Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race...

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Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming towards you? How would

Transcript of Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race...

Page 1: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Intro to Spectral Analysis and Matlab

Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming towards you? How would you set the experiment up?

Page 2: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Running the Experiment .

Data is often recorded in the time domain. The stored dataset is called a timeseries. It is a set of time and amplitude pairs.

Page 3: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.
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Frequency Domain (Do a Fourier Transform on Timeseries)

We have converted to the Frequency Domain. This dataset is called a Spectra. It is a set of frequency and Amplitude pairs.

Page 5: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Time Domain

What’s the Frequency?What’s the Period?What will this look like in the Frequency Domain?

Page 6: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.
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What’s the new (red) period?How Does its amplitude Compare to the 1 s signal?

Page 8: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Power Spectral Densities

Secondary Microseism (~8 s)

Primary Microseism (~ 16 s)

Page 9: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

QSPA PSD PDF

Page 10: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

The Mysterious Case of HOWD

Page 11: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Sampling Frequency

• Digital signals aren’t continuous– Sampled at discrete times

• How often to sample?– Big effect on data volume

Page 12: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

How many samples/second are needed?

Page 13: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Are red points enough?

Page 14: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

AliasingFFT will give wrong frequency

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Nyquist frequency1/2 sampling frequency

Page 16: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Nyquist frequency

• Can only accurately measure frequencies <1/2 of the sampling frequency– For example, if sampling frequency is 200

Hz, the highest theoretically measurable frequency is 100 Hz

• How to deal with higher frequencies?– Filter before taking spectra

Page 17: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Summary• Infinite sine wave is spike in frequency

domain• Can create arbitrary seismogram by adding

up enough sine waves of differing amplitude, frequency and phase

• Both time and frequency domains are complete representations– Can transform back and forth – FFT and iFFT

• Must be careful about aliasing– Always sample at least 2X highest frequency

of interest

Page 18: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

To create arbitrary seismogram

• Becomes integral in the limit

• Fourier Transform – Computer: Fast Fourier Transform - FFT

Page 19: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Exercise plots

Page 20: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Sine_wave column 2

Page 21: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Sine_wave column 2

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Sine_wave column 2 and 3

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Sine_wave column 2 and 3 sum

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Spectra, column 2

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Spectra, columns 2, 3

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Spectra, column 2, 3, 2 and 3 sum

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Multi_sine, individual columns

Page 28: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Multi_sine, individual columns

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Multi_sine spectra

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Spike in time

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Spike in time, frequency

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Rock, sed, bog time series

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Rock spectra

Page 34: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Rock (black), Sed (red), bog (blue)

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Spectral ratio sed/rock

Page 36: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Basin Thickness

• Sediment site

• 110 m/s /2.5 Hz = 44 m wavelength

• Basin thickness = 11 m

• Peat Bog

• 80 m/s /1 Hz = 80 m

• Basin thickness = 20 m

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Station LKWY, Utah

raw

Filtered2-19 Hz

Filtered twice

Page 38: Intro to Spectral Analysis and Matlab Q: How Could you quantify how much lower the tone of a race car is after it passes you compared to as it is coming.

Station LKWY, Utah

raw

Filtered2-19 Hz

Filtered twice

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Triggered earthquakes