Displacement from accelerometer data

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Derek Cooper 2021-4-22

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https://ww2.mathworks.cn/matlabcentral/answers/809765-displacement-from-accelerometer-data

评论： William Rose 2023-6-28

采纳的回答： Mathieu NOE

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Dear everyone,

I am trying to integrate data from accelerometer measurements to determine velocity and displacement of the system. The velocity looks ok, for which i consider the following approach

acceleration = [nx1];       % Data from accelerometer
dt = [1x1];                 % Length of each time-step
velocity = cumtrapz(dt,acceleration);

However, when I try to utilize the same approach once again in the aim of determining displacement of the system i get unrealistic displacements. The following code is considered

displacement = cumtrapz(dt,velocity);

I have also tried other resources and functions available on matlab community, however, no progress yet.

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采纳的回答

Mathieu NOE 2021-4-22

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hello

the drift in the displacement is due to the fact that the velocity itself is not a zero mean signal

so if you are interested in the dynamic signal only , before each integration with cumtrapz you have to detrend your input data

help detrend

detrend Remove a polynomial trend.

Y = detrend(X) removes the best straight-line fit linear trend from the data in vector X and returns the residual in vector Y. If X is a matrix, detrend removes the trend from each column of the matrix.

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Mathieu NOE 2023-6-28

it depends of your signal quality and fft spectrum

if you have a loft of drift / ofset and very low frequency noise , then you may need more filtering

with very clean data , you may have to use only detrend but every situation is a special case

William Rose 2023-6-28

@Oskar Kilgus,

Excellent advice form @Mathieu NOE, as always.

A good general principle is to avoid detrending and filtering of your raw data as much as possible, so that you preserve the information in the data. Detrend and filter only to the extent that it is required to get reasonable looking results. Even then, consider whether the required detrending and filtering indicates some probelm with the instrumentaiton which you could correct in future experiments. It is not surprising that accelerometer signals need detrending, since even small offsets will grow parabolically when integrated twice. And for this reason, fitting a quadratic to the full length acceleration signal is a reasonable next step, if linear detrending seems to be insufficient.

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