Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …

Recently, condition monitoring (CM) and fault detection and diagnosis (FDD) techniques for
rotating machinery (RM) have witnessed substantial advancements in recent decades …

行星齿轮箱振动信号具有非平稳特性, 需要一定的先验知识和诊断专业知识设计和解释特征从而
实现故障诊断. 为了实现行星齿轮箱的智能诊断, 提出一种基于经验模态分解(Empirical mode …

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with
complicated damage detection problems of mechanical systems. Nevertheless, this …

Worm gearboxes (WG) are frequently used in many areas of the industry. WG is different
from other gearbox types and due to their working principles they are under high risk of wear …

Accurately and intelligently identifying faults of the planetary gearbox is essential in the safe
and reliable operation and maintenance of the mechanical drive system. Recently, fault …

With the great ability of transforming data into deep and abstract features adaptively through
nonlinear mapping, deep learning is a promising tool to improve the intelligence and …

Rotating speed fluctuation is a key problem that affects the fault diagnosis performance of
mechanical equipment. Deep learning theory can use deep neural networks to realize …

Aiming at the problem of gear fault feature extraction and fault classification under different
load excitation, we present a new fault diagnosis method that combines three methods …

Sažetak Motor electrical current signature analysis (MCSA) is sensing an electrical signal
containing current components that are direct by-product of unique rotating flux components …