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Mechanical and Ocean Solutions

Signal Processing

Jean Baptiste Joseph Fourier (1768 - 1830) was a French Mathematician best known for initiating the investigation of the Fourier Series, and their applications to problems of heat transfer and vibrations. Since Fourier's time, numerous papers and books dealing with Fourier Theory have been published. The Discrete Fourier Transform (DFT) is a discrete approximation of the Fourier Integral, and is used to transform time series data from the time domain to the frequency domain. The DFT is cumbersome when working with large sets of data, so in the 1960's, J.W. Tukey and J.W. Cooley developed the Cooley - Tuckey algorithm, also known as the Fast Fourier Transform (FFT), which quickly and efficiently evaluates the DFT.

The plots below show the Frequency, Amplitude, and Power spectrums of an automobile's vibration data. A total of 4096 data points were analyzed at a sampling rate of 10khz.


FFT Applications

Motors, pumps, compressors, rollers, and other rotating machinery vibrate when they are in operation. When a machine vibrates too much, it becomes obvious that something is wrong. The best approach to maintaining rotating machinery is to take periodic readings from acceleration transducers. Imbalances, misalignments, and bearing instabilities will appear as changes in the machine's vibration (power) spectrum, or 'Mechanical Signature'. Corrective action can then be taken before a worsening situation becomes critical.

Fast Fourier Transform (FFT)

The FFT shows the spectral content of your vibration signal, which include the amplitude and phase of harmonics in your signal.

FFT is the best analysis to use for stationary, non varying signals.

Power Spectrum

The power spectrum, which is the absolute magnitude of the FFT, adds physical meaning to your signal analysis. The power spectrum gives you the power of your signal in each frequency band.