Lower cutoff frequency for signal processing (filtering ) of LVDT and strain gauge data?
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Hi,
I have carried out some shake table tests on piles inside the soil. I have applied white noise motion as input for the shake table. While estimating the bending moment and displacement, what should be the lower cutoff frequency while applying filter?
I usually do a low pass filter for LVDT data and strain gauge data, where i define the upper cutoff frequency. I do not put a lower cutoff frequency as putting a lower cutoff frequency will take out the bending moment or displacement of a pile, which may be of residual value or basically static in nature.
Hope you understand this point. Is my approach correct?
2 件のコメント
thoughtGarden
2019 年 9 月 19 日
Can you confirm I understand your problem:
You have excited an instrumented structure with vibration and measured the deflection in the structure. You now are going to use that measured deflection data to estimate bending moment. You need to ensure that the measurement data is clean, and represents true deflection instead of high frequency noise from the shaker.
can you elaborate on why a simple low pass filter will not work?
回答 (1 件)
thoughtGarden
2019 年 9 月 19 日
It sounds like a low pass filter is all that is needed. There are several considerations in selecting low-pass cutoff frequencies. Given that you know something about the input (shaker table motion) and the structure, you can select the filter type and bandwidth.
Considering that I don't know anything about your setup, I will quote from Mechanical Vibrations and Shock Measurments, "It is not possible to give generally valid rules for selection of bandwidth".
That being said, here are two potentially invalid rules to consider
- Don't let your filter remove the real thing...the mechanical reasonance of the instrumented structure. You want to capture the strain/deflection of the structure, so the bandwidth must be greater than the -3dB frequency of the structure. If possible, you want seperate the filter and natural frequncy by as much as possible while still achieving the goal of removing noise. This is a balancing act which is custom to each application.
- If digitally filtering, always be mindful of aliasing. Aliasing is when high frequncy content appears as low frequency folded/ghost content due to sampling frequency being below 2*signalFrequency.
There are other guidlines, but start here and return with more questions.
2 件のコメント
thoughtGarden
2019 年 9 月 20 日
If you found this answer to be correct, please accept it. Otherwise, please add aditional comments so that it may be improved.
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