1. Real world measurements

2. Measuring things Making measurements is an essential part of all branches science and engineering. Much (all?)of our understanding of the world was born from experimental measurements (often ones that disagreed with the current theory). Models of systems are useless without validation. Performance of engineered systems must always be measured and tested. “Experiment is the sole judge of scientific truth” Feynman

6. Healthcare

7. Modern engineering systems

8. Physics – classical and today Michelson-Morley Large hadron collider

9. And corporations want to instrument your life (this is a conspiracy)

10. What you will learn (hopefully) Make a set of physical measurements. Analyze and present experiment data. Conduct basic error analysis of data. Design a basic computer based experimental system. Use measurements test physical models.

11. Leverage Sensors and electronics keep getting cheaper. Wireless keeps getting cheaper and better. Sensors getting smaller. GPS is getting easy and cheap. IPhone and Wii are driving down complex sensor costs. Ability to interface to computers keeps getting easier.

12. Course structure (some details TBD) Week 1Individual Lab: Intro to data acquisition - acceleration Week 2Individual Lab: Op-amps - lie detector Week 3Individual Lab: Instrumentation amp. – EKG Week 4Individual Lab: Mechanical – Stress/strain Week 5Individual Lab: Mechanical – Strain project (?) Week 6Individual Lab: Signal processing – EEG (brain waves) Week 7Individual Lab: Remote data collection (weather station) Week 8 Team Project Week 9Team Project Week 10Team Project Week 11Team Project Week 12Team Project Week 13Team Project

13. Project theme – The natural world Environment Weather balloons Lakes, rivers. Weather, wind, rain. Bio-instrumentation EKG EEG Pulse oximeter Biomechanics (accelerometers in your shoes) Possible examples: Projects can focus on building a reasonably challenging sensor/circuit or using commercial sensors and focus on the experiment and the data.

14. A few things…. This is not an EE course. Ninjas. Lab reports – focus mainly on results. Weekly labs will be individual, we will try to minimize the sharing of equipment. Team project will be in groups of about 4. Significant changes in labs from last years class.

15. Grades – yes we have to give them Storey conjecture: If you turn everything in on time, come to class, spend a reasonable amount of time on homework, and put forth a reasonable effort, the lowest grade you will receive is a B. Corollary: You can easily get a C, D, or F by not doing the above mentioned tasks.

16. So… let’s get down to business

17. Hardware – USB data acquisition

18. Analog to digital conversion What is the sample rate? Our system has a 14 bit ADC, if we set the range to ±10 V, what is resolution?

19. Resolution 14 bit ADC: 00101011101101 2 14 =16384 numbers Resolution = range/16384 Eg: range is +10 to -10 V; 20/16384=1.2 mV range is +1 to -1 V; 2/16382 = 0.12 mV

20. Aliasing error

21. Noise What are sources of noise?

22. Types of noise Thermal (Johnson) noise – due to thermal motion of charge carriers. Shot noise – discrete nature of electrons 1/f noise or flicker noise Interference Electromagnetic interference – (man-made or natural) Cross-talk – coupling between different signal lines

23. How accurate is the DAQ? If we measure 1 V, should we believe it? Test with Keithley

24. How close is the measured value to the actual one? Pressure sensor example:

25. Simple voltage divider demo What’s this voltage? = =2.5V R R

26. USB 6009 – input impedance = =2.5V R R i i is not 0!

27. Analog output demo = =1V R=20K and 200 Ω

28. Source impedance DAQ Analog Output =1V =200 Ω What is R source for our DAQ?

29. Generic sensor measurement Sensor Measurement- DAQ If R source is small, and Rmeas is big, then you measure Vsensor Otherwise, you might be measuring something else!

30. This week: Accelerometers

31. Matlab data acquisition toolbox

32. In class exercises See Data Acq. Toolbox tutorial, try exercises 1, 2, and 3. Work with the person next to you. Try to create a virtual scope, where data is collected and plotted continuously. Hint: collect an infinite number of samples.