1. Data Acquisition

2. Data Acquisition System Analog Signal Signal Conditioner ADC Digital Processing Communication

3. Analog vs. Digital Signal Analog signals: –Continuous, expressed in decimal system –No limitation on the maximum/minimum value –Can not be processed by computer Digital signals: binary number system –All numbers are expressed by a combination of 1 & 0 –The maximum value is limited by # of bits available

4. Signal Conditioning Functions: modify the analog signal to match the performance of the ADC –Pre-filtering: remove undesirable high frequency components –Amplification: amplify the signal to match the dynamic range of the ADC

5. Analog-to-Digital Conversion (ADC) Function: convert analog signals into digital signals –Sample & hold –Quantization –Coding y(t)=f(t)  y k =f(t k )

6. Quantization Definition: transformation of a continuous analog input into a set of discrete output state –Coding: the assignment of a digital code word or number to each output states –# of possible state: N=2 n, n is # of bits –Quantization resolution: Q=(Vmax-Vmin)/N –Quantization Error:

7. Select a Data Acquisition Card Functions: A/D, D/A, Digital I/O, signal conditioning (amplification, prefiltering), timer, trigger, buffer Features: –A/D resolution (# of bits used) –Maximum sampling rate –# of channels –Total throughput –Aperture time

8. Example of Data Acquisition Card

9. Timing Aperture time: the duration of the time window that the analog is sampled Jitter:

10. Sampling Sampling: Numerical evaluate the signal at discrete distance in time, y k =y(k  t) Digitized Signal: a sequence of numbers that is an approximation to an analog signal Sampling time/Period: time duration between two consecutive samples,  t Sampling rate (Hz): 1/  t Nyquist Frequency: 2f max Sampling theory: fs > Nyquist Frequency

11. Sampling Theory Shannon-Nyquist sampling theorem –The maximum frequency component a sampled data system can accurately handle is its Nyquist limit (i.e., Nyquist frequency).

12. Aliasing Matlab example of aliasing

13. Anti-aliasing Filter One way of avoiding the problem of aliasing is to apply an anti-aliasing filter to the signal, prior to the sampling stage, to remove any frequency components above the "folding" or Nyquist frequency (half the sampling frequency). An anti-aliasing filter is a low-pass filter.