Multiple-signal defect identification of hydraulic pump using an adaptive normalized model and S transform

Y Zhu, S Tang, S Yuan - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Axial piston pump plays a pivotal role in a hydraulic transmission system since it can supply
the core power source. The complexity of structure and the invisibility of failure feature bring …

Detecting wind turbine anomalies using nonlinear dynamic parameters-assisted machine learning with normal samples

K Shao, Y He, Z Xing, B Du - Reliability Engineering & System Safety, 2023 - Elsevier
Anomaly detection is critical for the reliability and safety of wind turbine. Toward this
objective, this paper proposes an anomaly detection scheme for wind turbine using only …

[HTML][HTML] A deep convolutional neural network for vibration-based health-monitoring of rotating machinery

P Ong, YK Tan, KH Lai, CK Sia - Decision Analytics Journal, 2023 - Elsevier
The gearbox is a critical component in the mechanical system, requiring vigilant monitoring
to prevent adverse consequences on safety and quality due to malfunction. Therefore, early …

Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery

S Tang, J Ma, Z Yan, Y Zhu, BC Khoo - Engineering Applications of …, 2024 - Elsevier
Rotating machinery plays an essential part in many engineering fields. It needs prompt
solutions to the prognosis and health management to ensure the system reliability …

A novel hierarchical training architecture for Siamese Neural Network based fault diagnosis method under small sample

J Zhao, M Yuan, J Cui, J Huang, F Zhao, S Dong, Y Qu - Measurement, 2023 - Elsevier
Although current deep learning-based fault diagnosis methods have made great progress,
the accuracy of these models is usually attained based on many balanced training samples …

MIFDELN: A multi-sensor information fusion deep ensemble learning network for diagnosing bearing faults in noisy scenarios

M Ye, X Yan, D Jiang, L Xiang, N Chen - Knowledge-Based Systems, 2024 - Elsevier
Owing to the harsh operating environment of rolling bearings, acquired vibration signals
contain strong noise interference, which makes it challenging for conventional methods to …

Intelligent fault diagnosis of rolling mills based on dual attention-guided deep learning method under imbalanced data conditions

P Shi, H Gao, Y Yu, X Xu, D Han - Measurement, 2022 - Elsevier
As an important link in the steel production chain, the health of the rolling mill directly affects
the steel production. Therefore, the study of rolling mill fault diagnosis methods is of great …

Robust fault diagnosis of quayside container crane gearbox based on 2D image representation in frequency domain and CNN

J Zhang, Q Zhang, X Qin, Y Sun - Structural Health …, 2024 - journals.sagepub.com
To accurately diagnose the quayside container crane (QCC) gearbox faults, this article
proposes a method that combines the frequency-domain Markov transformation field …

Weighted average selective ensemble strategy of deep convolutional models based on grey wolf optimizer and its application in rotating machinery fault diagnosis

H Zhou, P Yan, Q Huang, D Wu, J Pei… - Expert Systems with …, 2023 - Elsevier
To improve the fault diagnosis performance of rotating machinery under harsh conditions, a
weighted average selective ensemble strategy of deep convolutional models based on the …

Fault diagnosis of power-shift system in continuously variable transmission tractors based on improved Echo State Network

G Wang, L Xue, Y Zhu, Y Zhao, H Jiang… - Engineering Applications of …, 2023 - Elsevier
For better reliability of tractors with continuously variable transmission, reported here is fault
diagnosis of their power-shift systems. First, four hydraulic system faults are analyzed, ie …