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Microphone FFT Lab

Module by: Casey Weltzin. E-mail the author

Summary: The Fast Fourier Transform (FFT) is a tool that can be used to convert time domain information into a frequency domain representation. In the Microphone FFT Lab, experimenters use a Low Cost National Instruments Data Acquisition device to acquire data from a microphone element. Signal Express software is then used to visualize measured sound data and convert it to the frequency domain. The Microphone FFT lab is designed as a laboratory or at-home experiment.

Microphone FFT Using National Instruments Low Cost Data Acquisition

Introduction

Whenever a sound is made, a pressure wave travels through a medium (such as air) and vibrates our eardrums. This same principle can be used to convert sound information into an electrical form so that the experimenters can visualize, interpret, and analyze the sound information.

In addition to visualizing the amplitude of a sound wave (electrically) over time, we can also look at the frequency content of the sound signal. Simply put, we can use the Fast Fourier Transform (FFT) algorithm to look at how much of each frequency the sound signal contains. More information on the FFT will be provided in the theory section.

During this exercise, the experimenters will use a microphone element to convert a sound wave into an electrical signal. This signal will be then digitized using a Low Cost USB DAQ device. Finally, the Signal Express application will be used to quickly visualize the time domain sound signal as well as compute its Fast Fourier Transform for viewing in the frequency domain.

Pre-Lab Assignment

1) Find a microphone element datasheet by searching the internet for “electret condenser microphone element.” Most detailed datasheets should show the frequency response curve of the element. This curve shows how much of each sound frequency makes it through to the electrical signal produced. What does this curve look like for the element you found?

2) What frequency response would be ideal for a microphone element to have? Would a flat curve be advantageous? What about a curve that rolls off at 5 Hz? Hint: first determine which frequencies are audible to the human ear.

3) Write a short summary about how the electret microphone works. You should be able to find a variety of sources online; Wikipedia is a good starting point.

4) Become familiar with the National Instruments USB 6008 and 6009 data acquisition devices. These datasheets are available at www.ni.com.

Theory

Electret Microphone Elements

One way to convert sound pressure waves into an electrical signal is using an electret microphone element. A picture of such an element is shown below:

Figure 1: Electret Microphone Element
Figure 1 (Graphic1.png)

Inside the electret microphone element, a dielectric material is made to hold a permanent charge. When the element vibrates, the internal capacitance changes and an electrical signal is produced. A variety of additional components inside the microphone element act as a small output amplifier.

The Fast Fourier Transform (FFT)

It is very common in science and engineering to view a signal’s amplitude vs. time. For example, imagine that a doctor is watching a patient’s heartbeat on an electrical device. He might see peaks in the heartbeat signal every 1 second if the patient’s heart beats 60 times a minute.

If the doctor wishes to calculate the patient’s heart rate (assuming it is perfectly steady), he can try to measure the time between successive peaks on the screen (1 second in this case) and calculate the heart rate from that information. However, there is an easier way!

Any signal (electrical or otherwise) can be viewed as a number of sine waves at different frequencies with various amplitudes and phase shifts. Simply put, a graph can be made that shows amplitude vs frequency instead of amplitude vs time. In the doctor’s case above, it would be very convenient for him to have a graph of amplitude vs heart rate frequency. If the patient’s heart rate is approximately 1 Hz as noted above, then the amplitude vs frequency plot should show a peak somewhere near 1 Hz as well. Now, the doctor can simply glance at the graph to see the heart beat frequency.

In order to convert a time domain signal such as heart rate amplitude vs time into the frequency domain to produce a plot such as amplitude vs frequency, the Fourier Transform can be used. Several variations of this transform exist, including the Fast Fourier Transform (FFT) algorithm that is typically used by computers. For the purposes of this exercise, the low level mathematical details of the transform will not be needed. The experimenter does, however, need to remember the basic concept:

Remember, any signal can be thought of as being composed of sine waves, where each frequency of sine wave will have a given amplitude and phase shift.

Hardware and Software Required

  1. 10 Ohm resistor
  2. 4.7 uF capacitor
  3. Electret microphone element
  4. National Instruments Low Cost USB DAQ
  5. Signal Express software

Laboratory Exercise

During this exercise, the experimenter will acquire a sound signal from an electret microphone element. This sound signal will then be converted into the frequency domain using the Fast Fourier Transform to produce a chart similar to the following:

Figure 2: Frequency Domain Representation of Microphone Signal
Figure 2 (Graphic2.png)

1) Connect the following circuit to the Low Cost USB DAQ as shown. The microphone element can be purchased cheaply at Radio Shack, etc. Note that the +5V power supply can be obtained directly from the National Instruments USB 6008 or 6009 devices.

Figure 3: Electret Microphone Circuit
Figure 3 (Graphic3.png)

2) Program steps in National Instruments Signal Express software to match the sequence below. These steps will acquire a sound signal from the circuit constructed above and compute the frequency domain representation using the FFT.

Figure 4: Completed Signal Express Steps
Figure 4 (Graphic4.png)

3) Drag the acquired time domain sound signal as well as the frequency domain (FFT) signal into the data view window. Choose “run continuously” within Signal Express to loop the sequence.

4) Try generating various sounds by talking, whistling, etc. Make sure that you are close to the microphone element. Observe the FFT signal when you whistle different notes.

Post-Lab Questions

1) Do research in a textbook or online to determine the frequency range that the human voice can produce. Did the FFT of your voice / whistling fall within that range?

2) Imagine you tried to use the electret microphone element outside on a windy day. What might happen if your tried to record your voice? How does the frequency response of the microphone play a factor here?

3) How can you tell if high frequency noise is present in your sound signal without playing it back? Hint: think about the concepts discussed in the theory section above.

4) What could be added to the Signal Express sequence above in order to attenuate any noise in your sound signal? What frequency ranges must remain intact (assuming you are attempting to record a human voice)? What frequency ranges do you not have to be concerned about at all?

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