The vertical cross-section displays a graph to the right of the spectrogram with the data for a vertical slice down the spectrogram.The slice can be moved by dragging the horizontal crossbar up and down on the spectrogram. The horizontal cross-section displays a graph under the spectrogram with the data for a horizontal slice across the spectrogram.The mouse cursor displays the X, Y, and Z values of the data under the cursor.These options can be found under Spectrogram Graph Options. There are several graph options that are useful for analysis. If the tach sweep direction doesn’t match the direction of the tach sweep, the tool will report little to no readings. Tach sweep direction: triggers spectrogram readings and can be configured to match the direction of the tach trace sweep.For example, these values may be changed to focus on a subset of the total RPM range or to purposely exclude errant data. Min and max tach values: limit the tachometer range of the spectrogram.
In addition to these settings, the tach spectrogram includes: FFT width: width of time data each FFT represents.FFT spacing: distance in time between FFT anchor points (left, center, right) an approximation based on the spectrogram range and frame count.The user cannot define these properties directly. The FFT spacing and FFT width are properties of the amount of time analyzed with respect to the FFT sample count and number of FFTs. Min and max frequency: limits the frequency range of the spectrogram plot.Frame count: number of FFTs that make up the spectrogram.In ObserVIEW, there is a time spectrogram and tachometer spectrogram graph option.įor the time spectrogram, the following settings can be adjusted: They are selected based on the highest peak acceleration level within the user-defined analysis range. In ObserVIEW, you can automatically find the orders with the highest amplitude. With order analysis, engineers can identify how the vibration of an individual component contributes to the overall level. Orders identify the relationship between the response of a rotational component at a specific amplitude, the RPM, and the frequency of rotation. Spectrograms can also be used to identify order lines. Still, atypical bands can indicate very useful information regarding potential damage. In a spectrogram, there are many indicators of damage and they can be complex. In comparison to an FFT, a spectrogram gives a better look into how the vibration changes over time. It illustrates the patterns of energy change which may not be visible in an FFT or PSD. For this reason, a spectrogram is a helpful tool for analyzing real-world data where there are various frequency components and/or mechanical and electrical noise.Ī spectrogram is most helpful for vibration analysis in a changing environment. As a collection of time-frequency analyses, the spectrogram can be used to identify characteristics of nonstationary or nonlinear signals. How Spectrograms Differ from other Signal Processing AnalysesĪ time-domain analysis can point out a defect in a DUT but does not specify the location or nature of the defect. The result is a jagged spectrogram with many gaps in the data. In the graphs below, the number of FFTs is reduced from 500 to 50. Conversely, a 1-minute spectrogram can be defined with 1000 FFTs, which would cover all time samples with some overlap between FFT analyses. However, there would be many gaps between FFT analyses. The Frame Count parameter determines the number of FFTs used to create the spectrogram and, as a result, the amount of the overall time signal that is split into independent FFTs.įor instance, it is possible to define a spectrogram covering 10 hours with only 10 FFT frames.
The spectrogram is a plot of the spectrum on each segment. Then, the fast Fourier transform (FFT) is applied to each segment. To generate a spectrogram, a time-domain signal is divided into shorter segments of equal length. With the data, users can locate strong signals and determine how frequencies change over time. The color scale is red-green-blue, where blue corresponds to low amplitudes, or “loudness,” and red corresponds to high amplitudes.įor vibration testing, spectrograms can be used to analyze the frequency content of a waveform to distinguish different types of vibration. In ObserVIEW, the tachometer- and time-based spectrogram graph can be viewed in two or three dimensions. Spectrograms can be two-dimensional graphs with a third variable represented by colors or three-dimensional graphs with a fourth color variable.
A spectrogram displays the strength of a signal over time at a waveform’s various frequencies.