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Fault diagnosis of wind turbine bearings based on CNN and SSA–ELM
X Liu, Z Zhang, F Meng, Y Zhang - Journal of Vibration Engineering & …, 2023 - Springer
Purpose As a critical component of the wind turbine drive train, the bearings are easy to fail
under the complex environment of variable working conditions and loads in long-term …
under the complex environment of variable working conditions and loads in long-term …
A neural network compression method based on knowledge-distillation and parameter quantization for the bearing fault diagnosis
Condition monitoring and fault diagnosis have been critical for the optimal scheduling of
machines, improving the system reliability and the reducing maintenance cost. In recent …
machines, improving the system reliability and the reducing maintenance cost. In recent …
Rolling bearing fault diagnosis based on multiple wavelet coefficient dimensionality reduction and improved residual network
X Zheng, P Yang, K Yan, Y He, Q Yu, M Li - Engineering Applications of …, 2024 - Elsevier
In response to limitations in traditional intelligent fault diagnosis methods, such as accuracy,
robustness, generality, and susceptibility to noise, this article proposes Multiple Wavelet …
robustness, generality, and susceptibility to noise, this article proposes Multiple Wavelet …
Condition monitoring and fault diagnosis of rotating machinery towards intelligent manufacturing: Review and prospect
H Zhang, W Che, Y Cao, Z Guan, C Zhu - Iranian Journal of Science and …, 2024 - Springer
Rotating machinery is advancing in the direction of high efficiency, high rotary speed,
enhanced automation, and widespread application with the quickening growth of intelligent …
enhanced automation, and widespread application with the quickening growth of intelligent …
Spectral proper orthogonal decomposition and machine learning algorithms for bearing fault diagnosis
Vibration analysis has been extensively exploited for bearing fault diagnosis. However,
signal acquisition is quite expensive since external hardware is required. Moreover, for …
signal acquisition is quite expensive since external hardware is required. Moreover, for …
Real-time damage analysis of 2D C/SiC composite based on spectral characters of acoustic emission signals using pattern recognition
X Zeng, H Shao, R Pan, B Wang, Q Deng, C Zhang… - Acta Mechanica …, 2022 - Springer
In this study, unsupervised and supervised pattern recognition were implemented in
combination to achieve real-time health monitoring. Unsupervised recognition (k-means++) …
combination to achieve real-time health monitoring. Unsupervised recognition (k-means++) …
A deep convolutional neural network model with two-stream feature fusion and cross-load adaptive characteristics for fault diagnosis
W Pan, H Qu, Y Sun, M Wang - Measurement Science and …, 2023 - iopscience.iop.org
Research aimed at diagnosing rolling bearing faults is of great significance to the health
management of equipment. In order to solve the problem that rolling bearings are faced with …
management of equipment. In order to solve the problem that rolling bearings are faced with …
A multi fault classification in a rotor-bearing system using machine learning approach
Modern condition monitoring of rotating machinery became intelligent for enhanced
reliability, productivity, and safety. Signal processing has been collaboratively implemented …
reliability, productivity, and safety. Signal processing has been collaboratively implemented …
Bearing fault diagnosis based on artificial intelligence methods: machine learning and deep learning
This paper presents a comprehensive study on the application of Artificial Intelligence (AI)
methods, specifically machine learning and deep learning, for the diagnosis of bearing …
methods, specifically machine learning and deep learning, for the diagnosis of bearing …
A case study of wind turbine rotor over-speed fault diagnosis using combination of SCADA data, vibration analyses and field inspection
Reduction of wind turbines down times is paramount in wind energy develop-ment and cost
effectiveness. Such reductions require early fault detection and more importantly, a …
effectiveness. Such reductions require early fault detection and more importantly, a …