Gearbox fault diagnosis based on Multi-Scale deep residual learning and stacked LSTM model
Fault diagnosis methods based on signal analysis techniques are widely used to diagnose
faults in gear and bearing. This paper introduces a fault diagnosis model that includes a …
faults in gear and bearing. This paper introduces a fault diagnosis model that includes a …
Augmented data driven self-attention deep learning method for imbalanced fault diagnosis of the HVAC chiller
C Shen, H Zhang, S Meng, C Li - Engineering Applications of Artificial …, 2023 - Elsevier
The chiller fault diagnosis is of great significance to maintain the normal operation of the
HVAC system and indoor comfort. Due to the difficulty in collecting the chiller's fault data, we …
HVAC system and indoor comfort. Due to the difficulty in collecting the chiller's fault data, we …
A bearing fault diagnosis model based on CNN with wide convolution kernels
X Song, Y Cong, Y Song, Y Chen, P Liang - Journal of Ambient …, 2022 - Springer
Intelligent fault diagnosis of bearings is an essential issue in the field of health management
and the prediction of rotating machinery systems. The traditional bearing intelligent …
and the prediction of rotating machinery systems. The traditional bearing intelligent …
Intelligent fault diagnosis of rolling bearings under varying operating conditions based on domain-adversarial neural network and attention mechanism
H Wu, J Li, Q Zhang, J Tao, Z Meng - ISA transactions, 2022 - Elsevier
As a domain adaptation method, the domain-adversarial neural network (DANN) can utilize
the adversarial learning of the feature extractor and domain discriminator to extract the …
the adversarial learning of the feature extractor and domain discriminator to extract the …
Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions
Intelligent fault diagnosis based on domain adaptation has recently been extensively
researched to promote reliability of safety-critical assets under different working conditions …
researched to promote reliability of safety-critical assets under different working conditions …
Support vector machines based non-contact fault diagnosis system for bearings
Bearing defects have been accepted as one of the major causes of failure in rotating
machinery. It is important to identify and diagnose the failure behavior of bearings for the …
machinery. It is important to identify and diagnose the failure behavior of bearings for the …
Towards Zero Defect Manufacturing paradigm: A review of the state-of-the-art methods and open challenges
Abstract Nowadays, Internet-of-Things (IoT), big data, and cloud computing technologies
allow increasing the throughput and quality of manufacturing systems, bringing to the rise of …
allow increasing the throughput and quality of manufacturing systems, bringing to the rise of …
Bearing fault detection with vibration and acoustic signals: Comparison among different machine leaning classification methods
J Pacheco-Chérrez, JA Fortoul-Díaz… - Engineering Failure …, 2022 - Elsevier
Despite the recent advances in supervised ML-based methods for fault bearing detection is
that most published work uses only vibration data for damage detection. However …
that most published work uses only vibration data for damage detection. However …
Extreme learning Machine-based classifier for fault diagnosis of rotating Machinery using a residual network and continuous wavelet transform
H Wei, Q Zhang, M Shang, Y Gu - Measurement, 2021 - Elsevier
Effective fault diagnosis of rotating machinery is essential for the predictive maintenance of
modern industries. In this study, a novel framework that combines a residual network …
modern industries. In this study, a novel framework that combines a residual network …
Quality analysis in metal additive manufacturing with deep learning
As a promising modern technology, additive manufacturing (AM) has been receiving
increasing research and industrial attention in the recent years. With its rapid development …
increasing research and industrial attention in the recent years. With its rapid development …