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Intro to Spectral Analysis and Matlab

Intro to Spectral Analysis and Matlab

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Intro to Spectral Analysis and Matlab. Time domain. Seismogram - particle position over time. Amplitude. Time. Frequency domain. Why might frequency be as or more important than amplitude? Filtering signal from noise Understanding earthquake source, propagation effects Ground shaking. - PowerPoint PPT Presentation

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Page 1: Intro to Spectral Analysis and Matlab

Intro to Spectral Analysis and Matlab

Page 2: Intro to Spectral Analysis and Matlab

Time domain

• Seismogram - particle position over time

Time

Amplitude

Page 3: Intro to Spectral Analysis and Matlab

Frequency domain

• Why might frequency be as or more important than amplitude?– Filtering signal from noise– Understanding earthquake source, propagation effects– Ground shaking

Page 4: Intro to Spectral Analysis and Matlab

Time domain <-> Frequency domain

• Possible to mathematically transform from time to frequency domain

• Relative importance of the frequencies contained in the time series

• Can completely describe the system either way.

• Goal of today’s lab– Begin to become familiar with describing seismograms in either

time or frequency domains– Will leave out most of the mathematics

Page 5: Intro to Spectral Analysis and Matlab

Sine wave in time

Page 6: Intro to Spectral Analysis and Matlab

Spectra of infinite sine wave

Page 7: Intro to Spectral Analysis and Matlab

Spectra of infinite sine wave

Page 8: Intro to Spectral Analysis and Matlab

Two sine waves in time

Page 9: Intro to Spectral Analysis and Matlab

Spectra of 2 infinite sine waves

Page 10: Intro to Spectral Analysis and Matlab

Spectra of discrete, finite sine waves

Page 11: Intro to Spectral Analysis and Matlab

To create arbitrary seismogram

• Becomes integral in the limit • Fourier Transform

– Computer: Fast Fourier Transform - FFT

Page 12: Intro to Spectral Analysis and Matlab

Time domain, single spike in time

Page 13: Intro to Spectral Analysis and Matlab

Spectra of a single spike in time

Page 14: Intro to Spectral Analysis and Matlab

Sampling Frequency

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

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

Page 15: Intro to Spectral Analysis and Matlab

How many samples/second are needed?

Page 16: Intro to Spectral Analysis and Matlab

Are red points enough?

Page 17: Intro to Spectral Analysis and Matlab

AliasingFFT will give wrong frequency

Page 18: Intro to Spectral Analysis and Matlab

Nyquist frequency1/2 sampling frequency

Page 19: Intro to Spectral Analysis and Matlab

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 20: Intro to Spectral Analysis and Matlab

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

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

of interest

Page 21: Intro to Spectral Analysis and Matlab

Exercise plots

Page 22: Intro to Spectral Analysis and Matlab

Sine_wave column 2

Page 23: Intro to Spectral Analysis and Matlab

Sine_wave column 2

Page 24: Intro to Spectral Analysis and Matlab

Sine_wave column 2 and 3

Page 25: Intro to Spectral Analysis and Matlab

Sine_wave column 2 and 3 sum

Page 26: Intro to Spectral Analysis and Matlab

Spectra, column 2

Page 27: Intro to Spectral Analysis and Matlab

Spectra, columns 2, 3

Page 28: Intro to Spectral Analysis and Matlab

Spectra, column 2, 3, 2 and 3 sum

Page 29: Intro to Spectral Analysis and Matlab

Multi_sine, individual columns

Page 30: Intro to Spectral Analysis and Matlab

Multi_sine, individual columns

Page 31: Intro to Spectral Analysis and Matlab

Multi_sine spectra

Page 32: Intro to Spectral Analysis and Matlab

Spike in time

Page 33: Intro to Spectral Analysis and Matlab

Spike in time, frequency

Page 34: Intro to Spectral Analysis and Matlab

Rock, sed, bog time series

Page 35: Intro to Spectral Analysis and Matlab

Rock spectra

Page 36: Intro to Spectral Analysis and Matlab

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

Page 37: Intro to Spectral Analysis and Matlab

Spectral ratio sed/rock

Page 38: Intro to Spectral Analysis and Matlab

Basin Thickness

• 110 m/s /2.5 Hz = 44 m wavelength• Basin thickness = 11 m

• 80 m/s /1 Hz = 80 m• Basin thickness = 20 m

Page 39: Intro to Spectral Analysis and Matlab

Station LKWY, Utah

raw

Filtered2-19 Hz

Filtered twice

Page 40: Intro to Spectral Analysis and Matlab

Station LKWY, Utah

raw

Filtered2-19 Hz

Filtered twice

Page 41: Intro to Spectral Analysis and Matlab

Zoomed in once

Page 42: Intro to Spectral Analysis and Matlab

Zoomed in once

Page 43: Intro to Spectral Analysis and Matlab

Zoomed in again

Page 44: Intro to Spectral Analysis and Matlab

Triggered earthquakes