Grouped FFT Computation Processor

Modified on Tue, 30 Nov 2021 at 04:49 PM


The Grouped FFT Computation Processor computes Fast Fourier Transformations for datasets grouped by a given time-window size. It uses a divide and conquer algorithm that efficiently decomposes digital signals into frequencies.


As input, the processor requires a dataset with a timestamp column (of type datetime) and numeric column to which compute the FFT.


For more information, check the linked section.


The processor returns a table with five columns: The sensor column name, the window number and the corresponding FFT properties (frequency, power magnitude and phase).


Example Input


In the following workflow, the Ordering processor is used to order the output data by ascending window number. This doesn't affect the result, it just makes it easier to interpret.

Example Configuration


Additional Information

This section clarifies some of the concepts appearing in the processor configuration:

  • Zero padding simply refers to adding zeros to a time-domain signal to increase its length.
  • Interpolation is the process of estimating and inserting missing values in time series data.

Related Articles

Moving Average Processor

Grouped Root Mean Square Processor

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