For the detection of incipient interturn short-circuit (IITSC) faults of machines without shutting
them down, there are still shortcomings of insufficient incipient fault features and a high false …

As a key component of mechanical equipment, real-time monitoring and diagnosis of rolling
bearings play a critical role in ensuring the stable operation of equipment and the safety of …

Health condition detection is an essential method in ensuring the equipment operates
safely, which relies on effective feature learning technology. However, traditional feature …

Novelty detection of leukocyte images aims to learn effective data description from in-
distribution leukocyte samples and detect out-of-distribution ones that deviate from the …

An innovative deep-learning-based model, namely, deep anomaly detection with the same
probability distribution (DADSPD) is proposed to improve the accuracy of anomaly detection …

One of the most critical assignments in fault diagnosis is to decide the finest set of features
by evaluating the statistical parameters of the time-domain signals. However, these …

Deep learning techniques have been widely applied for performing intelligent fault
diagnosis (IFD) for applications such as bearing fault diagnosis, wind turbines and drilling …

It is difficult to obtain bearing fault data under actual operating conditions, so a small number
of data samples are captured, which leads to over-fitting problems in model training, and the …

Remaining Useful Life (RUL) prediction of mechanical equipment is an application of
Prognostics and Health Management (PHM) technology in mechanical equipment, and is …

为了解决传统纸机轴承故障带来的突然停机停产问题, 提出基于射频识别(RFID)
管理的纸机轴承在线自动修复系统. 该系统以嵌入式LPC2103 微处理器为控制中枢 …