A review of the application of deep learning in intelligent fault diagnosis of rotating machinery

Z Zhu, Y Lei, G Qi, Y Chai, N Mazur, Y An, X Huang - Measurement, 2023 - Elsevier
With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …

Machine learning applications in power system fault diagnosis: Research advancements and perspectives

R Vaish, UD Dwivedi, S Tewari, SM Tripathi - Engineering Applications of …, 2021 - Elsevier
Newer generation sources and loads are posing new challenges to the conventional power
system protection schemes. Adaptive and intelligent protection methodology, based on …

Machine learning based bearing fault diagnosis using the case western reserve university data: A review

X Zhang, B Zhao, Y Lin - Ieee Access, 2021 - ieeexplore.ieee.org
The most important parts of rotating machinery are the rolling bearings. Finding bearing
faults in time can avoid affecting the operation of the entire equipment. The data-driven fault …

Adaptive decision-level fusion strategy for the fault diagnosis of axial piston pumps using multiple channels of vibration signals

Q Chao, HH Gao, JF Tao, YH Wang, J Zhou… - Science China …, 2022 - Springer
An axial piston pump is a key component that plays the role of the “heart” in hydraulic
systems. The pump failure will lead to an unexpected breakdown of the entire hydraulic …

A review of the application of artificial intelligence to nuclear reactors: Where we are and what's next

Q Huang, S Peng, J Deng, H Zeng, Z Zhang, Y Liu… - Heliyon, 2023 - cell.com
As a form of clean energy, nuclear energy has unique advantages compared to other energy
sources in the present era, where low-carbon policies are being widely advocated. The …

[HTML][HTML] Machine learning and deep learning for safety applications: Investigating the intellectual structure and the temporal evolution

L Leoni, A BahooToroody, MM Abaei, A Cantini… - Safety science, 2024 - Elsevier
Over the last decades, safety requirements have become of primary concern. In the context
of safety, several strategies could be pursued in many engineering fields. Moreover, many …

Synthetic data augmentation and deep learning for the fault diagnosis of rotating machines

A Khan, H Hwang, HS Kim - Mathematics, 2021 - mdpi.com
As failures in rotating machines can have serious implications, the timely detection and
diagnosis of faults in these machines is imperative for their smooth and safe operation …

Vibration-based fault diagnosis of broken impeller and mechanical seal failure in industrial mono-block centrifugal pumps using deep convolutional neural network

S Manikandan, K Duraivelu - Journal of Vibration Engineering & …, 2023 - Springer
Purpose Hydraulic pump failure results in a high rate of energy loss, performance
degradation, high vibration levels, and continuous noise emission. An unexpected pump …

An attention EfficientNet-based strategy for bearing fault diagnosis under strong noise

B Hu, J Tang, J Wu, J Qing - Sensors, 2022 - mdpi.com
With the continuous development of artificial intelligence, data-driven fault diagnosis
methods are gradually attracting widespread attention. However, in practical industrial …

[PDF][PDF] 一种面向旋转机械的基于Transformer 特征提取的域自适应故障诊断

黄星华, 吴天舒, 杨龙玉, 胡友强, 柴毅 - 仪器仪表学报, 2023 - emt.cnjournals.com
针对基于深度学习的旋转机械故障诊断方法在新工作条件下缺乏标注数据, 跨域诊断精度较低的
问题, 提出了一种基于Transformer 的域自适应故障诊断方法. 采用Transformer 的变体VOLO …