Deep fault recognizer: An integrated model to denoise and extract features for fault diagnosis in rotating machinery
Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an
accurate and timely diagnosis method is necessary. With the breakthrough in deep learning …
accurate and timely diagnosis method is necessary. With the breakthrough in deep learning …
Automatic feature extraction and construction using genetic programming for rotating machinery fault diagnosis
Feature extraction is an essential process in the intelligent fault diagnosis of rotating
machinery. Although existing feature extraction methods can obtain representative features …
machinery. Although existing feature extraction methods can obtain representative features …
Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation
Intelligent machinery fault diagnosis system has been receiving increasing attention recently
due to the potential large benefits of maintenance cost reduction, enhanced operation safety …
due to the potential large benefits of maintenance cost reduction, enhanced operation safety …
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 …
Fault diagnosis of rolling bearing using marine predators algorithm-based support vector machine and topology learning and out-of-sample embedding
X Chen, X Qi, Z Wang, C Cui, B Wu, Y Yang - Measurement, 2021 - Elsevier
The long-term safe operation of rotating machinery is closely related to the stability of rolling
bearings. This paper proposes a rolling bearing fault diagnosis method based on refined …
bearings. This paper proposes a rolling bearing fault diagnosis method based on refined …
Sparse representation learning for fault feature extraction and diagnosis of rotating machinery
S Ma, Q Han, F Chu - Expert Systems with Applications, 2023 - Elsevier
Early fault feature extraction and fault diagnosis are of great importance for predictive
maintenance of rotating machinery. To accurately extract early fault features from original …
maintenance of rotating machinery. To accurately extract early fault features from original …
Application of spectral kurtosis and improved extreme learning machine for bearing fault classification
The condition monitoring of rotating machinery systems based on effective and intelligent
fault diagnosis has been widely accepted. Traditional signal processing (SP) methods are …
fault diagnosis has been widely accepted. Traditional signal processing (SP) methods are …
Feature trend extraction and adaptive density peaks search for intelligent fault diagnosis of machines
Traditional machine fault diagnosis techniques are labor-intensive and hard for nonexperts
to use. In this paper, a novel three-stage intelligent fault diagnosis approach is proposed for …
to use. In this paper, a novel three-stage intelligent fault diagnosis approach is proposed for …
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 …
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 …