The OPC Logger: Triggers and Spanning Functions

1. The OPC Logger:Triggers and Spanning Functions Team MU: (-1) Michael Anders Kathleen O’Malley Kharel Thompson

2. Problem of Interest • For most experiments run in DPCL, data is analyzed from graphs. • All process variables shown on the graph – cluttered and difficult to read! • Need better way to collect data and store information for analysis.

3. What is the OPC Logger? • OPC is the industry leader in data collection technology. • Relatively inexpensive • Compatible with multitude of software, including DeltaV control • Offers several key functions including triggers and spanning functions • Easy to set up and operate

4. Triggers • Triggers are functions set up to control when the data gets logged • Start and stop logging based on times and conditions • Scheduled, Recurring, and Monitored Item options • Can perform sampling, batch runs, alarm runs • Your data when and where you want it!

5. Spanning • Spanning records the data with a date and time stamp • Helps keep data organized • Aids reading of data • Assists in observing trends and patterns • Know when your data took place!

6. Execution • Plan of Action • Familiarize group with OPC Logger with Help file and Professor Heider’s assistance • Set up triggers for Experiments #1, 2, and 3 • Set up spanning for same three experiments • Ensure file with logging data opened in Microsoft Excel

7. OPC Logger Screen Shots

8. How to Set Up Spanning • Go to the TextFileLogger • Select the spanning tab • Input the appropriate data • Spanning • Takes the data at specified intervals • Intervals are 5 secs for our purposes • Select format for displaying time

9. How to Set Up Triggers • Select Trigger type: • Scheduled • Recurring • Monitored • Create an OPC boolean block inside the Delta V control studio • Input appropriate conditions for the boolean • Input expression for the variables

10. Trigger Box

11. Delta V Block

12. New Delta V Block • Use conditional block! • Input condition using editor…set variable of interest greater than some number. • When this occurs, the output of the box will be 1 and trigger will start. • If condition not met, the output of the box is 0 and the trigger does not start.

13. Experiment One Overview • We are controlling the level and pressure in the tank for experiment one. • The controllers used are the level and pressure controllers.

14. Experiment One: Excel Data

15. Experiment Two Overview • In experiment two, we have a cross-flow heat exchanger. • We have two inputs, hot water and cold water. • We can control the output temperature of the water stream by varying the flow of the input cold and hot water streams.

16. Experiment Two: Excel Data

17. Experiment Three Overview • In experiment three, we maintain constant flow to a particular valve by varying the incoming flow from two upstream valves.

18. Experiment Three: Excel Data

19. Conclusions • Benefits • Data from first three experiments logged to Excel file • Graphs can be generated from data for specific items of interest • Time stamp on each data point • Triggered logging allows for collection only when necessary

20. Industry Use of the OPC Logger • OPC DataLogger has been around as a product for 6 years and is in use in Asia, Australia, Africa, Europe, & North America by major global users. • Some industrial users are: • AK Steel • Atlas Copco • Baxter Healthcare • Delta Corporation • Dow Chemical • General Electric • Georgia Pacific • Morningstar Foods • Nasa • Pfizer • Siemens • Sony • Southwest Gas • Veolia Water • Verso Paper http://www.opcdatalogger.com/html/users.html

21. Group Responsibilities • Michael Anders • Assisted with initial setup of triggers • Helped in preparation of Power Point slides. • Kathleen O’Malley • Assisted with correcting trigger controls • Helped in preparation of Power Point slides • Kharel Thompson • Helped to implement the triggers and spanning • Helped in preparation of Power Point slides

22. Questions? • Does anyone have any questions regarding our project?