Use the sbFilter function to apply a sine-Butterworth filtering operation to a previously saved X–Y data object (a collection of ordered pairs) to produce a new X–Y data object. This filtering operation can be used, for example, to remove high frequency noise.
The Visualization module uses a sine-Butterworth filter whose transfer function 
has the following form:
The number of poles control the shape of the transfer function above the cut-off frequency. The greater the number of poles, the steeper the drop-off and the lower the “far point.” The default value is usually adequate for filtering high frequency noise from a curve. High numbers of poles increase the computational effort and eventually lead to the filter becoming unstable.
For the filter to be applied to a curve, the curve must have data points at regularly spaced intervals in time. Therefore, a curve to be filtered is resampled at a given frequency (the sampling frequency). The default sampling frequency will be inadequate for curves containing data with a frequency content that is much higher than the cut-off frequency. Using a very high sampling frequency will create a curve with a very large number of data points.
The parameters required for the sbFilter function are the data object name, the cut-off frequency, the sampling frequency, and the number of poles. The default value for the sampling frequency is five times the cut-off frequency, while the default value for the number of poles is six.
Your X–Y data object must have a constant time step for it to be filtered. If the time step is not constant, ABAQUS/CAE computes additional points at constant intervals by interpolation. The constant time step is computed from the sampling frequency according to the following relationship:
Figure 30–21 illustrates the type of X–Y plot that can be produced using the sbFilter operation.
To apply sine-Butterworth filtering to an X–Y data object:
Locate the Operate on XY Data dialog box.
From the main menu bar, select Tools
XY DataCreate. Click Operate on XY data in the dialog box that appears; then click Continue. The Operate on XY Data dialog box appears.
From the Operators listed, click sbFilter(X,F,F,I).
The sbFilter function appears in the expression window.
From the XY Data choices, click the name of the X–Y data object on which to operate and click Add to Expression. You can choose from all X–Y data objects previously saved within this session (listed alphabetically in the XY Data field).
The X–Y data object name appears within the sbFilter function parentheses in the expression window.
Position your cursor after the data object name in the expression window and enter, in order, the following three parameters separated by commas:
A floating point value for the cut-off frequency.
A floating point value for the sampling frequency.
An even integer value for the number of poles; higher values increase computational effort and can eventually cause the filter to become unstable.
To continue to build your expression, position the cursor in the expression window and type in or select the functions, operators, and X–Y data you want to include.
To evaluate and display your expression, click Plot Expression.
To save your new X–Y data object, click Save As and then provide a name in the dialog box that appears.
Saving your data object makes it available for future operations within this session and for inclusion in X–Y plots containing multiple data objects.
When you are finished, click Cancel to close the dialog box.
