Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
Vibration measurement and monitoring are essential in a wide variety of applications.
Vibration measurements are critical for diagnosing industrial machinery malfunctions …
Vibration measurements are critical for diagnosing industrial machinery malfunctions …
A systematic review of data-driven approaches to fault diagnosis and early warning
As an important stage of life cycle management, machinery PHM (prognostics and health
management), an emerging subject in mechanical engineering, has seen a huge amount of …
management), an emerging subject in mechanical engineering, has seen a huge amount of …
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 …
Fabric defect detection in textile manufacturing: a survey of the state of the art
C Li, J Li, Y Li, L He, X Fu, J Chen - Security and …, 2021 - Wiley Online Library
Defects in the textile manufacturing process lead to a great waste of resources and further
affect the quality of textile products. Automated quality guarantee of textile fabric materials is …
affect the quality of textile products. Automated quality guarantee of textile fabric materials is …
Extreme learning Machine-based classifier for fault diagnosis of rotating Machinery using a residual network and continuous wavelet transform
H Wei, Q Zhang, M Shang, Y Gu - Measurement, 2021 - Elsevier
Effective fault diagnosis of rotating machinery is essential for the predictive maintenance of
modern industries. In this study, a novel framework that combines a residual network …
modern industries. In this study, a novel framework that combines a residual network …
Fault diagnosis of mechanical equipment in high energy consumption industries in China: A review
Y Sun, J Wang, X Wang - Mechanical Systems and Signal Processing, 2023 - Elsevier
Building materials machinery equipment play an important role in the production of cement,
brick and tile, glass and other building materials, which are high energy consumption …
brick and tile, glass and other building materials, which are high energy consumption …
Graph embedding deep broad learning system for data imbalance fault diagnosis of rotating machinery
The distribution of monitored data during the service life of machinery equipment is
imbalanced, especially there is more monitoring data for health conditions than for failure …
imbalanced, especially there is more monitoring data for health conditions than for failure …
Rotating machinery fault diagnosis through a transformer convolution network subjected to transfer learning
X Pei, X Zheng, J Wu - IEEE Transactions on Instrumentation …, 2021 - ieeexplore.ieee.org
Owing to complex operational and measurement conditions, the data available to realize the
effective training of deep models are often inadequate. Compared with traditional deep …
effective training of deep models are often inadequate. Compared with traditional deep …
Composite neuro-fuzzy system-guided cross-modal zero-sample diagnostic framework using multi-source heterogeneous non-contact sensing data
Zero-sample diagnostic methods have gained recognition in addressing the scarcity of
gearbox fault samples, thereby being regarded as a promising technique to guarantee …
gearbox fault samples, thereby being regarded as a promising technique to guarantee …
Coarse-to-fine: Progressive knowledge transfer-based multitask convolutional neural network for intelligent large-scale fault diagnosis
In modern industry, large-scale fault diagnosis of complex systems is emerging and
becoming increasingly important. Most deep learning-based methods perform well on small …
becoming increasingly important. Most deep learning-based methods perform well on small …