With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …

Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …

Maintaining electrical machines in good working order and increasing their life expectancy
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …

Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating
machinery (RM) has a vital role in the modern industrial world. However, the remaining …

Fault diagnosis of the bearing is vital for the safe and reliable operation of rotating machines
in the manufacturing industry. Convolutional neural networks (CNNs) have been popular in …

Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …

Untimely machinery breakdown will incur significant losses, especially to the manufacturing
company as it affects the production rates. During operation, machines generate vibrations …

In recent years, methods for detecting motor bearing faults have attracted increasing
attention. However, it is very difficult to detect the faults from weak motor bearing signals …

Thermographic fault diagnosis of ventilation in BLDC (brushless DC) motors is described.
The following states of BLDC motors were analyzed: a healthy BLDC motor running at 1450 …

Along with the rapid development of infrastructure worldwide, traditional manual operations
have been a concern that restricts the high efficiency, safety, and quality of construction …