Non-Stationary Vibratory Signatures Bearing Fault Detection Using Alternative Novel Kurtosis-based Statistical Analysis
Vibration signature-based analysis to detect and diagnose is the commonly used technique in the monitoring of rotating machinery. Reliable features will determine the efficacy of diagnosis and prognosis results in the field of machine condition monitoring. This study intends to produce a reliable s...
Main Authors: | Nur Adilla Kasim, Mohd Ghafran Mohamed, Mohd Zaki Nuawi |
---|---|
Format: | Article |
Language: | English |
Published: |
UNIMAS Publisher
2022-04-01
|
Series: | Journal of Applied Science & Process Engineering |
Subjects: | |
Online Access: | https://publisher.unimas.my/ojs/index.php/JASPE/article/view/4594 |
Similar Items
-
Mechanical bearing fault detection based on two-stage neural network
by: X. Y. Fu, et al.
Published: (2024-01-01) -
Experimental Vibration Data in Fault Diagnosis: A Machine Learning Approach to Robust Classification of Rotor and Bearing Defects in Rotating Machines
by: Khalid M. Almutairi, et al.
Published: (2023-10-01) -
FPGA implementation of an improved envelope detection approach for bearing fault diagnosis
by: Mohamed Rebiai, et al.
Published: (2024-01-01) -
Fault diagnosis of rolling bearing based on kurtosis criterion VMD and modulo square threshold
by: Xueying Zhang, et al.
Published: (2019-12-01) -
Calculation of Capacitive-Based Sensors of Rotating Shaft Vibration for Fault Diagnostic Systems of Powerful Generators
by: Ievgen Zaitsev, et al.
Published: (2022-02-01)