Settings for Analyzing Vibration Signals

November 7, 2023

These “Ask Joel” videos walk us through the general parameters of analyzing vibration signals, particularly converting time data to the frequency domain.

Time vs. Frequency

Complex time-domain data–the signal’s acceleration over time–is generally a combination of many sinusoidal waves. As such, engineers cannot use time-domain data to observe the frequency content and must convert the data into the frequency domain. This video illustrates the impact of doing so.

Learn more: Time vs. Frequency Domain

Lines of Resolution

The process of converting random vibration time-domain data into the frequency domain requires the engineer to select certain parameters. Many vibration control software programs use the fast Fourier transform (FFT) to convert the time data to a frequency-domain power spectral density (PSD).

For the FFT process, the “lines of resolution” parameter contributes to the frequency bin widths in the PSD. A higher lines of resolution value has several benefits; for instance, small bin widths result in a more accurate and smoother PSD plot.

Learn more: Calculating PSD from a Time History File

G2/Hz and GRMS

Time-domain vibration data is displayed in the acceleration unit G, often referred to as Gpk (“G-peak”). Frequency-domain vibration data is often displayed as a PSD plot with units of G2/Hz. Engineers also refer to the GRMS of a random vibration test. This video discusses the units of G2/Hz and GRMS, how they are derived from time data, and their importance.

Sample Rate (Nyquist Theorem)

The sample rate determines the number of data points a system collects per second. Engineers must select a proper sample rate for an accurate representation of the signal. Too low of a sample rate results in an inaccurate representation. The Nyquist theorem determines that the sample rate should be greater than twice the test’s predicted highest frequency.

Learn more: The FFT and Digital Sampling

Analysis Lines

Engineers must select an appropriate “analysis lines” value when converting time-domain data to frequency-domain. A low analysis lines value results in an inaccurate conversion of time-domain data to the frequency domain. A higher value results in a more accurate conversion but a slower response time.

Tuning Fork vs. Cellphone App

A pure tone from a third-party cell phone application confirms that the VR ObserVIEW software accurately measures the vibrations of a tuning fork. We can hear and observe when the tuning fork is out of tune with the app.

Wrap Up

This video explains the relationship between the concepts presented in this lesson. It investigates proper sample rate settings–particularly as they relate to the Nyquist theorem–and the possibility of aliasing occurring with too low of a sample rate.