A K-means clustering approach is proposed for the automated diagnosis of defective rolling
element bearings. Since K-means clustering is an unsupervised learning procedure, the …

This study explores the use of a hyperchaotic signal as an excitation to probe a system for
dynamic changes induced by damage events. In chaotic interrogation a deterministic chaotic …

Fractal dimension (FD) is one of the most utilized parameters for characterizing and
discriminating vibration signals in gear fault detection. However, most of the natural signals …

根据混沌信号处理理论, 研究分析了关联维数, 最大Lyapunov 指数和Kolmogorov
熵等转子碰摩声发射源的非线性动力学特征量的特性. 并将这些特征量作为神经网络的输入 …

This paper proposes a novel technique combining datadriven and model-based techniques
to significantly improve the performance in bearing fault diagnostics. Features that provide …

La presencia de una falla en un rodamiento hace que el sistema mecánico evolucione de
una dinámica débilmente no lineal a una dinámica fuertemente no lineal, por lo tanto los …

The vibration signal of transmission bearing is decomposed by empirical mode
decomposition, and fractal dimensions of decomposed intrinsic mode functions are …

La metodología presentada en esta tesis está basada en una recopilación de métodos,
herramientas y conceptos utilizados por el grupo de Control y Procesamiento Digital de …

Feature selection is an effective way of improving classification, reducing feature dimension,
and speeding up computation. This work studies a reported support vector machine (SVM) …