When performing vibration analysis, understanding spectral resolution is very important. It directly influences our ability to identify and diagnose machinery faults. Here are the key points:

1. Spectral Resolution:
○ Spectral resolution refers to the ability to distinguish between adjacent
frequencies in a vibration spectrum.
○ It determines how finely we can dissect the frequency domain to pinpoint
specific vibration components.

2. Frequency Resolution Formula:
○ The frequency resolution (Δf) is inversely proportional to the total

○ acquisition time (T) and is given by: where:
■ (Fs) is the sample rate of the raw waveform.
■ (N) is the number of samples in the signal.

3. Lines of Resolution (LOR):
○ LOR represents the number of frequency bins or lines in the spectrum.
○ Higher LOR provides better resolution, allowing us to distinguish closely
spaced peaks.
○ LOR is calculated as:

4. Practical Considerations:
○ Collecting data with sufficient resolution is essential.
○ A balance must struck between capturing high-frequency details and avoiding
excessive noise.
○ Too few lines may miss critical information, while too many lines can lead to
longer acquisition times.

5. Example:
○ Suppose we collect a spectrum with an Fmax of 1,600 Hz and 800 lines of
resolution.
○ The resolution on our plot will be 1,600 / 800 = 2 Hz.
Remember, accurate vibration analysis relies on obtaining data with the right balance of
frequency coverage and resolution.