Ventilation diagnosis of angle grinder using thermal imaging
A Glowacz - Sensors, 2021 - mdpi.com
The paper presents an analysis and classification method to evaluate the working condition
of angle grinders by means of infrared (IR) thermography and IR image processing. An …
of angle grinders by means of infrared (IR) thermography and IR image processing. An …
Full attention Wasserstein GAN with gradient normalization for fault diagnosis under imbalanced data
J Fan, X Yuan, Z Miao, Z Sun, X Mei… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The fault diagnosis of rolling bearings is vital for the safe and reliable operation of
mechanical equipment. However, the imbalanced data collected from the real engineering …
mechanical equipment. However, the imbalanced data collected from the real engineering …
Dual-attention generative adversarial networks for fault diagnosis under the class-imbalanced conditions
Deep learning has been widely applied to intelligent fault diagnosis with balanced training
set. However, certain available fault data are extremely limited, resulting in an imbalanced …
set. However, certain available fault data are extremely limited, resulting in an imbalanced …
Detection of mechanical failures in industrial machines using overlap** acoustic anomalies: A systematic literature review
One of the most important strategies for preventative factory maintenance is anomaly
detection without the need for dedicated sensors for each industrial unit. The implementation …
detection without the need for dedicated sensors for each industrial unit. The implementation …
A review of gear fault diagnosis of planetary gearboxes using acoustic emissions
Despite the progress made in the last decades in the field of machine condition monitoring,
there are still cases where the current state of the art is not enough and new technologies …
there are still cases where the current state of the art is not enough and new technologies …
Acoustic emission for in situ process monitoring of selective laser melting additive manufacturing based on machine learning and improved variational modal …
H Wang, B Li, FZ Xuan - The International Journal of Advanced …, 2022 - Springer
Selective laser melting (SLM) additive manufacturing overcomes the geometric limits of
complex components produced with traditional subtractive methods, which has significant …
complex components produced with traditional subtractive methods, which has significant …
Untrained compound fault diagnosis for planetary gearbox based on adaptive learning VMD and DSSECNN
X Kong, L Meng, Y Su, T Xu, X Lan… - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Fault coupling and fault override are common phenomena when faults occur in different
parts of the planetary gearbox. Labeled compound fault samples are very rare or even …
parts of the planetary gearbox. Labeled compound fault samples are very rare or even …
An operating condition information-guided iterative variational mode decomposition method based on Mahalanobis distance criterion for surge characteristic …
As a significant high-speed rotating machinery being widely used in modern industry, the
centrifugal compressor is subject to a potentially damaging phenomenon called surge …
centrifugal compressor is subject to a potentially damaging phenomenon called surge …
Gear fault diagnosis based on variational modal decomposition and wide+ narrow visual field neural networks
In modern industrial production, rotating machinery plays an important role. The gears in this
machinery adjust the speed and transmission of torque. Therefore, when the gear fails, it is …
machinery adjust the speed and transmission of torque. Therefore, when the gear fails, it is …
Matching synchroextracting transform for mechanical fault diagnosis under variable-speed conditions
Time–frequency (TF) analysis (TFA) technique has been widely used to the analysis of
rotating machine vibration. However, vibration signal from practical sources contains …
rotating machine vibration. However, vibration signal from practical sources contains …