Structural monitoring systems installed on bridges are capable of capturing large-scale
dynamic responses online and in real-time. The response data of the bridge under different …

Photovoltaic (PV) power generation technology is an effective approach for alleviating the
current energy crisis. However, PV modules are prone to hot-spot faults and shorter service …

针对传统深度学习方法没有充分利用轴承信号的时序特点, 以及难以处理动态数据的问题,
提出一种基于改进卷积双向门控循环神经网络的轴承故障智能诊断方法. 采用卷积神经网络从 …

Deep learning provides new ideas for chemical process fault diagnosis, reducing potential
risks and ensuring safe process operation in recent years. To address the problem that …

Fault diagnosis for body-in-white (BIW) welding robots is important for ensuring the efficient
production of the welding assembly line. As a result of the complex mechanism of the body …

Fault diagnosis is crucial for ensuring the safe and stable operation of complex systems.
Recently, graph convolutional network (GCN)-based fault diagnosis method has emerged …

Text classification plays an important role in information science. In order to address the
issues of low classification efficiency, low accuracy, and incomplete text feature extraction in …

In existing fault diagnosis methods, fault categories are generally coarse-grained, which
may result in failure to precisely identify fault details. Therefore, fine-grained fault diagnosis …

To address the issues of high concealment and difficult positioning of loose bolts in
transmission towers, this paper proposes a new method for locating loose bolts in …

Background In response to the challenge that traditional fault diagnosis models are difficult
to maintain satisfactory accuracy when data distribution changes due to changes in process …