[HTML][HTML] Recent progress of machine learning in flow modeling and active flow control
In terms of multiple temporal and spatial scales, massive data from experiments, flow field
measurements, and high-fidelity numerical simulations have greatly promoted the rapid …
measurements, and high-fidelity numerical simulations have greatly promoted the rapid …
Fault diagnosis of a rotor-bearing system under variable rotating speeds using two-stage parameter transfer and infrared thermal images
Current fault diagnosis methods for rotor-bearing systems are mostly based on analyzing the
vibration signals collected at steady rotating speeds. In those methods, the data collected …
vibration signals collected at steady rotating speeds. In those methods, the data collected …
Spindle thermal error prediction approach based on thermal infrared images: A deep learning method
W Chengyang, X Sitong, X Wansheng - Journal of Manufacturing Systems, 2021 - Elsevier
It is essential to precisely model the spindle thermal error due to its dramatic influence on the
machining accuracy. In this paper, the deep learning convolutional neural network (CNN) is …
machining accuracy. In this paper, the deep learning convolutional neural network (CNN) is …
Rolling bearing fault severity recognition via data mining integrated with convolutional neural network
D Liu, L Cui, W Cheng, D Zhao, W Wen - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Rolling bearing vibration signals exhibit typically complex modulation characteristics, and
usually present nonstationary features. The defect of a rolling bearing is mainly manifested …
usually present nonstationary features. The defect of a rolling bearing is mainly manifested …
A unified framework incorporating predictive generative denoising autoencoder and deep Coral network for rolling bearing fault diagnosis with unbalanced data
X Li, H Jiang, S Liu, J Zhang, J Xu - Measurement, 2021 - Elsevier
In practical engineering, data imbalance is an urgent problem to be solved for rolling
bearing fault diagnosis. This paper proposes a unified framework incorporating predictive …
bearing fault diagnosis. This paper proposes a unified framework incorporating predictive …
Machine Learning‐Based Fault Diagnosis of Self‐Aligning Bearings for Rotating Machinery Using Infrared Thermography
A Mehta, D Goyal, A Choudhary… - Mathematical …, 2021 - Wiley Online Library
Bearings are considered as indispensable and critical components of mechanical
equipment, which support the basic forces and dynamic loads. Across different condition …
equipment, which support the basic forces and dynamic loads. Across different condition …
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 …
Transfer learning based fault diagnosis of automobile dry clutch system
G Chakrapani, V Sugumaran - Engineering Applications of Artificial …, 2023 - Elsevier
Dry friction clutches are prone to fault occurrences due to their continuous exposure to
thermal loading and high abrasive rate during power transmission. Fault occurrences in …
thermal loading and high abrasive rate during power transmission. Fault occurrences in …
Aero-engine high speed bearing fault diagnosis for data imbalance: A sample enhanced diagnostic method based on pre-training WGAN-GP
J Chen, Z Yan, C Lin, B Yao, H Ge - Measurement, 2023 - Elsevier
Rolling bearing is the key supporting component of aero-engines, of which fault diagnosis is
very important to ensure its reliable operation and continuous airworthiness. However, the …
very important to ensure its reliable operation and continuous airworthiness. However, the …
Multi-channel sensor fusion for real-time bearing fault diagnosis by frequency-domain multilinear principal component analysis
A Al Mamun, MM Bappy, AS Mudiyanselage… - … International Journal of …, 2023 - Springer
Real-time health condition monitoring of bearings plays a significant role in the functionality
of the rotary machinery. Multi-channel sensor fusion can be more robust for identifying …
of the rotary machinery. Multi-channel sensor fusion can be more robust for identifying …