Timeline for Removing unwanted square-wave noise from a signal
Current License: CC BY-SA 3.0
17 events
| when toggle format | what | by | license | comment | |
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| Mar 9, 2015 at 18:13 | history | tweeted | twitter.com/#!/StackSignals/status/574996427606196225 | ||
| Mar 6, 2015 at 4:46 | answer | added | SergV | timeline score: 1 | |
| Mar 5, 2015 at 22:55 | answer | added | andrew | timeline score: 0 | |
| Mar 5, 2015 at 20:55 | answer | added | Otto Hunt | timeline score: 0 | |
| Mar 4, 2015 at 15:09 | history | edited | Alberto Castillo Graza | CC BY-SA 3.0 |
added 77 characters in body
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| Mar 4, 2015 at 15:03 | history | edited | Alberto Castillo Graza | CC BY-SA 3.0 |
added 77 characters in body
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| Mar 4, 2015 at 13:50 | comment | added | Alberto Castillo Graza | @SergV: The desired signal shape and amplitude is known in a range but obviously there is no very exact shape. The location of the desired signal can be anywhere in a given signal. I can post other signals in which the signal is noise free, but it can just provide an idea and does not resemble that of exact desired signal. Desired signal is not periodic (I already mentioned that it is just a short damping pulse). What kind of extra information about the noise you are looking for. As I said, it is a harsh factory atmosphere among robots and we can hardly record these signals. | |
| Mar 4, 2015 at 13:43 | comment | added | Alberto Castillo Graza | @SergV: This is an ultrasonic scanner in a factory line. When we scan an area of size mxn, there are m signals of length n. This is one of those signals only. From m signals, almost 15% are affected by a very strong square-like noise which might have been caused because of the huge amount of power used by the robots moving around the objects to perform some tests including this ultrasonic test. We cannot intimidate movement of robots and therefore, we cannot avoid that strong noise. Location of the noise is random and as I said depends on robots. Now, let's answer your questions (next). | |
| Mar 4, 2015 at 4:15 | comment | added | SergV | @AlbertoCastilloGraza Can you mark the desired signal on plot of your data? Do you have any additional information about your signal? Shape? amplitude? Is signal periodic? etc. Do you have information about square-shape noise without desired signal? If your answers are NO for those questions you need to change your measurements scheme and eliminate noise. There is not silver bullet for such signals. | |
| Mar 3, 2015 at 16:42 | comment | added | Alberto Castillo Graza | Update: I received a comment from a colleague stating that ICA (independent component analysis) might help for separation. Any detailed suggestion in that regard? | |
| S Mar 3, 2015 at 12:44 | history | suggested | SergV | CC BY-SA 3.0 |
Add plot of signal
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| Mar 3, 2015 at 9:00 | review | Suggested edits | |||
| S Mar 3, 2015 at 12:44 | |||||
| Mar 3, 2015 at 3:48 | comment | added | ChocoBilly | There were no obvious peaks in your samples that I could distinguish from line noise. The period of your square wave is $25$ samples, giving it $12$ to $13$ samples between each peak. You could try a noise filter and create a square wave at your sample rate $/25$. You could programmatically, manually identify the square wave and subtract it off. That could leave your original signal. I would normalize the wave first. This would be a comment but I'm a newb here. | |
| Mar 2, 2015 at 21:38 | comment | added | Alberto Castillo Graza | Hi Emanuel, I have applied couple of filtering approaches, however, the problem is that the desired signal is just like a very short damping pulse. It also has a very small amplitude compared to the square wave. Therefore, traditional filtering approaches usually destroy the desired signal. It could help if one could first extract the square wave correctly and then try to subtract it from the original to reach the desired signal. | |
| Mar 2, 2015 at 20:53 | comment | added | Emanuel Landeholm | If the square noise is LF, what about a simple high pass filter? Otherwise I would consider rectifying and band pass filtering. How important is waveform shape vs. magnitude response? | |
| Mar 2, 2015 at 16:19 | history | edited | jojeck♦ | CC BY-SA 3.0 |
Added formatting to samples.
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| Mar 2, 2015 at 16:08 | history | asked | Alberto Castillo Graza | CC BY-SA 3.0 |