A comprehensive review of conventional and intelligence-based approaches for the fault diagnosis and condition monitoring of induction motors
This review paper looks briefly at conventional approaches and examines the intelligent
means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail …
means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail …
Novel joint transfer network for unsupervised bearing fault diagnosis from simulation domain to experimental domain
Unsupervised cross-domain fault diagnosis of bearings has practical significance; however,
the existing studies still face some problems. For example, transfer diagnosis scenarios are …
the existing studies still face some problems. For example, transfer diagnosis scenarios are …
Dual-threshold attention-guided GAN and limited infrared thermal images for rotating machinery fault diagnosis under speed fluctuation
End-to-end intelligent diagnosis of rotating machinery under speed fluctuation and limited
samples is challenging in industrial practice. The existing limited samples methods usually …
samples is challenging in industrial practice. The existing limited samples methods usually …
Intelligent diagnosis using continuous wavelet transform and gauss convolutional deep belief network
H Zhao, J Liu, H Chen, J Chen, Y Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Bearing fault diagnosis is of significance to ensure the safe and reliable operation of a
motor. Deep learning provides a powerful ability to extract the features of raw data …
motor. Deep learning provides a powerful ability to extract the features of raw data …
Deep order-wavelet convolutional variational autoencoder for fault identification of rolling bearing under fluctuating speed conditions
X Yan, D She, Y Xu - Expert Systems with Applications, 2023 - Elsevier
Because of the complex operating environment of high-end industrial machinery, rolling
bearing is generally operated at fluctuating working conditions such as variable speeds or …
bearing is generally operated at fluctuating working conditions such as variable speeds or …
Multi-input CNN based vibro-acoustic fusion for accurate fault diagnosis of induction motor
Induction motor (IM) is a highly efficient prime mover in industrial applications. To maintain
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
Thermographic fault diagnosis of shaft of BLDC motor
A Glowacz - Sensors, 2022 - mdpi.com
A technique of thermographic fault diagnosis of the shaft of a BLDC (Brushless Direct
Current Electric) motor is presented in this article. The technique works for the shivering of …
Current Electric) motor is presented in this article. The technique works for the shivering of …
Feature extraction using parameterized multisynchrosqueezing transform
X Li, H Zhao, L Yu, H Chen, W Deng… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Parametrized time-frequency analysis (PTFA) can effectively improve time-frequency energy
aggregation of non-stationary signal and immunity of cross term interference, but it exists the …
aggregation of non-stationary signal and immunity of cross term interference, but it exists the …
Deep branch attention network and extreme multi-scale entropy based single vibration signal-driven variable speed fault diagnosis scheme for rolling bearing
D Zhao, S Liu, H Du, L Wang, Z Miao - Advanced Engineering Informatics, 2023 - Elsevier
In view of the difficulty in measuring the speed signal and integrating the vibration and
speed information flexibly in actual variable speed bearing fault diagnosis, a single vibration …
speed information flexibly in actual variable speed bearing fault diagnosis, a single vibration …
Data-augmented wavelet capsule generative adversarial network for rolling bearing fault diagnosis
Y Liu, H Jiang, C Liu, W Yang, W Sun - Knowledge-Based Systems, 2022 - Elsevier
Rolling bearing fault diagnosis with limited imbalance data is significant and challenging. It
is a nice attempt to generate data for balancing datasets. In this paper, a wavelet capsule …
is a nice attempt to generate data for balancing datasets. In this paper, a wavelet capsule …