A permutation algorithm based on dynamic time warping in speech frequency-domain blind source separation

2017 ◽  
Vol 92 ◽  
pp. 132-141 ◽  
Author(s):  
Zhao Lv ◽  
Bei-bei Zhang ◽  
Xiao-pei Wu ◽  
Chao Zhang ◽  
Bang-yan Zhou
Keyword(s):  
Frequency Domain ◽  
Blind Source Separation ◽  
Dynamic Time Warping ◽  
Source Separation ◽  
Time Warping ◽  
Dynamic Time

Research on a feature extraction method for local faults in planetary gearboxes based on improved dynamic time warping

2021 ◽  
Vol 63 (8) ◽  
pp. 465-471
Author(s):  
Shang Zhiwu ◽  
Yu Yan ◽  
Geng Rui ◽  
Gao Maosheng ◽  
Li Wanxiang
Keyword(s):  
Feature Extraction ◽  
Fault Diagnosis ◽  
Frequency Domain ◽  
Extraction Method ◽  
Dynamic Time Warping ◽  
Spectral Feature ◽  
Time Warping ◽  
Feature Extraction Method ◽  
Time Frequency ◽  
Dynamic Time

Aiming at the local fault diagnosis of planetary gearbox gears, a feature extraction method based on improved dynamic time warping (IDTW) is proposed. As a calibration matching algorithm, the dynamic time warping method can detect the differences between a set of time-domain signals. This paper applies the method to fault diagnosis. The method is simpler and more intuitive than feature extraction methods in the frequency domain and the time-frequency domain, avoiding their limitations and disadvantages. Due to the shortcomings of complex calculation, singularity and poor robustness, the paper proposes an improved method. Finally, the method is verified by envelope spectral feature analysis and the local fault diagnosis of gears is realised.

Multichannel sparse spike deconvolution based on dynamic time warping

2021 ◽  
Author(s):  
Xiaowei Zhao ◽  
Shangxu Wang ◽  
Sanyi Yuan ◽  
Liang Cheng ◽  
Youjun Cai
Keyword(s):  
Dynamic Time Warping ◽  
Time Warping ◽  
Dynamic Time
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