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 …
[HTML][HTML] Deep learning techniques in intelligent fault diagnosis and prognosis for industrial systems: A review
S Qiu, X Cui, Z Ping, 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 …
Highly efficient fault diagnosis of rotating machinery under time-varying speeds using LSISMM and small infrared thermal images
The existing fault diagnosis methods of rotating machinery constructed with both shallow
learning and deep learning models are mostly based on vibration analysis under steady …
learning and deep learning models are mostly based on vibration analysis under steady …
Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images
The bearings are the crucial components of rotating machines in an industrial firm.
Unplanned failure of these components not only increases the downtime, but also leads to …
Unplanned failure of these components not only increases the downtime, but also leads to …
Towards Zero Defect Manufacturing paradigm: A review of the state-of-the-art methods and open challenges
Abstract Nowadays, Internet-of-Things (IoT), big data, and cloud computing technologies
allow increasing the throughput and quality of manufacturing systems, bringing to the rise of …
allow increasing the throughput and quality of manufacturing systems, bringing to the rise of …
[HTML][HTML] Fusion domain-adaptation CNN driven by images and vibration signals for fault diagnosis of gearbox cross-working conditions
G Mao, Z Zhang, B Qiao, Y Li - Entropy, 2022 - mdpi.com
The vibration signal of gearboxes contains abundant fault information, which can be used for
condition monitoring. However, vibration signal is ineffective for some non-structural failures …
condition monitoring. However, vibration signal is ineffective for some non-structural failures …
Predictive monitoring of incipient faults in rotating machinery: a systematic review from data acquisition to artificial intelligence
Predictive maintenance is one of the major tasks in today's modern industries. All rotating
machines consisting of rotating elements such as gears, bearings etc are considered as the …
machines consisting of rotating elements such as gears, bearings etc are considered as the …
Multi-modal data cross-domain fusion network for gearbox fault diagnosis under variable operating conditions
Gearbox fault diagnosis is a critical aspect of machinery maintenance and reliability, as it
ensures the safe and efficient operation of various industrial systems. The cross-domain fault …
ensures the safe and efficient operation of various industrial systems. The cross-domain fault …
A transformer model with enhanced feature learning and its application in rotating machinery diagnosis
Deep learning has become the prevailing trend of intelligent fault diagnosis for rotating
machines. Compared to early-stage methods, deep learning methods use automatic feature …
machines. Compared to early-stage methods, deep learning methods use automatic feature …
[HTML][HTML] Research on gearbox temperature field image fault diagnosis method based on transfer learning and deep belief network
X Lu, P Li - Scientific Reports, 2023 - nature.com
This paper applies thermal imaging technology to gearbox fault diagnosis. The temperature
field calculation model is established to obtain the temperature field images of various faults …
field calculation model is established to obtain the temperature field images of various faults …