Federated learning is an effective means to combine model information from different clients
to achieve joint optimization when the model of a single client is insufficient. In the case …

Analysis of one-dimensional vibration signals is the most common method used for safety
analysis and health monitoring of rotary machines. How to effectively extract features …

As one of the critical components of rotating machinery, fault diagnosis of rolling bearings
has great significance. Although deep learning is useful in diagnosing rolling bearing faults …

With the development of the manufacturing industry, energy consumption is growing rapidly,
which makes the energy crisis and environmental problems become more and more …

In most of previous machine fault diagnosis, the performance of traditional methods was
over-dependent on high-quality feature extraction from original signals. Recently, deep …

This paper introduces a machine learning-based approach for fault detection in rotating
machinery within the oil and gas industry, focusing on a Gas Turbine-Compressor (GTC) …

Abstract Analysis of 1-D vibration signals is the most common method used for safety
analysis and health monitoring of rotary machines. How to effectively extract features …