Planetary gearboxes have various merits in mechanical transmission, but their complex
structure and intricate operation modes bring large challenges in terms of fault diagnosis …

In recent years, vibration signals have been widely applied for the identification of
mechanical states in oil-immersed transformers. This paper, following the framework of …

Recently, as a representative of deep learning methods, Transformers have shown great
prowess in intelligent fault diagnosis, offering powerful feature extraction and modeling …

Deep learning for bearing fault diagnosis often requires a large quantity of comprehensive
data to give support in the field of rotating machinery fault diagnosis. However, large …

Recording the trajectory of table tennis balls in real-time enables the analysis of the
opponent's attacking characteristics and weaknesses. The current analysis of the ball paths …

AI-enabled industrial equipment monitoring, diagnosis and health management -
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Planetary gearboxes are popular in many industrial applications due to their compactness
and higher transmission ratios. With recent developments in the area of machine learning …

High-quality data is essential for effective operation and maintenance of wind farms.
However, data missing is a persistent issue in the supervisory control and data acquisition …

Condition monitoring is a fundamental task in the reliability engineering and operation
management of a complex industrial system. It aims to detect faults based on sensing data …

The accurate predictions of remaining useful life (RUL) have become a key and extremely
challenging problem. Due to the limitations of the classical convolutional neural network and …