Intelligent diagnosis method for rotating machinery using dictionary learning and singular value decomposition
T Han, D Jiang, X Zhang, Y Sun - Sensors, 2017 - mdpi.com
Rotating machinery is widely used in industrial applications. With the trend towards more
precise and more critical operating conditions, mechanical failures may easily occur …
precise and more critical operating conditions, mechanical failures may easily occur …
A new local-global deep neural network and its application in rotating machinery fault diagnosis
X Zhao, M Jia - Neurocomputing, 2019 - Elsevier
Currently, it is a great challenge to effectively acquire more widespread equipment health
information for guaranteeing safe production and timely fault maintenance in the process of …
information for guaranteeing safe production and timely fault maintenance in the process of …
Multi-feature fusion for fault diagnosis of rotating machinery based on convolutional neural network
S Liu, Z Ji, Y Wang, Z Zhang, Z Xu, C Kan… - Computer Communications, 2021 - Elsevier
The fast and efficient fault diagnosis is the key to guarantee uninterrupted working of
facilities, which is more frugal and trustworthy than scheduled upkeep. At present, data …
facilities, which is more frugal and trustworthy than scheduled upkeep. At present, data …
A novel convolutional neural network for low-speed structural fault diagnosis under different operating condition and its understanding via visualization
H Tang, Z Liao, P Chen, D Zuo… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
A novel method of intelligent diagnosis is proposed for structural faults in low-speed rotating
machinery. It uses a hybrid scheme to automatically identify health states in a complex …
machinery. It uses a hybrid scheme to automatically identify health states in a complex …
Compound fault diagnosis of rotating machinery based on OVMD and a 1.5-dimension envelope spectrum
X Yan, M Jia, L Xiang - Measurement Science and Technology, 2016 - iopscience.iop.org
Owing to the character of diversity and complexity, the compound fault diagnosis of rotating
machinery under non-stationary operation has turned into a challenging task. In this paper, a …
machinery under non-stationary operation has turned into a challenging task. In this paper, a …
Multiple-signal defect identification of hydraulic pump using an adaptive normalized model and S transform
Y Zhu, S Tang, S Yuan - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Axial piston pump plays a pivotal role in a hydraulic transmission system since it can supply
the core power source. The complexity of structure and the invisibility of failure feature bring …
the core power source. The complexity of structure and the invisibility of failure feature bring …
Coupled neurons with multi-objective optimization benefit incipient fault identification of machinery
Organisms can sense subtle changes in the environment around them such as temperature,
vibration and magnetic field. That is because biological neural network interconnected …
vibration and magnetic field. That is because biological neural network interconnected …
An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis
J Liu, Y Hu, Y Wang, B Wu, J Fan… - … Science and Technology, 2018 - iopscience.iop.org
The diagnosis of complicated fault severity problems in rotating machinery systems is an
important issue that affects the productivity and quality of manufacturing processes and …
important issue that affects the productivity and quality of manufacturing processes and …
Wavelet leaders multifractal features based fault diagnosis of rotating mechanism
W Du, J Tao, Y Li, C Liu - Mechanical Systems and Signal Processing, 2014 - Elsevier
A novel method based on wavelet leaders multifractal features for rolling element bearing
fault diagnosis is proposed. The multifractal features, combined with scaling exponents …
fault diagnosis is proposed. The multifractal features, combined with scaling exponents …
Rotating machine fault detection based on HOS and artificial neural networks
CC Wang, GP James Too - Journal of intelligent manufacturing, 2002 - Springer
In order to identify the faults of rotating machinery, classification process can be divided into
two stages: one is the signal preprocessing and the feature extraction; the other is the …
two stages: one is the signal preprocessing and the feature extraction; the other is the …