Emerson Exchange 3D plots Process Analysis

Process Analysis Using 3D Plots Dr. Frank Seibert, University of Texas

Presenters
Frank Seibert, University of Texas
Terry Blevins, Principal Technologist
Julian Post,
Paul Muston,
Mark Nixon

Introduction
The benefits of 3-D plots in data analysis and history collection of array parameters have been demonstrated in a field trial. In this presentation we addressed:
Target applications – Analysis of high speed processes, distributed processes and data from spectral analyzers.
Historian modifications/design for support of arrays data.
Web enabled 3-D plotting, how array support was used to improve update performance.
Field Trial at University of Texas, Pickle Research Center where absorber temperatures were analyzed during startup 3-D plotting and .
The technical feasibility of providing 3-D plotting and historian collection of array data has been explore and the value of such a capability proven in two of the target application.

Analysis of High Speed Data Analysis
DeltaV supports measurement and control execution at speed as fast as100 msec.
To enable samples as fast as 100msec to be trended and analyzed, samples may be collected at the controller as an data set/ array and communicated to the historian.
Values are saved in historian and accessed as though they had been reported at the module execution rate.
Module executing at 100msec was created to place high speed data into an array parameter. Arrays communicated at a much slower rate e.g. once per 2 sec.
Controlle r Historian Application station Analysis Tools e.g. Entech Toolkit Profession /Operator Station Standard Trend – 100msec Resolution Array/Data Set

Distributed Process
Temperature and/or pressure distribution across a process unit is often important from an operation perspective.
Univariate plots are ineffective in finding problems
3-D plots show relationship of measurements and how this relationship changes with time
TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT

Spectral Analyzers
Spectral analyzers may be used at critical points throughout the process.
Pharmaceutical - inspection of feedstock, blend uniformity, granulation, drying and coating and particle size analysis . Online QA/QC tool for production.
Chemical - acid value, adhesive content, cure, melt index, and polymer processes -reaction monitoring
Refinery, petrochemical - fuel production monitoring
A wide variety of commercial on-line, at-line, and laboratory spectral analyzers are available.
Calibration of an NIR analyzer is based on use of spectral data to develop principal component analysis(PCA) and projection of latent structures (PLS) models.

Example: NIR Analyzers
Careful development of a set of calibration samples and their use in PCA/PLS model development is the basis for near-infrared analytical methods.
For purposes of analysis, the spectral data for a sample should be saved and accessed as one set of data e.g. an array .
3-D plotting of spectral data can be helpful in screening samples and in analyzing on-line use of spectral data.
Off-line PCA/ PLS Model Development On-line Quality Parameter Prediction Historian Array/Data Set Application station NIR Analyzer Controller VIM Interface 3-D Plot of Spectral Data

Field Trial - DvCH Array Handling Enhancement
All samples for an array are held in the database under a single tag, to enable high access speed (minimization of seek times) or logical grouping of data (e.g. spectral analysis)
Implementation caters for use of successive elements of array for different measured variables or of the same measured variable (high speed trending)
Designed also for use of 2-D array to hold several successive scans of several different measured variables
2-D array, variable per column Variable per row entry Single Variable Time Time

Time tagging in Controller
Array time tagging at Controller – high resolution, improving time-stamp accuracy
Faster sampling rates possible (scan periods down to 100ms)
PHV display of array tag

Field Trial Design Considerations
Designed to allow full incorporation in DvCH product
Existing facilities to be supported for each individual measured variable in scanned array, as if configured individually for history collection
Existing read of tag for specified interval, applied to tag for first element of array, gives all samples for array within time interval in time-stamp order (including array index part) so
Samples in time order
Samples at same time in array-index order
Hence DvCH clients (e.g. PHV, DeltaV Reporter and OPC HDA) can meaningfully access history without code change. (See PHV display on previous slide).
Easy to extend client-interface for individual measured variable access etc. e.g. 3-D plotting app

3D Plotting Technology
Various approaches may be taken in visualizing 3D data. Surface Plot, Bar Plot , Series Plot , Line Plot, Scatter Plot, Wirefame Plot, Mesh Plot
Limited number of commercially available components for use with a web browser.
Wire frame plot has may advantages in viewing and analyzing date.
3D Bar Plot 3D Wire Frame and Surface Plot

3D Plot Capability for Field Trial
A 3-D wire frame plot component was selected for the field trial.
Used to visualize absorber temperatures collected by the historian as array data.
Interface may be accessed using web browser .
3-D plot interface supports rotation and easy access to individual measurement values

Controls Provided for 3D Plot
Selection of Absorber or Stripper
3D views from different angles
Selection of time span and resolution
Move back in forth in time
Array data used for 3D plots was saved in DeltaV Continuous Historian

3D Views Supported View1 View2 View3

Time Span Selections 1 Hour 15 Minute 4 Hour

SRP CO2 Capture Pilot Plant
Gas Capacity, m 3 /min = 25
Solvent Capacity, liter/min = 130
Inlet CO2 Composition, mol% =1-20
Capabilities:
- Solvent Screening
- Packing Performance
- Effect of Absorber Inter-cooling
- Solvent Regeneration Variations
- Evaluate Process Dynamics
- Evaluate Heat Exchangers
- Model Validation

Field Trial - UT/SRP CO2 Capture Process

Stripping Column
Column Diameter, cm = 42.8
Packed Height, cm = 600
Pressure, bar = 0.2-4
Provides for Flashing Feed
Windows for Observation
Kettle Reboiler
Shell and Tube Condenser
Plate and Frame Cross Exchanger
11 bar Saturated Steam
10 C Chilled Water

Absorption Column
Column Diameter, cm = 42.8
Packed Height, cm = 600
Pressure, bar = 1
Windows for Observation
Inter-cooling Capability
Extensive Temperature Measurements

Absorber Intercooling Process Flowsheet

Absorber Intercooler Skid

Absorber: No Intercooling

Absorber Intercooling Operation

MEA Absorber Temperature Profile L/G = 4.8 (lb/lb), 415 ACFM, 0.3 Lean Loading No Intercooling 86.5% Removal, Run 1 Intercooling (40 ° C) 93% Removal, Run 2

MEA Absorber Temperature Profile L/G = 2.1 (lb/lb), 500 ACFM, 0.2 Lean Loading No Intercooling 83.2% Removal, Run 11 Intercooling (40 ° C) 82.5% Removal, Run 12

Effect of Absorber Inter-cooling Parameter Without Inter-cooling With Inter-cooling % CO2 Removal 87 93 Stripper Efficiency, kJ/kg CO 2 4,170 4,015

Absorber 8-27-2010 1:27-5:25pm View 1

Absorber 8-27-2010 1:27-5:25pm View 2

Absorber 8-27-2010 1:27-5:25pm View 3

Absorber 8-27-2010 4:27 – 8:25pm View 1

Absorber 8-27-2010 4:27 – 8:25pm View 2

Absorber 8-27-2010 4:27 – 8:25pm View 3

Stripper 8-27-2010 1:28 – 5:28pm View 1

Stripper 8-27-2010 2:28 – 6:28pm View 2

Stripper 8-27-2010 2:28 – 6:28pm View 3

Stripper 8-27-2010 3:28 – 8:26pm View 1

Stripper 8-27-2010 4:28 – 8:26pm View 2

Stripper 8-27-2010 4:28 – 8:26pm View 3

Business Results Achieved
3-D plots and historian support of array data is being used to analyze absorber column temperature variation during startup. It is expected that insight gained through the use of 3-D plotting on-line will lead to a reduction in startup time
Analysis of high speed data associated with liquid pressure/flow loops is planned and should lead to improvements in the process operations.

Summary
3-D plotting based on historian collection of array data can be used to analyze distributed process and spectral data.
Trending of high speed data is possible if data is collected at the controller in an array.
The benefits of 3-D plotting of absorber temperature and trending of high speed data will be demonstrated at the UT Pickle Research Center.
Field trial work to demonstrate 3-D plotting and historian collection of array data sets a foundation for future enhancement in DeltaV.

Questionnaire

http://www.emersonprocessxperts.com	40
http://modelingandcontrol.com	32
http://www.modelingandcontrol.com	31
http://majec.com	2
http://knowledge.deltav.com	2
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Emerson Exchange 3D plots Process Analysis

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Emerson Exchange 3D plots Process Analysis — Webinar Transcript