What Is Windowing in FFT and Why It Matters
Interactive demonstration of Rectangular and Hanning windows
🎯 Key Concept: What is Windowing?
When we measure vibration signals, we can only capture finite segments of data. The FFT assumes this segment repeats forever, which can cause "leakage" - energy spreading across frequencies. Window functions reduce this effect by smoothly tapering the signal at the edges.
Process Flow: Time Signal → Multiply by Window → Windowed Signal (still time domain) → Apply FFT → Frequency Domain
1. Time Domain Signal
2. Window Function
3. Windowed Signal
4. Frequency Domain (FFT)
Understanding the Plots
Current Setup: You have a 3.0 Hz signal with 2.5 cycles in the measurement window.
What's happening: With non-integer cycles (2.5), the signal doesn't end where it started. This discontinuity causes energy to "leak" into other frequencies in the FFT.
❗ The FFT's Hidden Assumption
The FFT assumes your measured signal repeats infinitely. If you measure 2.5 cycles of a sine wave, the FFT thinks the pattern continues as: 2.5 cycles → 2.5 cycles → 2.5 cycles... forever. This creates a sharp discontinuity at each junction where the signal "jumps" from its end value back to its start value.
This discontinuity is what causes leakage - it's not real vibration energy, it's a mathematical artifact!
💡 Practical Applications
- Rectangular Window: Use for transient events (impacts, shocks) that naturally start and end at zero
- Hanning Window: Use for continuous machine vibration monitoring - reduces leakage by 90%+
- Industry Standard: Most vibration analyzers default to Hanning for good reason
- Integer Cycles: When possible, adjust measurement time to capture whole cycles
📊 Real-World Example
Monitoring a pump at 3600 RPM (60 Hz):
- 0.1 second window = 6 cycles (might show leakage)
- 1 second window = 60 cycles (good frequency resolution)
- 10 second window = 600 cycles (excellent resolution, but slow updates)
Window Duration = Number of Cycles ÷ Signal Frequency
What Is Windowing in FFT and Why It Matters
Interactive demonstration of Rectangular and Hanning windows
🎯 Key Concept: What is Windowing?
When we measure vibration signals, we can only capture finite segments of data. The FFT assumes this segment repeats forever, which can cause "leakage" - energy spreading across frequencies. Window functions reduce this effect by smoothly tapering the signal at the edges.
1. Time Domain Signal
2. Window Function
3. Windowed Signal
4. Frequency Domain (FFT)
Understanding the Plots
References (clickable):
I am a senior CAE and Automation Engineer at Scania with over 7 years of hands-on experience in Finite Element Analysis (FEA). My daily work involves advanced simulations focusing on strength and durability analysis, helping design more reliable and efficient products.
Before joining Scania, I conducted research at KTH Royal Institute of Technology, where I focused on the additive manufacturing of heat exchangers. My work has been recognized internationally and published in peer-reviewed journals. You can find my publications on Google Scholar.
I am a senior CAE and Automation Engineer at Scania with over 7 years of hands-on experience in Finite Element Analysis (FEA). My daily work involves advanced simulations focusing on strength and durability analysis, helping design more reliable and efficient products.
Before joining Scania, I conducted research at KTH Royal Institute of Technology, where I focused on the additive manufacturing of heat exchangers. My work has been recognized internationally and published in peer-reviewed journals. You can find my publications on Google Scholar.