1. DeltaV Neural – Lab Entry
Automatic update based on lab or analyzer entry of new samples
Estimates future value of measurement based on current upstream conditions, crystal ball approach
Diagnostics to detect deviation in estimate from new sample value

2. Future Prediction
The trained neural network provides a predicted output into the future
NN block is configured with a ‘FUTURE’ Output and an ‘OUT’
Allows user to perform what-if studies
Valuable in processes with large dead times

3. Future Prediction
‘FUTURE’ is calculated by setting the delays with associated inputs to zero, that is give the steady state solution for the given input values

5. Lab Entry Function Block
Lab Entry (LE) allows lab analysis to be entered and collected in the DeltaV Historian
Time difference between the sample taken and the analysis is entered automatically to reflect the DELAY parameter
Lab value screening and time delay in processing the sample are provided in the LE block

6. Configure LE Open the EX2_SIM with the control studio
Remove the existing input, TT2-4, from the neural network block.
Add LE block, TT2-4LE, and wire as shown

7. Lab Entry, LE, Block Both OUT and DELAY should be wired

10. Lab Entry Modes Manual – Lab entry is passed through to the output
Out of Service – Output is set to Bad
OUT and DELAY parameters will normally be Good Constant when block is in MAN
When new analysis is entered, the status of OUT to Good Not Limited for two executions to indicate a new sample

11. Save and Download both The EX2_SIM control model and the Historian
Complete the wiring
Save and Download both
The EX2_SIM control model and the Historian

12. Add LE block to the Operator Display
Open lab2sim display, quick edit and add the LE block. Browse to locate the specific block
Configure the point with OUT and CV, or current value

15. LE Display Configuration
Save the display and exit
Open the display – Not how to make entries in the LE block

16. Detail Faceplate, Push Lab Entry to enter the data

18. LE experiment
Make changes in the inlet water temperatures and hot flow rate.
Note the temperature out and make the lab entry at various times
Watch for AM and PM
What about daylight saving time?
Retrain the network and check the results

19. Plant LIMS can interface with DeltaV through OPC
OPC, or OLE for Process Control, offers an alternative by defining
a standard set of objects, interfaces and methods for use in process
control and manufacturing automation applications to facilitate
interoperability. LabWare is a member of the OPC Foundation and
LabWare LIMS fully supports the Data Access Specification.
LabWare LIMS Process Windows can display "live" data that
automatically updates when it is changed. The data sources can be
either LIMS results, or OPC tag values.

20. Neural Network Feed Forward Experiment
We will now develop a neural network to compensate for changes in exchanger
We will develop a network that can anticipate the cold water rate required
The network will act as a feed forward calculation

21. Neural Network Feed Forward Experiment
Delete the LE block and the NN1 block before you configure the new block
Be sure to download the Historian before you train the new network!

22. Configure the inputs as shown,
Why do we just want the SP and not the PV?

23. Wire Output of NN block
To FF_VAL of TC2-4

24. For TC2-4 FF_VAL scale 1 to 1.0 GPM FF_GAIN of 1.0

25. Training from a file
In this lab you will train from an existing data file
The file is
EX2_SIM NN_FF save.dat

26. Auto generate from file