Adaptive fast iterative filter Holo-spectrum analysis and its applications to fault diagnosis of rolling bearing DOI
Guoliang Peng, Jinde Zheng,

Baohong Tong

et al.

Journal of Vibration and Control, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 13, 2024

As a signal demodulation analysis technique, Holo–Hilbert spectral (HHSA) excels in capturing the intricate cross-scale coupling dynamics present nonlinear and non-stationary vibration signals. Nonetheless, HHSA suffers from lack of rigorous mathematical foundation, is subject to modal mixing constraints, exhibits limited noise robustness. To address aforementioned issues, this study presents an innovative referred as adaptive fast iterative filter Holo-spectrum (AFIFHSA). Also, filtering (AFIF) algorithm incorporated within AFIFHSA designed dynamically achieve decomposing. From that, several approximate narrowband signals, possessing physical significance at instantaneous frequency, trend term can be obtained. Furthermore, marginal spectrum (MS) obtained by utilized represent effectiveness fault characteristic identification. Lastly, simulation measured data are showcase AFIFHSA’s exceptional capabilities recognizing high-resolution eximious modulation relationships. The outcomes additionally illustrate that AFIFHSA, proposed, showcases superior performance identification robustness with comparison other conventional approaches.

Language: Английский

Linking cognitive reserve to neuropsychological outcomes and resting-state frequency bands in healthy aging DOI Creative Commons
Vanesa Pérez, Vanesa Hidalgo, Alicia Salvador

et al.

Frontiers in Aging Neuroscience, Journal Year: 2025, Volume and Issue: 17

Published: March 17, 2025

As the proportion of older people has surged in past 100 years, healthy aging emerged as a crucial topic neuroscience research. This study aimed to investigate spectral power EEG frequency bands during resting-state with high and low cognitive reserve (CR). To do so, 74 (55-74 years old) were recruited divided into two groups based on their level CR: CR (n = 41; 21 men 20 women) 33; 15 18 women). Both participated assessment 3 min recording under conditions eyes open (EO) closed (EC). was analyzed across four bands: delta (0.1- < 4 Hz), theta (4- 8 alpha1 (8-10 alpha2 (10-12), beta (14-30 focusing five cortical regions interest. Neuropsychological tests did not reveal significant differences between most measures. However, analysis showed that individuals exhibited lower different brain regions, compared those CR. These findings suggest tend function more efficiently, relying fewer neural resources sustain performance. In contrast, may engage compensatory mechanisms, indicated by increased while resting, conceivably reflecting brain's effort preserve function.

Language: Английский

Citations

0
Adaptive fast iterative filter Holo-spectrum analysis and its applications to fault diagnosis of rolling bearing DOI
Guoliang Peng, Jinde Zheng,

Baohong Tong

et al.

Journal of Vibration and Control, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 13, 2024

As a signal demodulation analysis technique, Holo–Hilbert spectral (HHSA) excels in capturing the intricate cross-scale coupling dynamics present nonlinear and non-stationary vibration signals. Nonetheless, HHSA suffers from lack of rigorous mathematical foundation, is subject to modal mixing constraints, exhibits limited noise robustness. To address aforementioned issues, this study presents an innovative referred as adaptive fast iterative filter Holo-spectrum (AFIFHSA). Also, filtering (AFIF) algorithm incorporated within AFIFHSA designed dynamically achieve decomposing. From that, several approximate narrowband signals, possessing physical significance at instantaneous frequency, trend term can be obtained. Furthermore, marginal spectrum (MS) obtained by utilized represent effectiveness fault characteristic identification. Lastly, simulation measured data are showcase AFIFHSA’s exceptional capabilities recognizing high-resolution eximious modulation relationships. The outcomes additionally illustrate that AFIFHSA, proposed, showcases superior performance identification robustness with comparison other conventional approaches.

Language: Английский

Citations

0