Filter data that is not sampled uniformly?

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TheNovice 2015-3-1

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评论： Star Strider 2015-3-1

sample.mat

Hi, does anyone know how to filter data that's not sampled at a constant frequency? The data is based on pressure-crank angle, so I have a pressure sample at every 0.1 crank angle degree.

I'm trying to the use butter() function, but it requires a sampling frequency...

Regards, TheNovice

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dpb 2015-3-1

Is there a recorded timing interval or other way to know rpm, I presume? If so you can derive time. I'll have to cogitate on w/o a little...

TheNovice 2015-3-1

编辑：TheNovice 2015-3-1

I have an average rpm of 1000 in the attached sample. So yeah, I can reconstruct a time vector with uniform distribution from that. The problem I see though is that the RPM is not constant during a cycle, and this approach will contribute to an error. The question is how large...

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Star Strider 2015-3-1

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I have no mechanical engineering background, so I’m having a difficult time imaging what your data actually are. If it is constantly sampled, you could filter them with respect to the crank angle, or interpolate (resample) them at a constant sampling frequency in time. I have no idea how valid this may be, since I don’t have your data.

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Star Strider 2015-3-1

编辑：Star Strider 2015-3-1

My pleasure!

I don’t have a lot of experience with Savitsky-Golay filters, since in biomedical signal processing and analysis, we pretty much always have uniformly-sampled signals, hardware anti-aliasing filters ahead of the ADCs, and other conveniences. They seem to be perfect for your application, however.

There are a number of good signal processing textbooks. (A number of MATLAB based books are available here.) The one I’ve used since grad school (and updated as new editions emerged) is Proakis and Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications (Fourth Edn.), ISBN: 0-13-187374-1. Also see the MathWorks Academia section.

As for analogue signal processing, my gold-standard is Chen, Passive and Active Filters: Theory and Implementations, ISBN: 0-471-82352-X.

There may be later editions of both of these, so I would search for them, especially since the later editions would use later versions of MATLAB and toolboxes. Hardware filters are relatively easy to design and build (‘cookbook’ design sources are available for a number of active filters using op-amps), and they generally perform quite well.

I would go with a hardware low-pass filter in your application in the future, if you know that your signals are always within a specific frequency range. If you can expect significant baseline drift (that you would not want as part of your signal), consider a bandpass filter with a low-frequency cutoff to eliminate the baseline drift, as well as a high-frequency cutoff to eliminate the high-frequency noise.

TheNovice 2015-3-1

编辑：TheNovice 2015-3-1

Thank you the very informative answer. You have a lot of good points that I will consider in the future. Also a thank you for the suggested books, will definitely look into them. This is an area I need more knowledge of.

Thank you again for your help!

Regards, TheNovice

Star Strider 2015-3-1

My pleasure!

From my own experience, I would take courses on digital signal processing, experiment design, mathematical modeling and nonlinear parameter estimation, and if you are going to do a significant amount of instrumentation design, a course in hardware design and hardware signal processing. If you are doing imaging in your research, a course in digital image processing would also be necessary.

Your research seems interesting. Have fun!

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