Frequency-enhanced network with self-supervised learning for anomaly detection of hydraulic piston pumps DOI
Minseok Choi,

C. C. Lee,

Se Chang Park

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127662 - 127662

Published: April 1, 2025

Language: Английский

Fault diagnosis of hydro-turbine via the incorporation of bayesian algorithm optimized CNN-LSTM neural network DOI

Fang Dao,

Yun Zeng, Jing Qian

et al.

Energy, Journal Year: 2024, Volume and Issue: 290, P. 130326 - 130326

Published: Jan. 10, 2024

Language: Английский

Citations

95
Model-Assisted Multi-source Fusion Hypergraph Convolutional Neural Networks for intelligent few-shot fault diagnosis to Electro-Hydrostatic Actuator DOI
Xiaoli Zhao, Xingjun Zhu, Jiahui Liu

et al.

Information Fusion, Journal Year: 2023, Volume and Issue: 104, P. 102186 - 102186

Published: Dec. 11, 2023

Language: Английский

Citations

46
Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery DOI
Shengnan Tang, Jingtao Ma,

Zhengqi Yan

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 134, P. 108678 - 108678

Published: June 3, 2024

Language: Английский

Citations

32
A light deep adaptive framework toward fault diagnosis of a hydraulic piston pump DOI
Shengnan Tang, Boo Cheong Khoo, Yong Zhu

et al.

Applied Acoustics, Journal Year: 2024, Volume and Issue: 217, P. 109807 - 109807

Published: Jan. 4, 2024

Language: Английский

Citations

28
High imbalance fault diagnosis of aviation hydraulic pump based on data augmentation via local wavelet similarity fusion DOI
Song Fu, Lin Lin, Yue Wang

et al.

Mechanical Systems and Signal Processing, Journal Year: 2024, Volume and Issue: 209, P. 111115 - 111115

Published: Jan. 9, 2024

Language: Английский

Citations

22
Atomization process of GH4099 superalloy powder prepared by dual-gas nozzle DOI
Bo Chen, Zheyuan Zhang,

Wenying Li

et al.

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(2)

Published: Feb. 1, 2025

GH4099 is a typical age-hardened nickel-based superalloy with excellent overall performance, widely used in aerospace and other fields. In this study, novel tight-coupled dual-gas nozzle designed, two-phase coupling breakup model for the atomization process established based on volume of fluid flow model. The behavior melt under high-speed gas investigated depth. generation droplets analyzed, nozzle, enters chamber first impacted by intermediate airflow to generate initial droplets, move toward outer air channel action continue break into smaller channel. Powder particles are sampled at exit, particle characteristics generated analyzed detail. final size distribution obtained, influence pressure injection angle explored. results show that, within studied parameter range, as increases, powder increases then decreases. As decreases, also so small favorable reduction. When P2 = 4.5 MPa, α 25°, has narrowest distribution, smaller, median diameter D50 29.1 μm. findings study provide important references structure design optimization high-temperature alloys.

Language: Английский

Citations

4
Semi-supervised fault diagnosis of gearbox based on feature pre-extraction mechanism and improved generative adversarial networks under limited labeled samples and noise environment DOI
Lijie Zhang, Bin Wang, Pengfei Liang

et al.

Advanced Engineering Informatics, Journal Year: 2023, Volume and Issue: 58, P. 102211 - 102211

Published: Oct. 1, 2023

Language: Английский

Citations

31
Intelligent framework for degradation monitoring, defect identification and estimation of remaining useful life (RUL) of bearing DOI
Anil Kumar,

Chander Parkash,

Hesheng Tang

et al.

Advanced Engineering Informatics, Journal Year: 2023, Volume and Issue: 58, P. 102206 - 102206

Published: Oct. 1, 2023

Language: Английский

Citations

30
Estimation of soil moisture in drip-irrigated citrus orchards using multi-modal UAV remote sensing DOI Creative Commons

Zongjun Wu,

Ningbo Cui, Wenjiang Zhang

et al.

Agricultural Water Management, Journal Year: 2024, Volume and Issue: 302, P. 108972 - 108972

Published: July 30, 2024

Accurate and timely prediction of soil moisture in orchards is crucial for making informed irrigation decisions at a regional scale. Conventional methods monitoring are often limited by high cost disruption structure, etc. However, unmanned aerial vehicle (UAV) remote sensing, with spatial temporal resolutions, offers an effective alternative moisture. In this study, multi-modal UAV sensing data, including RGB, thermal infrared (TIR), multi-spectral (Mul) were acquired citrus orchards. The correlations between different sensor data analyzed to construct seven input combinations. Convolutional neural network (CNN), long short-term memory (LSTM) models new hybrid model (CNN-LSTM), employed predict depths 5 cm, 10 20 cm 40 cm. Additionally, the impact standalone sensor, texture features multi-sensor fusion on accuracy was explored. results indicated that RGB + Mul TIR achieved highest accuracy, followed those Mul, coefficient determination (R2) ranging 0.80–0.88, 0.64–0.84, 0.60–0.81, root mean square error (RMSE) 2.46–2.99 m3·m−3, 2.86–3.89 m3·m−3 3.15–4.25 respectively. Among single inputs, has 0.54–0.72, 0.36–0.52 0.14–0.26, 3.72–4.58 %, 3.81–5.04 % 4.27–6.21 CNN-LSTM exhibited CNN LSTM models, 0.20–0.88, 0.16–0.83, 0.14–0.81, 2.46–5.01 2.68–5.35 2.81–6.21 depth average 0.63, 0.62, 0.59, 0.55, 3.70 3.79 3.85 4.21 Therefore, recommended orchard. It provides method support precision decision-making.

Language: Английский

Citations

11
Global wavelet-integrated residual frequency attention regularized network for hypersonic flight vehicle fault diagnosis with imbalanced data DOI
Yutong Dong, Hongkai Jiang, Yunpeng Liu

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 132, P. 107968 - 107968

Published: Feb. 6, 2024

Language: Английский

Citations

10