Plant-wide disturbance
assessment with an application
on a paper making process
Zhang Di, M.Sc, Cheng Hui, M.Sc, Jämsä-Jounela
Sirkka-Liisa, Professor
29 Jan, 2009
15th Nordic Process Control Workshop
Contents:
1
Introduction
 2 Plant-wide disturbance detection
 3 Root cause diagnosis
 4 Methodology for plant-wide disturbance
assessment
 5 Case study on Paper making process
 6 Results
2
1 Introduction:
 There
are many pieces of process equiment
and control loops in one typical industrial
plant, and they interact with each other
instead of isolating from each other.
 So disturbance may propagate through the
plant and affect a large number of process
variables, evolving into a plant-wide
problem.
 The widespread nature of the disturbacne
then makes it difficult to identify its orgin.
3
1 Introduction:
A plant-wide approach means the
distrbution of a distrubance is mapped out,
and the location and nature of the cause of
the disturbance are determined with a high
probability of being right first time .
 The alternative is a time consuming
procedure of testing each control loop in
turn until the root cause is found.

4
Contents:
1
Introduction
 2 Plant-wide disturbance detection
 3 Root cause diagnosis
 4 Methodology for plant-wide disturbance
assessment
 5 Case study on Paper making process
 6 Results
5
2 Plant-wide disturbance detection
More from the single loop disturbance detection,
the plant-wide disturbance detection includes
the identification of clusters of measurements
having similar dynamic behaviour.
Thornhill and Horch (2007)
6
Contents:
1
Introduction
 2 Plant-wide disturbance detection
 3 Root cause diagnosis
 4 Methodology for plant-wide disturbance
assessment
 5 Case study on Paper making process
 6 Results
7
3 Root cause diagnosis
Sources of persistent dynamic plant-wide disturbance
The non-linear sources include:
For example:
 Control valves with excessive static friction
 On-off and split-range control
 Sensors faults
 Process non-linearities leading to limit cycles
 Hydrodynamic instability such as slugging flows
The linear sources include:
 Poor controller tuning
 Controller interaction
 Structural problems involving recycles
8
3 Root cause diagnosis

Diagnosis has two objectives, the identification
and the isolation of the disturbance.
9
Thornhill and Horch (2007)
Contents:
1
Introduction
 2 Plant-wide disturbance detection
 3 Root cause diagnosis
 4 Methodology for plant-wide disturbance
assessment
 5 Case study on Paper making process
 6 Results
10
4 Methodology for plant-wide
disturbance assessment
11
Contents:
1
Introduction
 2 Plant-wide disturbance detection
 3 Root cause diagnosis
 4 Methodology for plant-wide disturbance
assessment
 5 Case study on Paper making process
 6 Results
12
Testing environment :APROS interface
The basis weight valve is under concern
because the poor performance caused by
the malfunction of valves is quite common
in industry.
13
V1
V2
5
0
-5
V3
5
0
-5
V4
5
0
-5
5
0
-5
V7
V6
5
0
-5
V5
5 Case study on Paper making process
Measurement
5
0
-5
5
0
-5
0
50
100
150
200
250
300
350
400
450
500
0
50
100
150
200
250
300
350
400
450
500
0
50
100
150
200
250
300
350
400
450
500
0
50
100
150
200
250
300
350
400
450
500
0
50
100
150
200
250
300
350
400
450
500
0
50
100
150
200
250
300
350
400
450
500
0
50
100
150
200
250
i
300
350
400
450
500
14
5 Case study on Paper making process
Disturbance
detection
Power
spectra
15
5 Case study on Paper making process
Root cause
Diagnosis
16
5 Case study on Paper making
process
 In
Choudhury et al. (2004), the existence of
non-linearity in a system can be decided by
the Gaussian test and the nonlinearity test.
 If the signal is non-Gaussian it goes through
another test to determine its linearity.
 The nonlinearity index (NLI) is provided as
shown
2
NLI  | biˆcmax
 (biˆ c 2  2 bicˆ 2 ) |
17
5 Case study on Paper making
process
If the process is identified as linear, the root diagnosis path presented
by Bauer and Thornhill (2007) is applied to find the disturbance
propagation path and to build the causal diagraph.
 Basic idea: To get to know the cause-and-effect relationship through
the time delays between process variables.
 Procedure:
1 Time delay estimation (cross-correlation function)
2 Build the causality matrix
3 Consistency check
It is used to verify and ascertain the results. The limit is N-2.

18
Contents:
1
Introduction
 2 Plant-wide disturbance detection
 3 Root cause diagnosis
 4 Methodology for plant-wide disturbance
assessment
 5 Case study on Paper making process
 6 Results
19
6 Results
Disturbance detection
Process measurements after mean centering and unit deviation scaling
20
6 Results
Disturbance detection
ACF of time series for the seven variables
21
6 Results
Disturbance detection
Power spectra of the seven variables
22
6 Results
linear identification
V1
-6
x 10
2.5
2
NLI  | biˆcmax
 (biˆ c 2  2 bicˆ 2 ) |
Squared bicoherence
2
3.5
1.5
2
NLI  | biˆcmax
 (biˆ c 2  2 bicˆ 2 ) |
3
2.5
1
2
0.5
-3
x 10
1.5
1
0
0.5
3.5
3
2.5
2
1.5
1
-3
x 10
0
0.5
f1
0
f2
Squared Bicoherence calculation for V1
- Basis weight valve opening
23
6 Results
V3
V2
V4
-3
x 10
-3
x 10
0.04
8
7
0.03
6
0.025
0.02
6
5
4
3.5
0.015
7
Squared bioherence
0.035
Squared bicoherence
Squared bicoherence
8
3
3
4
3.5
3.5
3
3
3
2.5
2
2.5
2
2
-3
x 10
1
2.5
0.01
5
2
1.5
-3
x 10
1
2
0
1.5
-3
0.005
x 10
1.5
1
3.5
3
1
0.5
2.5
2
0
1
0.5
3.5
0
3
2.5
0.5
3.5
3
2.5
2
1.5
1
0
0.5
1.5
1
-3
1
0.5
f1
0
0
f2
f1
0
0.5
0
x 10
f1
0
2
1.5
-3
x 10
f2
-3
x 10
f2
V6
V5
V7
-3
x 10
-3
-3
x 10
x 10
8
3.5
8
7
3
7
5
4
3.5
3
3
5
4
3.5
3
3
Squared bicoherence
Squared bicoherence
6
Squared bicoherence
6
2.5
2
1.5
3.5
3
1
2.5
2.5
2
2
0.5
2.5
-3
2
x 10
-3
2
1.5
x 10
2
1
1.5
1
-3
x 10
1
1.5
0
3
0.5
3
2.5
3.5
3
2.5
0.5
2
1.5
1
-3
3.5
3.5
1
0.5
1
0
0
x 10
2.5
2
0
1.5
1
0.5
0
f1
0.5
0
0
f1
f2
-3
2
1.5
1
-3
0
0.5
f1
x 10
f2
0
x 10
f2
24
6 Results: propagation path
1 Causality matrix: 2 Consistency check:
3 Then:
It is used to verify and ascertain the results. The limit is N-2.
25
6 Results: Propagation path
4 The causal map:
The root cause is most likely close to the
variable 1 - Basis weight valve opening
26
Thank you for your attention!