Results 41 to 50 of about 36,269 (184)

A Comparative Study of Time-Frequency Representations for Fault Detection in Wind Turbine [PDF]

, 2011
To reduce the cost of wind energy, minimization and prediction of maintenance operations in wind turbine is of key importance. In variable speed turbine generator, advanced signal processing tools are required to detect and diagnose the generator faults ...
BARAKAT, Georges, BENBOUZID, Mohamed, CHARPENTIER, Jean-Frederic, CHOQUEUSE, Vincent, EL BOUCHIKHI, EL HOUSSIN   +4 more
core   +6 more sources

A technique to Improve the Empirical Mode Decomposition in the Hilbert-Huang Transform [PDF]

, 2012
The Hilbert-based time-frequency analysis has promising capacity to reveal the time-variant behaviors of a system. To admit well-behaved Hilbert transforms, component decomposition of signals must be performed beforehand.
Chen, Yangbo, Feng, Maria Q.
core   +2 more sources

Diagnostics of gear faults based on EMD and automatic selection of intrinsic mode functions [PDF]

, 2011
Signal processing is an important tool for diagnostics of mechanical systems. Many different techniques are available to process experimental signals, among others: FFT, wavelet transform, cepstrum, demodulation analysis, second order ciclostationarity ...
P. Pennacchi, R. Ricci
core   +1 more source

Characterization of non-linear bearings using the Hilbert–Huang transform

Advances in Mechanical Engineering, 2015
Changes in the performance of bearings can significantly vary the distribution of internal forces and moments in a structure as a result of environmental or operational loads.
Arturo González, Hussein Aied
doaj   +1 more source

Optimized Time–Frequency Analysis for Induction Motor Fault Detection Using Hybrid Differential Evolution and Deep Learning Techniques

International Journal of Adaptive Control and Signal Processing, EarlyView.
Workflow of the parameter optimization process for ITSC fault detection, applying Differential Evolution optimization and the Smooth Pseudo Wigner‐Ville Distribution for signal processing. The optimized parameters are then used in the failure identification pipeline, which combines the signal processing with a YOLO‐based architecture for fault severity
Rafael Martini Silva, Avyner Lorran de Oliveira Vitor, Marcelo Favoretto Castoldi, Alessandro Goedtel, Wesley Angelino Souza   +4 more
wiley   +1 more source

Characterizing Intermittency of 4-Hz Quasi-periodic Oscillation in XTE J1550-564 using Hilbert-Huang Transform [PDF]

, 2015
We present the time-frequency analysis results based on the Hilbert-Huang transform (HHT) for the evolution of a 4-Hz low-frequency quasi-periodic oscillation (LFQPO) around the black hole X-ray binary XTE J1550-564. The origin of LFQPOs is still debated.
Chou, Yi, Hu, Chin-Ping, Su, Yi-Hao, Yang, Ting-Chang   +3 more
core   +2 more sources

The Adaptive Trajectory of the Normal Force Vector in the Polishing of Curved Surface Component Robots

Advanced Intelligent Systems, EarlyView.
This study uses iterative learning control and voice coil motor to keep normal force constant in curved surface polishing. A mechanism‐data fusion model adjusts robotic posture via real‐time feedback for adaptive tracking control of normal force vector direction.
Jiale Xu, Haibin Huang, Hui Long, Shijing Lei   +3 more
wiley   +1 more source

Beyond Frequency Band Constraints in EEG Analysis: The Role of the Mode Decomposition in Pushing the Boundaries

Signals, 2023
This study investigates the use of empirical mode decomposition (EMD) to extract intrinsic mode functions (IMFs) for the spectral analysis of EEG signals in healthy individuals and its possible biological interpretations. Unlike traditional EEG analysis,
Eduardo Arrufat-Pié, Mario Estévez-Báez, José Mario Estévez-Carreras, Gerry Leisman, Calixto Machado, Carlos Beltrán-León   +5 more
doaj   +1 more source

Caracterización multicanal no lineal de señales EMG con la transformada Hilbert-Huang [PDF]

, 2009
En este documento se presenta una propuesta de caracterización multicanal no lineal y adaptativa de señales electromiográficas de superficie usando la transformada Hilbert-Huang, la cual es una técnica de procesamiento digital reciente basada en la ...
Castellanos Domínguez, César Germán, Orozco Gutiérrez, Álvaro Ángel, Pinzón Morales, Rubén Darío   +2 more
core  

Autonomous Recognition of Retained Secretions in Central‐Airway Based on Deep Learning for Adult Patients Receiving Invasive Mechanical Ventilation

Advanced Intelligent Systems, EarlyView.
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang, Zhuoran Xiao, Meng Wang, Jianchao Li, Chunjing Tao, Jiangzhen Guo, Yubo Fan   +6 more
wiley   +1 more source