This study aims to establish a novel entropy-based sparsity measure for two main purposes:
first is for the prognosis of bearing defects, secondly it is employed to construct sparsogram …

This study is a comprehensive and modern approach to predict customer churn in the
example of an e-commerce retail store operating in Brazil. Our approach consists of three …

Abstract Metal-based Laser Powder Bed Fusion (LPBF) has made fabricating intricate
components easier. Yet, assessing part quality is inefficient, relying on costly Computed …

Due to the spatially dispersed occurrence of faults and the challenges associated with
sensor installation in axial flow pump equipment, an underwater acoustic signal collection …

The occurrence of multiple faults is a practical problem in the bearings of rotating machines,
and early diagnosis of such issues in an intelligent manner is vital in the era of industry 4.0 …

Blockages in the suction or discharge side of the pump adversely affect the pump's
performance by reducing the flow rate and head, increasing vibration, noise, and …

In the signal analysis context, the entropy concept can characterize signal properties for
detecting anomalies or non-representative behaviors in fiscal systems. In motor fault …

Condition monitoring and fault diagnosis of wind turbines is an attractive yet challenging
task. This paper presents a novel data-driven fault diagnosis scheme for wind turbines …

The multi-row bearings of rolling mills are subject to axial and radial loads. Due to the
complex working conditions, it is difficult to achieve better results in fault diagnosis by …

Due to the complex service conditions of rolling bearings, vibration signals arising therefrom
exhibit non-linear characteristics, which means that single-scale feature extraction …