Results 11 to 20 of about 18,123 (142)

Feature Extraction of Weak Fault of Rolling Bearing based on TVF-EMD and TEO

Jixie chuandong, 2021
Aiming at the problem that the vibration signals for rotating machinery rotors are usually accompanied by strong noise， it is difficult to extract its effective information. A method of fault feature extraction based on time-varying filter empirical mode
Kexin Liu, Huer Sun, Fuwang Liang
doaj   +3 more sources

Applications of TVF‐EMD in Vital Signal Detection for UWB Radar

Journal of Sensors, 2021
When using pulsed ultra‐wideband radar (UWB) noncontact detection technology to detect vital signs, weak vital signs echo signals are often covered by various noises, making human targets unable to identify and locate. To solve this problem, a new method for vital sign detection is proposed which is based on impulse ultra‐wideband (UWB) radar.
Zhen Yang 0020, Chi Ma, Qingjie Qi, Xin Li 0107, Yan Li   +4 more
openaire   +2 more sources

Performance Comparison of Machine Learning Models for Annual Precipitation Prediction Using Different Decomposition Methods

Remote Sensing, 2021
It has become increasingly difficult in recent years to predict precipitation scientifically and accurately due to the dual effects of human activities and climatic conditions.
Chao Song, Xiaohong Chen
doaj   +2 more sources

Multi-scale wind speed prediction model based on improved escape algorithm for optimizing time-varying filtering empirical modal decomposition [PDF]

Scientific Reports
Wind energy’s stochasticity and volatility challenge grid stability and dispatch reliability. To overcome limitations of existing decomposition-based forecasting methods, this paper proposes an Improved Escape Algorithm (IESC) incorporating chaotic ...
Haili Zheng, Qian Wu, Xuanhan Lv, Peitong Zeng, Xiaoli Zhu, YuPan Zeng   +5 more
doaj   +2 more sources

Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm

Shock and Vibration, 2019
The separation and identification technology of noise sources is the focus and hot spot in the field of internal combustion engine noise research. Combustion noise and piston slap noise are the main noise sources of an internal combustion engine. However,
Jiachi Yao, Yang Xiang, Sichong Qian, Shuai Wang   +3 more
doaj   +2 more sources

Hybrid Time–Frequency Analysis for Micromobility-Based Indirect Bridge Health Monitoring [PDF]

Sensors
Bridges serve as vital connectors in the transportation network and infrastructure. Given their significance, it is crucial to continuously monitor bridge conditions to ensure the efficient operation of transportation systems.
Premjeet Singh, Harsha Agarwal, Ayan Sadhu   +2 more
doaj   +2 more sources

Dynamic prediction of adolescent sports injury probability based on the improved ARIMA model in the background of digital physical education teaching [PDF]

Scientific Reports
This study aims to solve the problem of dynamic prediction of sports injuries in adolescent physical education teaching. By integrating multi-source heterogeneous data and improving time series modeling, a real-time early warning system suitable for ...
Kai Wang
doaj   +2 more sources

Short-term wind farm cluster power point-interval prediction based on graph spatio-temporal features and S-Stacking combined reconstruction

Heliyon
Wind energy is becoming increasingly competitive, Accurate and reliable multi-engine wind power forecasts can reduce power system operating costs and improve wind power consumption capacity.
Xinxing Hou, Wenbo Hu, Maomao Luo
doaj   +2 more sources

Enhancing total hardness forecasting in water resources: a hybrid framework integrating machine learning, TVF-EMD signal decomposition, and XGBoost feature selection

Engineering Applications of Computational Fluid Mechanics
Total Hardness (TH) is a critical hydrochemical parameter influencing water quality management in industrial, potable, and agricultural systems. Accurate TH forecasting is essential for sustainable resource utilization but remains challenging due to the ...
Chujie Zhou, Sijun Wang, Meysam Salarijazi, Iman Ahmadianfar, Miklas Scholz, Saad Sh. Sammen   +5 more
doaj   +2 more sources

Bearing Fault Feature Extraction Method Based on Adaptive Time-Varying Filtering Empirical Mode Decomposition and Singular Value Decomposition Denoising

Machines
Aiming to address the difficulty in extracting the early weak fault features of bearings under complex operating conditions, a fault diagnosis method is proposed based on the adaptive fusion of time-varying filtering empirical mode decomposition (TVF-EMD)
Xuezhuang E, Wenbo Wang, Hao Yuan
doaj   +2 more sources