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FFT Analysis

Transform time-domain data into the frequency domain

Perform efficient data analysis on live data or an imported file with the fast Fourier transform (FFT). View changes in frequency and amplitude in a waveform, highlight harmonic excitation in a broad frequency range, and more.

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FFT Analysis in ObserVIEW

Efficient Data Analysis

ObserVIEW responds to any change to the settings with a fast and automatic recalculation of the computed parameters. The software can perform the calculation on live data streaming from Live Analyzer or an imported file.

Features of ObserVIEW’s FFT analysis include:

  • Up to 1,048,576 analysis lines (user-defined)
  • Industry-standard window functions with comprehensive support for the selection process
  • Standard, harmonic, and RMS cursor types and more
  • Quick reporting features, including copy and paste functionality
  • Live computation of data with Live Analyzer
  • AVD conversion (acceleration, velocity, displacement)

Live Analyzer

When VR hardware is connected to a Live Analyzer session, the user can access all analysis controls while live data are streamed in from the device. The user can pause the incoming data to perform a more in-depth analysis and/or export the waveform. They can then resume the live feed without losing any of the data that occurred while the stream was paused so long as the data was paused for less than the user-configurable buffer duration period.

 

Copy & Paste Feature

The copy and paste command in ObserVIEW allows the user to move data between graphs and software applications. In doing so, the user can perform an easy comparison of data from a multitude of applications. This can be useful for comparing graph data from different time locations, multiple test results, various test environments, and much more.

FFT analysis groups

What is the Fast Fourier Transform (FFT)?

ObserVIEW FFT Screenshot

In engineering, the frequency domain is the usual domain for analysis. For continuous data, engineers use the Fourier transform to project the time domain data into the frequency domain. To do so, the fast Fourier transform (FFT) uses sine or cosine waves of varying frequency, amplitude, and phase. The FFT is a computational algorithm that efficiently implements a mathematical operation called the discrete-time Fourier transform.

In a complex signal, the FFT helps the engineer to determine the frequencies that are being excited and the amplitude at each frequency. Additionally, it highlights the changes at frequency and amplitude and the harmonic excitation in a frequency range.

For a complex signal, the FFT can help to answer:

  • What frequencies are being excited?
  • What is the amplitude at each frequency?
  • What changes through the waveform?

The user can easily view changes in frequency and amplitude in a waveform and highlight harmonic excitation in a broad frequency range.

Window Functions

ObserVIEW includes the industry-standard window functions including Blackman, Hamming, and Hanning. The Help file also includes a comprehensive table of window functions for assistance with selection.

Blackman window in ObserVIEW

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