The sensible bearing vibration signal evaluation and complexity evaluation. three.two. Comparison among
The sensible bearing vibration signal analysis and complexity evaluation. 3.2. Comparison amongst MEDE, MDE, MPE and MSE To show the effectiveness of MEDE in evaluating the complexity and irregularity of a time series, MEDE of two noise signals (i.e., white noise and 1/f noise) are calculated. For a convenient comparison, 3 common entropies (i.e., MDE, MPE and MSE) of two noise signals (i.e., white noise and 1/f noise) are calculated to measure the complexity from the time series. Also, to examine the accuracy of complexity measures of distinctive entropies, 20 groups of white noise and 1/f noise are generated randomly. Figure six shows time domain waveform and amplitude spectrum of a group of white noise and 1/f noise. Figure 7a,b plot the error bar of distinct entropies (i.e., MEDE, MDE, MPE and MSE) of white noise and 1/f noise, respectively. Observed from Figure 7a, as the scale element increases, imply worth curve of 3 entropies (i.e., MEDE, MDE and MSE) of white noise possess a downward trend, whereas the imply value curve of MPE of white noise generally remains unchanged. That may be, the sensitivity of MEDE, MDE and MSE in detecting complexity of white noise is superior than MPE. As shown in Figure 7a, standard deviation of MEDE Entropy 2021, 23, x FOR PEER Review 12 of 30 of white noise at each and every scale issue is certainly smaller sized than MDE. That indicates that MEDE features a superior accuracy in complexity measures of white noise than MDE. Observed from Figure 7b, as the scale aspect increases, the mean worth curve of 3 entropies (i.e., MDE, entropies (i.e., MDE, MPE and MSE) of 1/fstable,is reasonably stable, whereas imply worth MPE and MSE) of 1/f noise is fairly noise whereas imply worth curve of MEDE of curve of MEDE of 1/f steadily, which means that MEDE is much more sensitive much more sensitive 1/f noise MCC950 Technical Information decreases noise decreases gradually, which indicates that MEDE is for uncertainty for uncertainty estimation of 1/f noise than other 3 entropiesand MSE). Additionally, in estimation of 1/f noise than other 3 entropies (i.e., MDE, MPE (i.e., MDE, MPE and MSE). In addition, in Figure 7b, typical deviation of MEDE of 1/f noise atthan that of MDE Figure 7b, typical deviation of MEDE of 1/f noise at each scale is less each scale is less than that of MDE and validates that MEDE can give an precise complexity estimation and MSE. This additional MSE. This further validates that MEDE can provide an accurate complexity estimation MEDE noise. That in complexity measurement and function extraction for 1/f noise. That is, for 1/f is effective is, MEDE is successful in complexity measurement of function extraction of andnonstationary signals.nonstationary signals.White noise Normalized amplitude 0.5 0 .5 0 1000 2000 3000 Data length 1/f noise 4000 5000 Normalized amplitude 1 1 White noise0.0.1 0.two 0.3 0.four Normalized frequency (Hz) 1/f noise0.Normalized amplitude0.five 0 .5 0 1000 2000 3000 Information length 4000Normalized amplitude0.0.1 0.2 0.three 0.4 Normalized frequency (Hz)0.Figure six. Time domain waveform and amplitude spectrum of two noise signals (i.e., white noise Figure 6. Time domain waveform and amplitude spectrum of two noise signals (i.e., white noise and 1/f noise). and 1/f noise).MEDE of white noise MDE of white noise MPE of white noise MSE of white noiseEntropy value 4.5 4 three.5 three two.five two MEDE of 1/f noise MDE of 1/f noise MPE of 1/f noise MSE of 1/f noise5 4 3 two 1 0 VBIT-4 MedChemExpress 5Entropy value1.NormaliNormali.five 0 1000 2000 3000 Information length 40000.1 0.2 0.3 0.four Normalized frequency.