Fast Fourier Transform (FFT)

This nodes performs a Fast Fourier Transform in a desired numeric timeseries data column. It requires the KNIME Python extensions with Python 3 set up.

The dataset cannot contain missing values.

Additionally, the component produces an interactive view displaying the normalized power spectrum of the signal.

The component requires the following extensions:
- KNIME Python Integration (https://kni.me/e/9Z2SYIHDiATP4xQK)
- KNIME JavaScript Views (https://kni.me/e/0qveOxOA3751S6Vx)

Topics: IoT, Internet of Things, Signal Processing

Options

Column to Transform
The selected column to be transformed with the Fast Fourier Transform.
Sampling Frequency
The sampling frequency on which the signal was acquired in Hz.
Tappering Window
Select a tappering window to deal with spectral leakage. The explanation of the different window types and their spectral responses can be found on https://docs.scipy.org/doc/scipy/reference/signal.windows.html

Input Ports

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The Input data. It should contain a numeric time series column.

Output Ports

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Output a table containing the original columns and two adittional columns with the resolved frequencies and their normalized power. Normalization is performed by dividing the raw amplitudes by the length of the signal.

Nodes

Extensions

Links

Download

To use this component in KNIME, download it from the below URL and open it in KNIME:

Download Component
On NodePit since: 2022-06-07
Last update: 2024-12-17
Created with KNIME version: v4.2.0

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