High-speed trains have become one of the most important and advanced branches of
intelligent transportation, of which the reliability and safety are still not mature enough for …

With the advancement of industrial systems, fault monitoring and diagnosis methods based
on the data-driven attract much attention in recent years. This kind of methods are widely …

Fault detection and diagnosis (FDD) is crucial for stable, reliable, and safe operation of
industrial equipment. In recent years, deep learning models have been widely used in data …

Energy-intensive manufacturing industries are characterised by high pollution and heavy
energy consumption, severely challenging the ecological environment. Fortunately …

Predictive maintenance is one of the important technical means to guarantee and improve
the normal industrial production. The existing bottlenecks for popularization and application …

针对滚动轴承故障特征提取不丰富而导致的诊断识别率低的情况, 提出了基于参数优化变分模态
分解(Variational mode decomposition, VMD) 和样本熵的特征提取方法, 采用支持向量机 …

Incipient faults in electrical drives can corrupt overall performance of high-speed trains;
however, they are difficult to discover because of their slight fault symptoms. By sufficiently …

Soft-sensors usually assist in dealing with the unavailability of hardware sensors in process
industries, thus allowing for less fault occurrence and better control performance. However …

In recent years, machine learning techniques have been applied to test the fault type in high-
voltage circuit breakers (HVCBs). Most related research involves in improving the …

Fault diagnosis methods based on deep learning and big data have achieved good results
on rotating machinery. However, the conventional deep learning method of bearing fault …