A review on vibration-based condition monitoring of rotating machinery
Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …
functioning states are related to specific patterns that can be extracted from vibration signals …
Role of artificial intelligence in rotor fault diagnosis: A comprehensive review
Artificial intelligence (AI)-based rotor fault diagnosis (RFD) poses a variety of challenges to
the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults …
the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults …
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 …
faults in time can avoid affecting the operation of the entire equipment. The data-driven fault …
Hybrid multimodal fusion with deep learning for rolling bearing fault diagnosis
C Che, H Wang, X Ni, R Lin - Measurement, 2021 - Elsevier
For vibration signal of rolling bearing with long time series obtained from multiple sampling
points, hybrid multimodal fusion with deep learning is proposed for fault diagnosis. Feature …
points, hybrid multimodal fusion with deep learning is proposed for fault diagnosis. Feature …
Advancements in condition monitoring and fault diagnosis of rotating machinery: A comprehensive review of image-based intelligent techniques for induction motors
Recently, condition monitoring (CM) and fault detection and diagnosis (FDD) techniques for
rotating machinery (RM) have witnessed substantial advancements in recent decades …
rotating machinery (RM) have witnessed substantial advancements in recent decades …
Adaptive fault diagnosis method for rotating machinery with unknown faults under multiple working conditions
Y Ge, F Zhang, Y Ren - Journal of Manufacturing Systems, 2022 - Elsevier
Fault diagnosis is an important part of the health management of many pieces of equipment.
It is an effective means to reduce equipment failure rate and shutdown loss. In engineering …
It is an effective means to reduce equipment failure rate and shutdown loss. In engineering …
A convolutional neural network for electrical fault recognition in active magnetic bearing systems
Active magnetic bearings are complex mechatronic systems that consist of mechanical,
electrical, and software parts, unlike classical rolling bearings. Given the complexity of this …
electrical, and software parts, unlike classical rolling bearings. Given the complexity of this …
Multi-branch convolutional neural network with generalized shaft orbit for fault diagnosis of active magnetic bearing-rotor system
Fault diagnosis based on vibration signals in active magnetic bearing-rotor systems is an
important research topic. However, it is difficult to obtain discriminative features to represent …
important research topic. However, it is difficult to obtain discriminative features to represent …
Vibration image representations for fault diagnosis of rotating machines: a review
Rotating machine vibration signals typically represent a large collection of responses from
various sources in a machine, along with some background noise. This makes it challenging …
various sources in a machine, along with some background noise. This makes it challenging …
Fault diagnosis of rotating machinery equipped with multiple sensors using space-time fragments
The vibration signals captured by multiple sensors can be fused and provide rich information
to distinguish faults of rotating machinery. However, previous studies mostly regard multiple …
to distinguish faults of rotating machinery. However, previous studies mostly regard multiple …