.4.4 Theory of PCA
2.5 Review on Partial Correlation Analysis, PCorrA
2.5.1 Theory of PCorrA
2.6 Chapter Summary
3
14
21
23
26
27
IMPROVED STATISTICAL PROCESS CONTROL CHART
3.1 Statistical Process Control, SPC
29
3.2 Traditional Statistical Process Control, SPC chart
30
3.2.1
Shewhart Chart
31
3.2.2
Exponential Weight Moving Average, EWMA Chart
35
3.2.3
Moving Average and Moving Range, MAMR Chart
39
3.3 Improve Statistical Process Control Chart
43
3.4 Chapter Summary
45
ix
4
DYNAMIC SIMULATED DISTILLATION COLUMN
4.1 Introduction
46
4.2 Process Description of Precut Column
48
4.3 The Information of Pre-cut column
49
4.4 Degree of Freedom (DoF) Analysis
51
4.5 Formulations of the Distillation Column Models
56
4.5.1
4.5.2
Mass Balance Equations
56
4.5.1.1
Bottom column model
58
4.5.1.2
Trays model
59
4.5.1.3
Reflux drum model
61
4.5.1.4
Pumparound drum model
62
Equilibrium Equations
63
4.5.2.1
66
Bubble Point Calculations
4.5.3
Summation Equation
68
4.5.4
Heat Balance Equation
68
4.5.5
Hydraulic Equations
69
4.6 Dynamic Simulation of the Study Column
70
4.7 Controller Tuning
74
4.7.1
Bottom Liquid Level Controller
75
4.7.2
Bottom Temperature Controller
76
4.7.3
Top Column Pressure Controller
78
4.7.4
Sidedraw Tray Liquid Level Controller
79
4.7.5
Pumparound Temperature Controller
80
4.7.6
Pumparound Flow Rate Controller
81
4.7.7
Reflux Flow Rate Controller
82
4.7.8
Controller Sampling Time, TAPC
82
4.8 Dynamic simulation Program Performance Evaluation
83
4.9 Chapter Summary
84
x
5
METHODOLOGY
5.1 Introduction
86
5.2 Variable Selection for Process Monitoring
87
5.3 Statistical Process Control Sampling Time, TSPC
90
5.4 Normal Operating Condition (NOC) Data Selection and 92
Preparation
5.4.1
Data pretreatment
94
5.4.2
Correlation Coefficient via Multivariate Analysis 94
Techniques
5.4.3
5.4.2.1
Principal Component Analysis, PCA
95
5.4.2.2
Partial Correlation Analysis, PCorrA
101
Control limits of Improved Statistical Process 103
Control, ISPC chart
5.5 Generated Out of Control, OC data
105
5.6 Fault Coding Monitoring Framework
109
5.7 Performance Evaluation of the FDD Method
111
5.7.1
Fault Detection Efficiency
111
5.7.2
Fault Diagnosis Efficiency
112
5.8 Chapter Summary
6
113
RESULTS AND DISCUSSIONS
6.1 Statistical Process Control Sampling Time, TSPC
116
6.2 Normal Operating Condition, NOC Data
117
6.2.1 Correlation coefficient via Principal Component 119
Analysis, PCA
6.2.2
Correlation
coefficient
via
Partial
Correlation 123
Analysis, PCorrA
6.3 Parameters to Design Improved Statistical Process Control 124
chart
6.4 Fault Detection and Diagnosis Method Performance
6.4.1
False alarm Analysis
127
127
xi
6.4.2
Fault Detection Efficiency Results and Results 129
Discussions
6.4.3 Fault Diagnosis Efficiency Results and Results 132
Discussions
6.5 Chapter Summary
7
136
CONCLUSIONS AND RECOMMENDATIONS
7.1 Introduction
138
7.2 Conclusions of Improved SPC framework
139
7.3 Recommendations to Future Research
141
LIST OF REFERENCES
142
APPENDICES
154
xii
LIST OF TABLES
TABLE NO.
TITLE
PAGE
4.1
Specification of the pre-cut column
49
4.2
Components composition and conditions of the pre-cut column
50
4.3
Number of variables
52
4.4
Number of equations
53
4.5
Control loops properties
55
4.6
Cohen-Coon controller settings
75
4.7
The step change results for bottom liquid level controller
76
4.8
Properties of bottom liquid level P controller
76
4.9
The step change results for bottom temperature controller
77
4.10
Properties of bottom temperature PID controller
77
4.11
The step change results for top column pressure controller
78
4.12
Properties of top column pressure PI controller
78
4.13
The step change results for sidedraw tray liquid level controller
79
4.14
Properties of sidedraw tray liquid level P controller
79
4.15
The step change results for pumparound temperature controller
80
4.16
Properties of pumparound temperature PID controller
81
4.17
Properties of pumparound flow rate P controller
81
4.18
Properties of reflux flow rate P controller
82
5.1
APC variables for each control loops
87
5.2
Normal correlation coefficient for process variables
88
5.3
SPC variables
88
xiii
5.4
The control limits of Improved SPC chart
104
5.5
Parameters to design EWMA
105
5.6
Description of sensor fault, valve fault and controller fault
107
5.7
Improved SPC chart statistic for FDD
108
5.8
Coding system for fault detection
109
5.9
Coding system for fault diagnosis
109
5.10
Fault coding system for Shewhart Chart
110
5.11
Fault coding system for EWMA Chart
110
5.12
Fault coding system for MAMR Chart
110
6.1
Time constant for each control loops
116
6.2
The skewness and kurtosis value of NOC data
118
6.3
Summary of the NOC data
118
6.4
Eigenvectors Matrix
119
6.5
Eigenvalues, variation explained by each PC and cumulative
119
variation
6.6
The correlation coefficient using different cumulative variation
121
6.7
The percentage difference for two PCs retained and three PCs
122
retained compared to six PCs
6.8
Simple correlation matrix
123
6.9
The correlation coefficient result using PCorrA
124
6.10
Constant to design Shewhart range chart
124
6.11
FDD result using different L and β to design EWMA chart
125
6.12
FDD result using PCA with different window size to design 126
MAMR chart
6.13
FDD result using PCorrA with different window size to design 126
MAMR chart
6.14
False alarm result corresponding to oleic acid composition
128
6.15
False alarm result corresponding to linoleic acid composition
128
6.16
The known fault causes
129
6.17
The known out of control, OC conditions
130
xiv
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE
2.1
Multi-block PCA monitoring framework
15
3.1
Shewhart range and Shewhart individual chart during normal
34
condition
3.2
Shewhart range and Shewhart individual chart during faulty
34
condition
3.3
EWMA control chart under normal condition
38
3.4
EWMA control chart under faulty condition
38
3.5
Moving average and range control chart under normal condition
42
3.6
Moving average and range control chart under faulty condition
42
3.7
The implementation of correlation coefficient, Cjk in SPC chart
44
4.1
Pre cut column
48
4.2
Distillation column control loop
54
4.3
Distillation column schematic diagram
57
4.4
Bubble point calculation procedure
67
5.1
The procedure to calculate and implement TSPC
92
5.2
Example Scree plot
97
5.3
The procedures to determine correlation coefficient, Cjk via PCA 100
method
5.4
The procedures to determine correlation coefficient, Cjk via 103
PCorrA metho
5.5
The outlined of FDD algorithm
115
xv
6.1
The autocorrelation plot
117
6.2
Histogram plot of NOC data
118
6.3
Scree plot
120
6.4
Fault detection efficiency using different Improved SPC chart
131
6.5
Percentage of faults occurs in different region detected by each 132
Improved SPC chart
6.6
Fault diagnosis situation using PCA for oleic acid composition
133
6.7
Fault diagnosis situation using PCorrA for oleic acid
134
composition
6.8
Fault diagnosis situation using PCA for linoleic acid
134
composition
6.9
Fault diagnosis situation using PCorrA for linoleic acid
composition
135
xvi
LIST OF SYMBOLS
aij
-
Wilson constant
n
-
Number of retained principal component
A
-
Square matrix
Ab
-
Bottom column area
At
-
tray active area
Ai,Bi,Ci
-
Antoine constant for component i
A*,B*,C*,D*
-
Constant for liquid heat capacity
A2, D.'001 , D.'999
-
Constant for MA and MR control limit
β
-
Weighting factor
B
-
Bottom flow rate
Cj,k
-
Correlation coefficient between variable j and variable k
δ
-
Shifted value in standard deviation unit
D
-
Distillate flowrate
FDetect
-
Fault Detection
FDiagnose
-
Fault Diagnosis
∆H vap
-
Heat of vaporization
∆H vap, n
-
Heat of vaporization at normal boiling point
hN
-
Liquid enthalpy leaving each tray
hb
-
Enthalpy for bottom stream
how
-
Over weir height
H, h
-
CuSum control limits
HN
-
Vapor enthalpy leaving each tray
xvii
I
-
Identity matrix
Kc
-
Controller Gain
Kp
-
Static Gain,
L28
-
Liquid flowrate at tray 28
LH, P
-
Pumparound drum height
Lf
-
Liquid feed flowrate
LH, Re
-
Reflux drum liquid level
LH, B
-
Bottom liquid level
L
-
Width of the control limit
M
-
Number of observations
MB
-
Bottom molar hold-up
MW
-
Molecular weight
MRe
-
Reflux drum molar hold-up
MP
-
Pumparound drum molar hold-up
MN
-
Molar hold up at tray N
N
-
Number of stages
p
-
Number of observations
P
-
Pumparound flowrate
Pci
-
Critical pressure of component i
Pi sat
-
Vapor pressure for component i
Ptot
-
Total pressure of the system
ρ
-
Liquid density
QR
-
Reboiler heat duty
Q
-
Number of variables for response variables
R
-
Correlation matrix
rj,k
-
Correlation value between variable j and variable k
Re
-
Reflux flowrate
R
-
Universal gas constant
rk
-
Autocorrelation coefficient
xviii
S
-
Sidedraw flowrate
S
-
Variance-Covariance matrix
sj,k
-
Covariance value of variable j and variable k
s
-
NOC standard deviation
T
-
Temperature of the system
Tci
-
Critical temperature of component i
Tri
-
Reduced temperature of component i
Tb,i
-
Boiling point for component i
TAPC
-
APC sampling time
TSPC
-
SPC sampling time
t, u
-
Latent vectors
τ
-
Time Constant
τD
-
Derivative Time Constant
τI
-
Integral Time Constant
θ
-
Dead time
V
-
Eigenvector matrix
v
-
Eigenvector or loading vectors
V
-
Vapor flowrate
Vci
-
Critical volume for component i
Vi
-
Liquid molar volume of component i
WL
-
Weir length
ω
-
Critical accentric factor of component i
w
-
Un-normalized eigenvectors
x
-
NOC mean
x1
-
Shifted mean
xi
-
ith observation in the process
xij
-
Value of the i-th row and j-th column matrix
xijs
-
Standardized variable
x
-
Liquid phase mole fraction
xix
xS
-
Sidedraw mole fraction
xRe
-
Reflux mole fraction
xP
-
pumparound liquid mole fraction
xD
-
Distillate mole fraction
γi
-
Liquid phase activity coefficient for component i
y
-
Vapor phase mole fraction
zi
-
The ith EWMA statistic
Zci
-
Critical compressibility factor for component i
φi
-
Vapor fugacity coefficient for component i
Λij
-
Wilson binary interaction parameter for component i and j
xx
LIST OF ABBREVIATIONS
APC
-
Automatic Process Control
DoF
-
Degree of Freedom
EWMA
-
Exponential Weight Moving Average
FDD
-
Fault Detection and Diagnosis
ISPC
-
Improved Statistical Process Control
MA
-
Moving Average
MESH
-
Mass, Equilibrium, Summation, Heat
MR
-
Moving Range
MSA
-
Multivariate Statistical Analysis
MSPC
-
Multivariate Statistical Process Control
NIPALS
-
Non-iterative Partial Least Squares
NOC
-
Normal Operating Condition
OC
-
Out of Control
PCA
-
Principal Component Analysis
PCorrA
-
Partial Correlation Analysis
PV
-
Process Variable
QV
-
Quality Variable
SPC
-
Statistical Process Control
USPC
-
Univariate Statistical Process Control
xxi
LIST OF APPENDICES
APPENDIX
TITLE
PAGE
A
Column profile comparison
155
B
Parameter selection to design EWMA chart
158
C
Parameter selection to design MAMR chart
163
D
Number of fault causes
170