This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …

With the increase of the scale and complexity of mechanical equipment, traditional intelligent
fault diagnosis (IFD) based on shallow machine learning methods is unable to meet the …

Bearing fault diagnosis has made some achievements based on massive labeled fault data.
In practical engineering, machines are mostly in healthy and faults seldom happen, it's …

Fault detection and classification are considered as one of the most mandatory techniques
in nowadays industrial monitoring. The necessity of fault monitoring is due to the fact that …

This paper presents a comprehensive review of the developments made in rotating bearing
fault diagnosis, a crucial component of a rotatory machine, during the past decade. A data …

The rolling bearing fault signals are complex time series with complex dynamic
characteristics and non-uniform periodicity due to the influence of random interference, such …

海量高维度的过程测量信息给传统的故障诊断算法带来极大的计算复杂度和建模复杂度,
且传统诊断算法存在难以利用高阶量进行在线估计的不足. 鉴于深度学习技术强大的数据表示 …

Reciprocating compression machinery is the primary source of compressed air in the
industry. Undiagnosed faults in the machinery's components produce a high rate of …

With the increase in the installed capacity of wind power systems, the fault diagnosis and
condition monitoring of wind turbines (WT) has attracted increasing attention. In recent …

Early fault diagnosis of rotating machinery is crucial in the industry. The network parameters
of the traditional deep learning-based fault diagnosis method are optimized only by the …