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I recently observed this phenomenon that when a signal is clipped the harmonics start to appear only after a certain level.

The Python code to reproduce the effect is given below. The signal has 3 components at 30, 60 and 90 Hz. So a maximum possible peak to peak voltage will be 3. I clipped the signal at various levels and observed the magnitude spectrum but the harmonics start to visibly noticable only if the clipping goes below -2.5 and 2.5.

enter image description here enter image description here

Is this a well-known phenomenon? What is the possible explanation behind this?.

import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
from scipy.io import wavfile

labelsize   =   12
width       =   3.5
height      =   width / 1.618
lwidth      =   0.9

plt.rc('font', family='serif')
plt.rc('text', usetex=True)
plt.rc('xtick', labelsize=labelsize)
plt.rc('ytick', labelsize=labelsize)
plt.rc('axes', labelsize=labelsize)

def MagnitudeSpectrum(data, Fs, clip):
    P = 20*np.log10(np.abs(np.fft.rfft(data)))
    f = np.linspace(0, Fs/2, len(P))

    fig, ax = plt.subplots()
    fig.subplots_adjust(left=.20, bottom=.25, right=.96, top=.90)

    plt.plot(f, P, color='k', ls='solid', linewidth=lwidth, label='')
    plt.xlim(0, 500)
    plt.title('Signal Clipped BW '+str(-1*clip)+' and'+str(clip))
    plt.xlabel('Frequency [Hz]')
    plt.ylabel('Magnitude [dB]')
    # plt.show()
    fig.set_size_inches(width, height)
    fig.savefig('SignalMagSpectro_'+str(clip)+'.png', dpi = 600)

cliplevels = np.arange(2.2, 3.2, 0.1)

for clip in cliplevels:
    Fs = 44100.0
    t = np.arange(0, 10, 1/Fs)
    data = np.sin(2*np.pi*30*t)+np.sin(2*np.pi*60*t)+ np.sin(2*np.pi*90*t) +0.1*np.random.randn(len(t))
    data = np.clip(data, -1*clip, clip)
    MagnitudeSpectrum(data, Fs, clip)
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    $\begingroup$ have you drawn and compared the two time-domain waveforms? $\endgroup$ – robert bristow-johnson Mar 27 '18 at 7:23
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    $\begingroup$ yep, as @robertbristow-johnson indicates, the phenomenom is best understood when you look at the time-domain waveform plot. If you want to give it a name, it's increasing nonlinearity of your system, necessarily leading to introduction of spurs/intermodulation products, and you can predict that by approximating your clipping transfer function with a power series. $\endgroup$ – Marcus Müller Mar 27 '18 at 10:25
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Is this a well-known phenomenon?

Yes, of course. You will see harmonics as soon as your clip point is lower than the maximum amplitude in the time domain. The latter is a function of the relative phases between the harmonic components. In your case the max amplitude is indeed 2.5 (plus whatever the noise adds).

If you change the phases you will get a different clip point. For example, if you use cosine instead of sine, you will get a clip point of 3.0

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