Rotating machinery fault-induced vibration signal modulation effects: A review with mechanisms, extraction methods and applications for diagnosis
Rotating machinery faults can induce characteristic modulation effects in a vibration signal,
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
A comprehensive survey of sparse regularization: Fundamental, state-of-the-art methodologies and applications on fault diagnosis
Q Li - Expert Systems with Applications, 2023 - Elsevier
Sparse regularization has been attracting much attention in industrial applications over the
past few decades. By exploiting the latent data structure in low-dimensional subspaces, a …
past few decades. By exploiting the latent data structure in low-dimensional subspaces, a …
Wavelet transform for rotary machine fault diagnosis: 10 years revisited
As a multi-resolution analysis method rooted rigorously in mathematics, wavelet transform
(WT) has shown its great potential in rotary machine fault diagnosis, characterized by …
(WT) has shown its great potential in rotary machine fault diagnosis, characterized by …
Compound fault diagnosis using optimized MCKD and sparse representation for rolling bearings
W Deng, Z Li, X Li, H Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The effective separation of fault characteristic components is the core of compound fault
diagnosis of rolling bearings. The intelligent optimization algorithm has better global …
diagnosis of rolling bearings. The intelligent optimization algorithm has better global …
Multi-scale deep intra-class transfer learning for bearing fault diagnosis
The tremendous success of deep learning in machine fault diagnosis is dependent on the
hypothesis that training and test datasets are subordinated to the same distribution. This …
hypothesis that training and test datasets are subordinated to the same distribution. This …
[PDF][PDF] 信号分解及其在机械故障诊断中的应用研究综述
陈是扦， 彭志科， 周鹏 - 机械工程学报, 2020 - qikan.cmes.org
重大装备制造业是国民经济的支柱, 也是关系到国家安全的战略性产业, 而重大机械装备的运行
安全一直是备受关注的焦点. 机械设备由于工作环境恶劣, 工况复杂, 其关键部件容易受损 …
安全一直是备受关注的焦点. 机械设备由于工作环境恶劣, 工况复杂, 其关键部件容易受损 …
Rolling bearing fault diagnosis based on SSA optimized self-adaptive DBN
S Gao, L Xu, Y Zhang, Z Pei - ISA transactions, 2022 - Elsevier
Due to the structure of rolling bearings and the complexity of the operating environment,
collected vibration signals tend to show strong non-stationary and time-varying …
collected vibration signals tend to show strong non-stationary and time-varying …
The optimized deep belief networks with improved logistic sigmoid units and their application in fault diagnosis for planetary gearboxes of wind turbines
Y Qin, X Wang, J Zou - IEEE Transactions on Industrial …, 2018 - ieeexplore.ieee.org
Efficient and accurate planetary gearbox fault diagnosis is the key to enhance the reliability
and security of wind turbines. Therefore, an intelligent and integrated approach based on …
and security of wind turbines. Therefore, an intelligent and integrated approach based on …
Multitask convolutional neural network with information fusion for bearing fault diagnosis and localization
Accurate fault information is critical for optimal scheduling of production activities, improving
system reliability, and reducing operation and maintenance costs. In recent years, many fault …
system reliability, and reducing operation and maintenance costs. In recent years, many fault …
Light neural network with fewer parameters based on CNN for fault diagnosis of rotating machinery
T Jin, C Yan, C Chen, Z Yang, H Tian, S Wang - Measurement, 2021 - Elsevier
Many recent studies on deep learning models have focused on increasing accuracy for
mechanical fault data sets, while disregarding the influences of model complexity on …
mechanical fault data sets, while disregarding the influences of model complexity on …