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Xiaojiao Gu, Yang Tian, Chi Li, Yonghe Wei and Dashuai Li
The fault diagnosis method proposed in this paper can be applied to the diagnosis of bearings in machine tool spindle systems.
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Zhenyu Yin, Feiqing Zhang, Guangyuan Xu, Guangjie Han and Yuanguo Bi
Confronting the challenge of identifying unknown fault types in rolling bearing fault diagnosis, this study introduces a multi-scale bearing fault diagnosis method based on transfer learning. Initially, a multi-scale feature extraction network, MBDCNet, ...
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Fengyun Xie, Gang Li, Hui Liu, Enguang Sun and Yang Wang
In the context of addressing the challenge posed by limited fault samples in agricultural machinery rolling bearings, especially when early fault characteristics are subtle, this study introduces a novel approach. The proposed multi-domain fault diagnosi...
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Ruosen Qi, Jie Zhang and Katy Spencer
This paper presents an up-to-date review of data-driven condition monitoring of industrial equipment with the focus on three commonly used equipment: motors, pumps, and bearings. Firstly, the general framework of data-driven condition monitoring is discu...
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Cheng-Jian Lin, Chun-Hui Lin and Frank Lin
The spindle of a machine tool plays a key role in machining because the wear of a spindle might result in inaccurate production and decreased productivity. To understand the condition of a machine tool, a vector-based convolutional fuzzy neural network (...
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Fengyun Xie, Linglan Wang, Haiyan Zhu and Sanmao Xie
Rolling bearings are the core component of rotating machinery. In order to solve the problem that the distribution of collected rolling bearing data is inconsistent during the operation of bearings under complex working conditions, which results in poor ...
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Yuansheng Dai, Yingyi Liu, Haoyu Song, Bing He, Haiwen Yuan and Boyang Zhang
Classification tasks are pivotal across diverse applications, yet the burgeoning amount of data, coupled with complicating factors such as noise, exacerbates the challenge of classifying complex data. For algorithms that require a large amount of data, t...
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Vladislav Kholkin, Olga Druzhina, Valerii Vatnik, Maksim Kulagin, Timur Karimov and Denis Butusov
For the last two decades, artificial neural networks (ANNs) of the third generation, also known as spiking neural networks (SNN), have remained a subject of interest for researchers. A significant difficulty for the practical application of SNNs is their...
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Bo Peng, Ying Bi, Bing Xue, Mengjie Zhang and Shuting Wan
The failure of a rolling bearing may cause the shutdown of mechanical equipment and even induce catastrophic accidents, resulting in tremendous economic losses and a severely negative impact on society. Fault diagnosis of rolling bearings becomes an impo...
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Shuangzhong Wang and Ying Zhang
The federated learning network requires all the connection weights to be shared among the server and clients during training which increases the risk of data leakage. Meanwhile, the traditional federated learning method has a poor diagnostic effect for n...
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