Effective fault diagnosis of rotating machinery is essential for the predictive maintenance of
modern industries. In this study, a novel framework that combines a residual network …

Combustion is the main source of energy and environmental pollution. The objective of the
combustion study is to improve combustion efficiency and reduce pollution emissions. In the …

The fault safety monitoring of hydrogen sensors is very important for their practical
application. The precondition of traditional machine learning methods for sensor fault …

Despite its growing importance in the energy generation and storage industry, the detection
of hydrogen in trace concentrations remains challenging, as established optical absorption …

As a part of the energy transmission chain, gearboxes are considered as important
components in rotating machines, and the gearbox failure results in costly economic losses …

The fault diagnosis of hydrogen sensors is of great significance. However, it is difficult to
collect data samples for some modes of hydrogen sensor signals, so the data samples may …

The incipient fault detection technology of rolling bearings is the key to ensure its normal
operation and is of great significance for most industrial processes. However, the vibration …

Sensor systems have been used widely in many fields. However, sensors are prone to
faults, which greatly reduce the performance of the trained pattern-recognition model. To …

This paper reports an infrared electronic nose based on ensemble learning and principal
component analysis (PCA) fault diagnosis, which addresses the self-detection and self …

This paper develops a new architecture for bearing fault diagnosis based on independent
vector analysis, feature selection, and extreme learning machines classifiers. The suggested …