Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …

Electric motors act as the backbone of industrial development. Their reliable and safe
operation is essential to various industries. At present, motor fault diagnosis based on …

The signal-processing and intelligent diagnostic and monitoring methods based on motor
current signature analysis for induction motors (IM) usually depend on preset parameters …

Motor plays a core role in most industrial equipment. Accurate fault diagnosis of motor is a
critical task and intelligent data-driven methods have gained significant advances. However …

Through the application of deep learning and multi-sensor data, fault features can be
automatically extracted and valuable information can be integrated to tackle intricate …

The fault diagnosis method based on generative adversarial networks (GANs) has been
successfully applied to the early fault detection of motor bearings, and it has effectively …

Effective damage identification is paramount to evaluating safety conditions and preventing
catastrophic failures of concrete structures. Although various methods have been introduced …

Using deep learning in three-phase induction motor fault diagnosis has gained increasing
interest nowadays. This paper proposes a Convolutional Neural Network (CNN) model to …

Deep learning methods have demonstrated promising performance in fault diagnosis tasks.
Although the scarcity of data in industrial scenarios limits the practical application of such …

Real-time motor fault diagnosis can detect motor faults on time and prompt the repair or
replacement of faulty motors, which minimizes the potential losses caused by motor faults …