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Transient analysis allows you to check the signal level over time like an oscilloscope. If you want to check the frequency components contained in the signal, it is convenient to use the FFT function. Signal distortion and noise components can be checked by simulation.
This time, I will introduce the FFT function.
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What is FFT?
FFT (Fast Fourier Transform) stands for Fast Fourier Transform.
Like a spectrum analyzer, SPICE calculates and displays the frequency components and levels (power) contained in the signal. The FFT function is a built-in function of Waveform Viewer because it performs calculations based on the data obtained by transient analysis (time axis).
Let's use the FFT function!
work procedure
This time, as an example, we will use transient analysis to check a signal waveform that combines three sine waves with different frequencies and magnitudes, and use the FFT display function to check the frequency distribution.
The transient analysis results are shown in Figure 2.
The frequency component and magnitude cannot be determined just by looking at the waveform of this OUT terminal.
So let's use the FFT display function.
Select View→FFT from the menu bar.
Then, a Box like the one in Fig. 4 will appear, so normally just press "OK".
The FFT display results are shown in Figure 5.
A logarithmic graph with signal level (dB) on the vertical axis and frequency (Hz) on the horizontal axis was obtained.
There are peaks at frequencies of 1 kHz, 3 kHz, and 10 kHz, and we were able to grasp the components and magnitude of the waveform.
Usage points
When using the FFT function, it is recommended to set the command “.options plotwinsize=0” to disable compression of analysis data. A low noise floor is obtained using this command (Figure 5).
Also, setting the transient command “Maximum Time Step” to less than 1/100th of the signal period will give good FFT results. However, if it is set short, the simulation time will take a little longer, so please make adjustments while looking at the balance.
For comparison, we removed the plotwinsize specification in .options and ran the simulation with the default Maximum Time Step. Compared to the previous results in Figure 5, the noise floor at the base is larger, and peaks are visible at unintended frequencies (Figure 6).
From this result, you can understand that the command “.options plotwinsize=0” is important for FFT analysis.
Let's look at the output voltage signal of the power supply IC with FFT!
Previously, let's use LTspice - Confirming the operation of the DC-DC converter confirmed the ripple voltage level of the output voltage, so I would like to confirm the frequency component with the FFT function.
The circuit uses the LT8640 Demo file. Since the FFT analysis requires steady-state results, check the ripple voltage after power-up. Therefore, the simulation time for transient analysis is set to 500u~700usec.
The output voltage ripple waveform is shown in Figure 8.
FFT analysis confirms that not only the 1MHz switching frequency component but also 2x, 3x, even and odd frequency components are included (Fig. 9).
Noise from power supply circuits may affect peripheral circuits and EMI tests.
By using the FFT function to understand the frequency components, noise countermeasures such as filter design can be studied through simulation.
Please take this opportunity to try the FFT function!
LTspice demo file verified this time
The two simulation files that were performed this time are stored. Please try!
At the end
This time, we introduced the FFT function!
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