“…In this comparative experiment, a comprehensive timefrequency domain feature vector is used as a contrastive feature vector, which contains nine time-domain features (root mean square, absolute mean value, mean square, kurtosis, skewness, waveform factor, peak factor, impulsion index, and margin index) and five frequency-domain features (mean value, standard deviation, root mean square, center frequency, and frequency kurtosis). Referring to the related researches (Wiener et al, 2021;Wu et al, 2022), the combination of particle collision frequency f c and maximum amplitude A max in the time-domain signal is used as another contrastive feature vector. Then SAWOA-MPE is compared with the two categories of feature vectors by using the DF diagnosis model.…”