FAST Fourier Transform (FFT) and Digital
Filtering Using LabVIEW
Wei Lin
Department of Biomedical Engineering
Stony Brook University
Instructor’s Portion
Summary
This experiment requires the student to use LabVIEW to perform signal
analysis on the acquired analog signals. Students should be familiar with
the Fast Fourier Transform (FFT) and digital filtering using LabVIEW
Uses
This lecture applies to all courses of virtual instrumentation.
Equipment List

Computers

LabVIEW 8.6 Express

NI-ELVIS benchtop workstation

Lecture Slides of “Data Analysis Using LabVIEW”

VIs from the project “Data Acquisition Using NI-DAQmx”
References
Student’s Portion
Introduction
The students should learn the basic LabVIEW programming techniques for
the FFT and digital filtering. They will modify two VIs developed in the
project “Data Acquisition Using NI-DAQmx” and add frequency spectrum
analysis and digital filter in the two VIs.
1
Objectives


Perform FFT analysis using LabVIEW Frequency Spectrum
Express VI
Design and test digital filter using LabVIEW Filter Express VI
Theory
The Fast Fourier Transform (FFT) and the power spectrum are powerful
tools for analyzing and measuring signals from plug-in data acquisition
(DAQ) devices. It can measure the frequency components within the
signal. FFT-based measurement requires digitization of a continuous
signal. According to the Nyquist criterion, the sampling frequency, Fs,
must be at least twice the maximum frequency component in the signal. If
this criterion is violated, a phenomenon known as aliasing occurs. When
the Nyquist criterion is violated, frequency components above half the
sampling frequency appear as frequency components below half the
sampling frequency, resulting in an erroneous representation of the signal.
This is called frequency aliasing. Therefore, before a signal is digitized,
antialiasing filters are used to attenuate the frequency components at and
above half the sampling frequency to a level below the dynamic range of
the analog-to-digital converter (ADC). Spectral leakage is another issue in
FFT analysis. It is the result of an assumption in the FFT algorithm that
the time record is exactly repeated throughout all time and that signals
contained in a time record are thus periodic at intervals that correspond to
the length of the time record. If the time record has a nonintegral number
of cycles, this assumption is violated and spectral leakage occurs. To
alleviate the spectrum leakage, a predefine window function is applied to
the signals to be analyzed.
Filters alter or remove unwanted frequencies from your signal. Depending
on the frequency range that they either pass or attenuate, they can be
classified into the following types:




A lowpass filter passes low frequencies, but attenuates high
frequencies.
A highpass filter passes high frequencies, but attenuates low
frequencies.
A bandpass filter passes a certain band of frequencies.
A bandstop filter attenuates a certain band of frequencies.
Digital filters have the following advantages over their analog
counterparts:


They are programmable in terms of filter order, cutoff frequencies, and
amount of ripple.
They are stable and predictable.
2


They do not drift with temperature or humidity and do not require
precision components.
They have a superior performance-to-cost ratio.
Therefore, it is recommended to use digital filters in instrumentation
except for the antialiasing filter.
LabVIEW has two express VIs for FFT analysis and digital filtering. They
are frequency spectrum express VI and filter express VI.
Lab Procedure
Experiment 1: Create a LabVIEW application of frequency spectrum
analysis:
1. Launch LabVIEW.
2. Load finite data acquisition VI.
3. Add the frequency spectrum VI (Express->Signal Analysis>Spectral). Configure the output of the express VI as linear in
result section and set window as None.
4. Connect the waveform data from DAQmx read VI to the signal
terminal of the frequency spectrum express VI.
5. Add a graph indicator on the front panel and connect the output
(FFT-(RMS)) of the frequency spectrum VI (FFT) to the graph.
6. Keep the ELVIS unit off. Connect the output of function generator
“FUNC OUT” to ACH0 using connection wire on the prototype
board.
7. Turn ELVIS unit on including the prototype board.
8. Launch ELVIS application and choose function generator.
9. Enter the parameters for the controls of the LabVIEW.
Recommended sampling frequency is 1000 Hz and number of
samples is 1000.
10. Set the frequency, and function type of the signal generator
(recommended function: sine wave, frequency 20 Hz. and run the
VI and observe the frequency spectrum. In this case, you should
collected integer number of cycles of the signal. Therefore, no
spectrum leakage is present.
11. Change the signal frequency or the number of samples so that there
is a disconnection at the end of the signal (non integer number of
cycles collected) and observe the spectrum leakage.
12. You may need to add write Meas file VI to save the signal and the
FFT result for your lab report.
13. Save the VI
Experiment 2, Create a LabVIEW application of digital filter:
1. Use the VI from previous experiment.
3
2. Add two more graph indictors on the front panel for the filtered
signal and the spectrum of the filtered signal.
3. Add a filter express VI (Express->Signal Analysis->Filter) and
connect the output from the DAQmx VI to the signal terminal of
the filter VI
4. Connect the output of filter to the graph indicator of filtered signal.
5. Add another frequency spectrum express VI (Express->Signal
Analysis->Spectral) on the block diagram and connect the filtered
signal to its input.
6. Connect the output of the above frequency spectrum express VI to
the graph indicator of the filtered signal spectrum.
7. Combine the two dynamic data, the spectrum of the original signal
and the spectrum of the filtered signal using signal manipulation
VI (Express->Signal Manipulate->merge signals) and connect it
to the “Write LabVIEW Measurement Data” express VI (Express>Output->write meas data). In the wizard, select
a. Ask user to choose file
b. Ask each iteration
c. If a file already exists, overwrite file
d. X value columns: one column per channel
8. Run the application and record the results in files. The following
are the suggestions for the test of digital filters.
a. Use square wave at low frequency, far below the sampling
frequency. (20 Hz)
b. Change the cutoff frequency of the filter.
c. Change the type of filter, e.g. lowpass or highpass.
d. Change the order of the filter. (optional)
e. Change the topology of the filter. (optional)
Experiment 3. (Extra credits): Using FFT to measure the cutoff
frequencies of the band pass filter you made in the previous lab. The
expected solution will use one or two measurements to estimate the
cutoff frequencies instead of using multiple sinusoidal signals.
Lab Report
1. Objective.
2. Theory (What it FFT? Filter?)
3. Data: Demonstrate frequency spectrum of the tested signal and filter
effects.
4. Due on 11/20/2009
Reference VIs
4
FFT VI
Filter VI
5