A systematic review of deep transfer learning for machinery fault diagnosis
With the popularization of the intelligent manufacturing, much attention has been paid in
such intelligent computing methods as deep learning ones for machinery fault diagnosis …
such intelligent computing methods as deep learning ones for machinery fault diagnosis …
Application of recurrent neural network to mechanical fault diagnosis: A review
J Zhu, Q Jiang, Y Shen, C Qian, F Xu, Q Zhu - Journal of Mechanical …, 2022 - Springer
With the development of intelligent manufacturing and automation, the precision and
complexity of mechanical equipment are increasing, which leads to a higher requirement for …
complexity of mechanical equipment are increasing, which leads to a higher requirement for …
Intelligent fault diagnosis of rotating machinery based on continuous wavelet transform-local binary convolutional neural network
This paper presents a data-driven intelligent fault diagnosis approach for rotating machinery
(RM) based on a novel continuous wavelet transform-local binary convolutional neural …
(RM) based on a novel continuous wavelet transform-local binary convolutional neural …
Multireceptive field graph convolutional networks for machine fault diagnosis
Deep learning (DL) based methods have swept the field of mechanical fault diagnosis,
because of the powerful ability of feature representation. However, many of existing DL …
because of the powerful ability of feature representation. However, many of existing DL …
Intelligent fault diagnosis of gearbox under variable working conditions with adaptive intraclass and interclass convolutional neural network
The industrial gearboxes usually work in harsh and variable conditions, which results in
partial failure of gears or bearings. Accordingly, the continuous irregular fluctuations of …
partial failure of gears or bearings. Accordingly, the continuous irregular fluctuations of …
Deep learning techniques in intelligent fault diagnosis and prognosis for industrial systems: a review
S Qiu, X Cui, Z **, N Shan, Z Li, X Bao, X Xu - Sensors, 2023 - mdpi.com
Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …
captured sensory data, and also predict their failures in advance, which can greatly help to …
A two-stage transfer adversarial network for intelligent fault diagnosis of rotating machinery with multiple new faults
Recently, deep transfer learning based intelligent fault diagnosis has been widely
investigated, and the tasks that source and target domains share the same fault categories …
investigated, and the tasks that source and target domains share the same fault categories …
Semisupervised graph convolution deep belief network for fault diagnosis of electormechanical system with limited labeled data
The labeled monitoring data collected from the electromechanical system is limited in the
real industries; traditional intelligent fault diagnosis methods cannot achieve satisfactory …
real industries; traditional intelligent fault diagnosis methods cannot achieve satisfactory …
Latest developments in gear defect diagnosis and prognosis: A review
Gears are an important component of industrial machinery and a breakdown of machinery
on account of the failure of gears could result in immense production loss. Timely monitoring …
on account of the failure of gears could result in immense production loss. Timely monitoring …
Bearing remaining useful life prediction using self-adaptive graph convolutional networks with self-attention mechanism
Bearings are commonly used to reduce friction between moving parts. Bearings may fail due
to lubrication failure, contamination, corrosion, and fatigue. To prevent bearing failures, it is …
to lubrication failure, contamination, corrosion, and fatigue. To prevent bearing failures, it is …