Improved leak localization in water distribution systems using SGTCC: Comparative analysis with EMD-HT and EEMD-HT under transient conditions DOI
Mohd Fairusham Ghazali,

Nor Azinee Said,

Muhammad Hanafi Yusop

и другие.

Measurement, Год журнала: 2025, Номер unknown, С. 118072 - 118072

Опубликована: Июнь 1, 2025

Язык: Английский

A Wavelet Transform-Based Transfer Learning Approach for Enhanced Shaft Misalignment Diagnosis in Rotating Machinery DOI Open Access
Houssem Habbouche, Tarak Benkedjouh, Yassine Amirat

и другие.

Electronics, Год журнала: 2025, Номер 14(2), С. 341 - 341

Опубликована: Янв. 17, 2025

Rotating machines are vital for ensuring reliability, safety, and operational availability across various industrial sectors. Among the faults that can affect these machines, shaft misalignment is particularly critical due to its impact on other components connected shaft, making it a key focus diagnostic systems. Misalignment lead significant energy losses, therefore, early detection crucial. Vibration analysis an effective method identifying at stage, enabling corrective actions before negatively impacts equipment efficiency consumption. To improve monitoring efficiency, essential system not only intelligent but also capable of operating in real-time. This study proposes methodology diagnosing by combining wavelet transform feature extraction transfer learning fault classification. The accuracy proposed soft real-time solution validated through comparison with time-frequency transformation techniques networks. includes experimental procedure simulating using laser measurement tool. Additionally, evaluates thermal vibration signature each type multi-sensor monitoring, highlighting effectiveness robustness approach. First, used obtain good representation signal domain. step allows features from signals. Then, network processes different layers identify their severity. combination provides decision-support tool faults, monitoring. tested two datasets: first public dataset, while second was created laboratory simulate alignment demonstrate effect this defect imaging. evaluation carried out criteria methodology. results highlight potential implementing faults.

Язык: Английский

Процитировано

4
Zinc Electrode Manufacturing Quality Control with machine learning: Using SMOTE & Image Augmentation to Prevent Overfitting DOI Creative Commons

Lola Azolay-Younes,

Anesu Nyabadza, Mercedes Vázquez

и другие.

Journal of Engineering Research, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2
Experimental Investigation of Conducted Electromagnetic Interference Differential-Mode Performance in Various Split-Phase Induction Motors Designs DOI Creative Commons
Houcine Miloudi, Mohamed Miloudi, Sid Ahmed El Mehdi Ardjoun

и другие.

Results in Engineering, Год журнала: 2025, Номер 25, С. 103963 - 103963

Опубликована: Янв. 5, 2025

Язык: Английский

Процитировано

1
Signal Processing Approaches for Power Quality Disturbance Classification: A Comprehensive Review DOI Creative Commons

Madgula Satyanrayana,

Venkataramana Veeramsetty,

Durgam Rajababu

и другие.

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104569 - 104569

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1
Power Quality Disturbance Classification Method Based on Unscented Kalman Filter and Kernel Extreme Learning Machine DOI Creative Commons

Yanjun Jiao,

Haoyu Cao,

Linke Wang

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(5), С. 2721 - 2721

Опубликована: Март 4, 2025

The power quality index is an important in the industry. Power disturbances (PQDs) have a great impact on grid. It to identify type of PQDs accurately. However, it difficult analyze large number PQDs, especially more complex systems. Considering limitations traditional time–frequency domain method and complexity optimization algorithm extracting features, novel proposed classify this paper, which based unscented Kalman filter (UKF) kernel extreme learning machine (KELM). UKF used detect process original disturbances, anti-noise detection performance analyzed by tracking amplitude change voltage swell under different signal–noise ratios (SNRs). amplitudes fundamental wave, third harmonic, fifth seventh oscillatory wave are tracked real time, their minimum peak indexes taken as optimal feature vector set. set classified KELM. has also been evaluated with simulated experimental results.

Язык: Английский

Процитировано

0
Pressure characterization study in the jet influence zone of riser based on HHT analysis DOI Creative Commons
Z. Zheng,

J. Ma,

Zihan Yan

и другие.

Petroleum Science, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
A review of printing methods, materials, and artificial intelligence applications in sodium-ion battery manufacturing and management systems DOI Creative Commons
Anesu Nyabadza, A.H. Titus, Mayur A. Makhesana

и другие.

Chemical Engineering Journal Advances, Год журнала: 2025, Номер unknown, С. 100787 - 100787

Опубликована: Июнь 1, 2025

Язык: Английский

Процитировано

0
Improved leak localization in water distribution systems using SGTCC: Comparative analysis with EMD-HT and EEMD-HT under transient conditions DOI
Mohd Fairusham Ghazali,

Nor Azinee Said,

Muhammad Hanafi Yusop

и другие.

Measurement, Год журнала: 2025, Номер unknown, С. 118072 - 118072

Опубликована: Июнь 1, 2025

Язык: Английский

Процитировано

0