Diagnosing faults in electric motors is a task of great importance for the Industrial Sector
since stop** these types of equipment can cause several invaluable losses for industries …

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 …

Objective Recently, monkeypox virus is slowly evolving and there are fears it will spread as
COVID-19. Computer-aided diagnosis (CAD) based on deep learning approaches …

When dealing with a limited number of fault samples, prevailing fault diagnosis methods
often succumb to overfitting, impeding the attainment of precise fault diagnosis. Hence, this …

Fault diagnosis of industrial processes plays an important role in avoiding heavy losses and
ensuring production safety. Complex industrial processes often have many working …

Rags, dusts, foreign particles, etc., are the primary cause of blockage in the centrifugal pump
and deteriorate the performance. This study elaborates an experimental and data-driven …

Monitoring and fault detection can be critical for efficient, safe and reliable operation of
electric drive systems. Unfortunately, develo** accurate physics-based models for these …

High-speed traveling wave acquisition devices often use a mutation start algorithm with a
low threshold value, which can collect a large number of interference clutters. If the devices …

Since wind turbines are exposed to harsh working environments and variable weather
conditions, wind turbine blade condition monitoring is critical to prevent unscheduled …

Anomalies in wind turbines pose significant risks of costly downtime and maintenance,
underscoring the importance of early detection for reliable operation. However, conventional …