Vibration feature extraction using signal processing techniques for structural health monitoring: A review
Structural health monitoring (SHM) has become an important and hot topic for decades in
various fields of civil, mechanical, automotive, and aerospace engineering, etc. Estimating …
various fields of civil, mechanical, automotive, and aerospace engineering, etc. Estimating …
Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: A state-of-the-art review
Uninterrupted and trouble-free operation of induction motors (IMs) is the compulsion of the
modern industries. Firstly, the paper reviews the conventional time and spectrum signal …
modern industries. Firstly, the paper reviews the conventional time and spectrum signal …
[HTML][HTML] A review on rolling bearing fault signal detection methods based on different sensors
G Wu, T Yan, G Yang, H Chai, C Cao - Sensors, 2022 - mdpi.com
As a precision mechanical component to reduce friction between components, the rolling
bearing is widely used in many fields because of its slight friction loss, strong bearing …
bearing is widely used in many fields because of its slight friction loss, strong bearing …
EEMD-based notch filter for induction machine bearing faults detection
This paper deals with induction machine bearing faults detection based on an empirical
mode decomposition approach combined to a statistical tool. In particular, it is proposed an …
mode decomposition approach combined to a statistical tool. In particular, it is proposed an …
Uncertainty-weighted domain generalization for remaining useful life prediction of rolling bearings under unseen conditions
S Tong, Y Han, X Zhang, H Tian, X Li… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Domain adaptation (DA) methods are widely used in rolling bearing remaining useful life
(RUL) prediction to align source and target domains. However, DA relies on previously …
(RUL) prediction to align source and target domains. However, DA relies on previously …
Broken rotor bar fault diagnosis using fast Fourier transform applied to field-oriented control induction machine: simulation and experimental study
In the paper, a fault diagnosis of the induction motor (IM) at closed loop is presented, and the
fault considered in the machine is the adjacent broken rotor bars. The technique of control …
fault considered in the machine is the adjacent broken rotor bars. The technique of control …
[HTML][HTML] Bearing faults diagnosis by current envelope analysis under direct torque control based on neural networks and fuzzy logic—a comparative study
Diagnosing bearing defects (BFs) in squirrel cage induction machines (SCIMs) is essential
to ensure their proper functioning and avoid costly breakdowns. This paper presents an …
to ensure their proper functioning and avoid costly breakdowns. This paper presents an …
[Retracted] Music Recommendation Algorithm Based on Multidimensional Time‐Series Model Analysis
J Shi - Complexity, 2021 - Wiley Online Library
This paper proposes a personalized music recommendation method based on
multidimensional time‐series analysis, which can improve the effect of music …
multidimensional time‐series analysis, which can improve the effect of music …
Bearing fault detection in asd-powered induction machine using modwt and image edge detection
Today the industry depends on various types of three-phase induction machines, requiring
operating at variable speeds to perform more complex processes. Therefore, it is vital to …
operating at variable speeds to perform more complex processes. Therefore, it is vital to …
[HTML][HTML] Fault diagnosis of induction machines in a transient regime using current sensors with an optimized slepian window
J Burriel-Valencia, R Puche-Panadero… - Sensors, 2018 - mdpi.com
The aim of this paper is to introduce a new methodology for the fault diagnosis of induction
machines working in the transient regime, when time-frequency analysis tools are used. The …
machines working in the transient regime, when time-frequency analysis tools are used. The …