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Measurement methods · Signal analysis

Frequency spectra and FFT resolution

Does the tallest spectrum peak always identify the mode?

A spectrum separates a recording into frequency components. Understanding sampling, record length and leakage is essential before reading a resonant frequency from a peak.

Try the interactive demo

Start with something familiar

Hearing two people speak at once gives one mixed sound at your ear. A frequency spectrum asks which repeating components are present in a mixed recording; it does not automatically identify which object produced each component.

Time: components mixed

Time

One synthetic signal, two frequencies

Frequency: components separated

f₁f₂

Schematic peaks, not a measured spectrum

Diagram · Two component waveforms add into one signal; frequency analysis separates their contributions. The additional lab computes an FFT of a known synthetic signal.
  1. Notice what changes

    The time trace shows how pressure varies as time passes. The spectrum reorganizes the same samples by frequency: horizontal position means oscillations per second, not time.

  2. Understand why

    Listening for longer can help distinguish nearby frequencies. A shorter record has broader features and more widely spaced FFT bins. Drawing more points by zero-padding does not add missing observations.

  3. Connect it to wood and making

    A wood tap contains several modes and room sound. A strong peak is a candidate, not proof of the intended bending mode. Move the tap, repeat and compare the spatial pattern.

Put names to the ideas

01

Bin spacing and duration

For N samples at sampling rate f_s, duration T = N/f_s and FFT bin spacing is f_s/N = 1/T. Longer useful recordings provide finer spacing, but a decaying signal eventually reaches noise.

02

Leakage and windows

A finite record can spread a component over nearby bins. A window reduces some leakage while changing peak width and amplitude. State the window when comparing spectra or using a half-power width.

03

A strong peak is not an identity

Tap and microphone positions weight the modes differently. Room sound, mains interference or an unwanted mode may produce the strongest peak. Use repeat taps and modal evidence.

Δf=fsN=1T,fNyquist=fs2\Delta f=\frac{f_s}{N}=\frac{1}{T},\qquad f_{\mathrm{Nyquist}}=\frac{f_s}{2}

T is the useful observation duration. The spacing 1/T means 0.5 seconds gives 2 Hz bins. Peak width also depends on windowing and damping, so bin spacing alone is not a guarantee that two peaks are resolved.

A worked example

A 0.5 s useful record has 2 Hz bin spacing. Zero-padding can make the displayed curve smoother, but cannot create the resolving power of an actually longer recording.

Explore it yourself

Record unclipped taps, avoid automatic voice processing where possible, compare repeated spectra, and save the chosen peak with the original recording.

CONTROLLED TEACHING MODEL
Observation duration
0.125 s
Bin spacing
8.0 Hz
Known frequencies
200 / 206 Hz
Time waveform · fixed amplitude scale0–40 msFFT · dB relative to visible peak0−60160320 Hz
Two equal-amplitude synthetic sinusoids, 2048 samples/s, periodic Hann window, no zero-padding. Dotted lines mark the known inputs, not measured peak estimates. No microphone is used.

Check your understanding

Can zero-padding a short recording replace a longer useful recording?

References