Finding Spectral Slope in dB/Octave for Hydrophone Data

In summary, the student is trying to find the spectral slope in dB/octave. They are trying to find the difference between two PSD points and then divide this value by amount of octaves estimated based on the mentioned formula. They need to count the difference between 1 Hz - 1.5 Hz and then calculate the amount of decades from taken frequencies. Finally, they mention "decade" when they are interested in per "octave."
  • #1
Clmz
3
0

Homework Statement


I have some registration of sound gathered by hydrophone. Next I have created a power spectral density (dB re 1 Pa^2/Hz) vs frequency plot (semilog in matlab). And now I want to find spectral slope in dB/octave (one octave is log2(f2/f1).
I suppose that I should calculate the difference between two PSD points (max and min) and then divide this value by amount of octaves estimated based on the mentioned formula?
Could you if I'm right? Or mby there should use some different formula?

Homework Equations

The Attempt at a Solution

 
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  • #2
Semilog...and your horizontal axis is f or log(f/fo)?

One actave is a doubling in frequency. So if linear f can you draw a straight line approximation to any region of interest, then extend that line over an exact octave and read the change in dB.

Drawing by hand has inherent noise-averaging, in comparison with a two points reliance which does not.
 
  • #3
Here is an example
https://i.imgsafe.org/b3c770eb73.png
 
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  • #4
Are you looking for a fixed dB/oct figure? If so, you will be looking for a straight line best fit to this.
 
  • #5
Ok, so for that I must count the difference value of dB i.e. from 1 Hz - 1.5 Hz and then calculate the amount of decades from taken frequencies?
 
  • #6
Clmz said:
Ok, so for that I must count the difference value of dB i.e. from 1 Hz - 1.5 Hz and then calculate the amount of decades from taken frequencies?
Why do you mention "decade" when you are interested in per "octave"? Note that 1.5 Hz is difficult to read, it's definitely not midway between grid lines on a log plot.

There is a grid line at 1 Hz, the next grid line adjacent to that is 2 Hz, so why not use that for your double frequency? If you take a plastic ruler and measure this horizontal distance between these 2 grid lines, then everywhere and anywhere along the horizontal axis this same distance (in mm) represents a doubling in frequency. (Try it on the 2 Hz, 3 Hz, 4 Hz, and 5 Hz grid lines to demonstrate this is true.)

Is this noise on the recording, and you want to smooth it before doing calculations? If there are spectral peaks that you want to preserve, then I guess you'll want to exclude them from your smoothing.
 

Related to Finding Spectral Slope in dB/Octave for Hydrophone Data

What is spectral slope in dB/octave?

Spectral slope in dB/octave is a measurement of how quickly the amplitude of a sound changes with frequency. It is often used to characterize the frequency content of hydrophone data, which is data collected from underwater sound recordings.

Why is finding spectral slope important in hydrophone data analysis?

Finding spectral slope is important because it provides valuable information about the characteristics of the sound source being recorded. It can help identify different types of marine life or man-made noise sources, and can also be used to monitor changes in the underwater environment.

How is spectral slope calculated for hydrophone data?

Spectral slope is typically calculated by performing a spectral analysis on the hydrophone data, which involves breaking down the sound signal into its component frequencies. The slope is then determined by fitting a straight line to the logarithmic amplitude spectrum and calculating the slope of that line.

What factors can affect the spectral slope of hydrophone data?

The spectral slope of hydrophone data can be influenced by a variety of factors, including the type of sound source, the distance between the hydrophone and the sound source, and the properties of the underwater environment such as water depth and composition.

How can spectral slope analysis be used in real-world applications?

Spectral slope analysis of hydrophone data has a wide range of applications, including marine mammal monitoring and conservation, underwater noise pollution studies, and acoustic communication research. It can also provide valuable information for industries such as oil and gas, fisheries, and shipping.

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