Sentence examples for Impulsive features from inspiring English sources

Complex wavelet based envelope detection method was designed to extract the impulsive features contained in the signal.

With this method, the fault-related impulsive features could be recognized, while the influence caused by non-fault modulation is eliminated.

The results show that, the CSMM is capable of generating demodulation signals with higher resolution, and the optimal scale band demodulation based on the CSMM can reliably extract impulsive features for bearing defect diagnosis.

The main goal of this paper is to exploit the low-rank physical structure of periodic impulsive features and further establish a weighted low-rank sparse model for bearing fault detection.

However, the nuclear norm regularization treats all singular values equally and thus ignores one basic fact that larger singular values have more information volume of impulsive features and should be preserved as much as possible.

Consequently, the impulsive features would be strengthened and the noise would be suppressed effectively.

Firstly, due to the periodic repetition mechanism of impulsive feature, an adaptive partition window could be designed to transform the impulsive feature into a data matrix.

Among different signal processing algorithms, morphological filter (MF) has attracted lots of attention because it could directly extract the geometric structure of the impulsive feature and only needs little computation.

Based on the frequency domain kurtosis criterion, a narrowband merging operation is employed to locate the optimal scale band that best reflects the impulsive feature from the CSMM analysis results.

When applied for impulsive feature demodulation of vibration signal of rolling element bearings, the integer-scale MM (ISMM) may lead to low resolution result and thus undermines its defect diagnosis capability.

Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis.