Transcript An Intelligent Tool for Set Point Prediction and

An Intelligent Tool for Set
Point Prediction and Diagnostics
for Steam and Condensate System
of a
Paper Machine
Narendra Gadwal
Forbes Marshall Pvt. Ltd.
Copyright © 2014. Forbes Marshall Private Limited. All Rights Reserved.
Flow of Presentation
Problem Definition/Objective
Possible Reasons
Proposed Solution
Methodology
Site Results
Objective
• To maintain the performance of the S&C system of a paper machine
within optimum limits.
• The performance parameter is Specific Steam Consumption (SSC)
Current
SSC
Desired
Optimum
Limits
Time
Performance Hampering Factors
• Variety of grades of paper
• Shift changes
• Different operators handling the machine
• Paper breaks
• Incorrect pressure and differential pressure set points
• Condensate logging
• Excessive venting of steam
Solution Approach
• Development of a tool exclusively for Steam and Condensate system
• Inputs from user – moisture values, GSM range, base line values of drive loads and dryer surface
temperatures
• Define the SSC limits based on steam to water ratios as per TAPPI standards
• Gather S&C data, synchronize the tool with the paper machine and understand the behavior of
various parameters on the performance
• Predict the pressure and differential pressure set points to operate the machine within optimum
limits
• Provide the diagnostics whenever the paper machine underperforms
Solution
To predict pressure and differential pressure set points
based on historical data
To troubleshoot the underperformance of the machine
and prescribe the necessary actions
System Architecture
Intelligent Tool
integrated
PLC-SCADA/DCS
Predicted Set Points
Diagnostics
Steam and Condensate System
Set Point Prediction
Paper Grades,
Moisture
Values from
the user
Artificial
Neural
Network
(ANN)
S&C data
from the
paper
machine
Steam to
Water ratio as
per TAPPI
standards
Set Point
Predictor
Pressure,
Differential Pressure
Advance
Data
Analysis
Set Point Prediction: ANN
Hidden
Inputs
w1
GSM
w2
w8
Outputs
w9
w3
w10
P
w4
Speed
w5
w11
dp
Season
w6
w12
w7
Set Point Prediction: Development of ANN
Collection of data
Sorting of data
Select a network module
Train the network with
sorted data
ANN
7/20/2015
10
Set Point Prediction: ANN Limitations
• Selecting the transfer functions, determining the weights is a time
consuming process
• Large Number of inputs makes the network unstable
• Single ANN cannot consider for all the grade changes
Set Point Prediction: Advance Data Analysis
Collection of data
Sorting of data
Data Filtering
Data Processing
Set Point
7/20/2015
12
Diagnostics
Whenever the paper machine’s SSC exceeds the maximum limit, the
diagnostic part gets activated
Monitoring Parameters:
• Pressure , differential pressure set points
• Drive loads/Dryer surface temperatures
• Valve openings
• Paper breaks
Diagnostics
Trouble
Steam consumption
is high
Monitoring
Parameter
Drive Load Current
Observation
Higher than the
base line value
Reason
Condensate
Flooding
Necessary
Action
Increase Differential
Pressure
Features
Automatic
Data
Logging
Easy to
integrate
with S&C
systems
Features
Self
Learning
Improved
accuracy
with time
Benefits
Strengthen
the
Operator
in Set Point
Prediction
Optimum
Performance
Benefits
Diagnostics
Report
Generation
Site Results
Parameter Screen
Site Results
Predicted Set Points
Site Results
Diagnostics Screen
Site Results
Paper Break Information
Site Results
Site Results
SSC
180GSM
Oct-13 to Mar-14
Apr-14 to June-14
Site Results
180GSM
Before Tool Installation
After Tool Installation
Oct-13 to Mar-14
Apr-14 to June-14
Site Results
180GSM
Before Tool Installation
After Tool Installation
Oct-13 to Mar-14
Apr-14 to June-14
Conclusions
• The tool started to predict the set points and is under advance testing
process
• The diagnostics tool is active and allows the operator to control the
steam consumption
• Improvement in SSC
Future Work
• Consider pulp quality effects as inputs
• Coupling of set point prediction tool with the control system
Copyright © 2014. Forbes Marshall Private Limited. All Rights Reserved.