The purpose of this experimentation was was to view how sound waves travel through air in order to gain a more physical understanding of the nature of sound waves. This experiment will be comparing the wave characteristics of a human voice saying "Ahhh" into a microphone as well as the characteristics of a more precise wave, in this case a tuning fork.
Procedure:
1. the necessary equipment below was gathered:
a. tuning fork
b. microphone
c. logger pro hardware
d. laptop
2. logger pro was then started and the mic connected to the laptop.
3. the microphone was then held close to my mouth as I spoke into in and the data was collected and displayed into the graph show below.
fig. 1
4. my lab partner, Cesar, then repeated this process. this data collected is shown in blue with my original data collected of my voice in red in the background in order to compare results.
fig. 2
5. next, the same procedure was repeated although this time the process was done with a tuning for substituting in place for our voice.
fig. 3
6. the tuning fork was truck against my thigh softly to allow it to vibrate and transmit its sound. the data was collected and graphed. the blue line signifies the tuning fork while the red again represent my original voice.
fig. 4
7. finally, the tuning fork was then once again struck but this time with a much harder force so as to produce a more intenese sound then previously. this was done to compare how the sound wave differed from the original tuning fork measurment (i.e. frequency, wavelenght, amplitude, etc.). the resulting wave is depicted below in blue with my original voice trail in red in the background.
fig. 5
Analysis:
From the initial graph of my voice, fig 1, you can conclude that although it is not necessarily sinusoidal, it is in fact still a period wave since the amplitudes of the wave repeat over time. The data that was collected includes a total of about 5 and a half waves. The waves can be counted by taking the highest amplitude of the waves and counting from peak to peak. The time that this data was collected was within a .03 second window. This can be compared to the blink of an eye (0.3-0.4 seconds) which is actually ten times longer than the time of data that was taken here.
since the period is the amount of time it takes for one wave length to cycle by, the period( T ) can be determined by taking the time at one peak and subtracting it from the time at another other given peak. the calculation for determining my voice's period is as followed:
T = t2-t1
T = 0.0106s - 0.0043s = 0.0063s
with the period being found, the frequency of the wave ( f ), can be determined by taking the reciprocal of the period:
f = 1/T = 1/.0063s = 158.7 Hz
now that the frequency is found, determining the wave length ( λ ) of the wave is simple assuming that the speed of sound to be 340m/s. the calculation follows:
λ = v/f = (340m/s)/(158.7Hz) = 2.14 m
two meters can be compared to a little above average person.
If the collection time taken was longer, say about ten times longer, this would not change any of the previous results calculated above ( with of course the exception in variations from not being able to completely duplicate the exact same sound as before ). If the same sound were to be recorded in the exact same manner as before but for a longer period of time, the period, frequency, and wave length would all still be the same. this is because the sample size is the only thing that is changing, not the actual frequency itself of the sound. the only difference would be that the number of wave lengths in the sample set would be larger.
as pictured in fig 2, this same recording process was repeated for Cesar's voice (in blue). Upon initial observation, it is obvious that the wave are not the same. The differences that stand out initially are the amplitude, which is smaller than my initial. This decrease in amplitude is due to Cesar's voice not being as loud as mine in the recording process. All he need to do is project louder into the mike and his amplitude would surpass my on.
another difference that can be spotted is the number of wave lengths. the number of waves recorded in this sample are close to five(5), where as my collection had five and a half(5.5). from this initial observation, it can be assumed that Cesar's frequency should be less than mine. from this assumption, since period is the reciprocal of frequency, it can also be concluded that his period will be larger than mine. again, before making any calculations, the wave length of Cesar's voice should be larger for two reasons: (1) the number of waves collected within the same time frame are less (2) the frequency is assumed to be less and the wave length is inversely proportional to the frequency ( λ = v/f ) therefore the wave length must be larger. using the same calculations above for my voice, the information for Cesar's voice was measured:
f = 120.5 Hz
T = .0083 s
λ = 2.82 m
as shown above, the calculations agree with the initial assumptions.
next, the sound that was recorded was emitted by a tuning fork, fig 3. the data for the tuning fork is displayed in fig 4. as you can see, the graph of the tuning fork is much cleaner then the sound that was emitted by my voice. this sound is a nearly ideal sinusoidal periodic wave. unlike my voice, the tuning fork did not have multiple amplitudes per wave length, just one is viewable. using the same techniques as before, the same properties can be found for this wave:
# of waves = ~7
T = Δt = 0.0063s - 0.0024s = 0.0039 s
f = 256.41 Hz
λ = 1.33 m
the same tuning fork was then struck again but this time it was hit harder so as to emit a louder sound. this data that was collected is shown in fig 5. since the tuning fork is used to tune instruments, it is safe to assume that it always vibrates at a relatively constant frequency each time it is struck. if this is true, then the assumption can be made that every characteristic of the wave that depends on the frequency will remain unchanged from the first recording. these characteristics are period and wave length. the below calculated data shows this to be true.
# of waves = ~7
T = Δt = 0.0157s - 0.0118s = .0039s
f = 256.41 Hz
λ = 1.33 m
as you can see from the data, both match exactly in every characteristic. the only difference that the waves have is their amplitude. the larger amplitude corresponding to the louder struck fork. although not entirely clear in the picture above of the tuning fork, on the fork itself under the note that it is intended for, in this case "C", is the frequency at which this fork should vibrate. this fork read a frequency of 256 Hz which makes our reading extremely accurate.
Summary:
from this lab experiment, it can be seen exactly what effects on a sound wave change its characteristics and which ones do not. this experiment displayed that the human voice is not a simple wave. rather, it is a complex wave composed of multiple simple waves that can still be classified as a periodic wave. from this data, it is also worth noting that the volume or intensity of the wave only changes the amplitude of the wave; increasing the volume does not increase or decrease the period, frequency, or wave length.
No comments:
Post a Comment