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Unread 01-12-2005, 22:26
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DonRotolo DonRotolo is offline
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Team Role: Mentor
 
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Teaching DAQ to FIRST teams

Team 1676 is planning on introducing the concept of design verification and validation, using the principles of data acquisition (DAQ). We have formed a testing & integration team for this purpose, and in the weeks leading up to kickoff we are covering the basics of DAQ, using classroom instruction and the 2005 robot to provide some hands-on experience. (The Robot Controller has limited A/D capabilities, and the Operator Interface "Dashboard" would be a good display for simple virtual instruments)

One of the mentors has developed a lesson plan, shown below. There is a lot of material behind this simple outline, probably about 8 hours at least. As the build season starts, and the students are sensoring and measuring the subsystems and, eventually, the whole robot, we'll be there to finish the rest of the teaching on a more practical level.

What I am interested in is, in the outline below what topics are missing, or could be covered more thoroughly or differently, or particular issues within a topic that are important? Also, any ideas for some of the topics, such as particularly effective demonstrations or useful 'labs' to use, would be greatly appreciated. While many of the mentors and coaches have some experience with DAQ, surely there are people who live in this world who can share some of their expertise.

Any and all advice would be most welcome.

Don

======================
DAQ course outline

What good is DAQ?
Systems and interrelationships
Natural DAQ systems (seat of the pants)
Feedback systems, open & closed
Problem solving
Design processes
Gathering & interpreting real-time data

Sensors
Analog
Digital
Signal conditioning & buffering
Sensor calibration & scaling

DAQ hardware
Sampling rate, resolution, scaling, aliasing, dynamic range
Data accuracy & precision
Differential & single-ended inputs, input impedance
Grounding & ground reference, isolation

DAQ software
Simple data collection, file management
Data interpretation
Real-time data streams
Virtual instruments
Counters
Programming

Outputs
Digital
Analog
Triggers & events
=====================
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