A review on the application of blind deconvolution in machinery fault diagnosis
Fault diagnosis is of significance for ensuring the safe and reliable operation of machinery
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …
Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …
machinery. The majority of these machines comprise rotating components and are called …
Wavelet transform for rotary machine fault diagnosis: 10 years revisited
As a multi-resolution analysis method rooted rigorously in mathematics, wavelet transform
(WT) has shown its great potential in rotary machine fault diagnosis, characterized by …
(WT) has shown its great potential in rotary machine fault diagnosis, characterized by …
Adaptive maximum second-order cyclostationarity blind deconvolution and its application for locomotive bearing fault diagnosis
B Zhang, Y Miao, J Lin, Y Yi - Mechanical Systems and Signal Processing, 2021 - Elsevier
Maximum second-order cyclostationarity blind deconvolution (CYCBD) outperforms other
deconvolution methods in retrieving the weak periodic impulses related to bearing incipient …
deconvolution methods in retrieving the weak periodic impulses related to bearing incipient …
Application of parameter optimized variational mode decomposition method in fault diagnosis of gearbox
Z Wang, G He, W Du, J Zhou, X Han, J Wang… - Ieee …, 2019 - ieeexplore.ieee.org
The selection of variational mode decomposition (VMD) parameters usually adopts the
empirical method, trial-and-error method, or single-objective optimization method. The …
empirical method, trial-and-error method, or single-objective optimization method. The …
A scoping review on multi-fault diagnosis of industrial rotating machines using multi-sensor data fusion
Rotating machines is an essential part of any manufacturing industry. The sudden
breakdown of such machines due to improper maintenance can also lead to the industries' …
breakdown of such machines due to improper maintenance can also lead to the industries' …
An improved whale optimization algorithm for forecasting water resources demand
W Guo, T Liu, F Dai, P Xu - Applied Soft Computing, 2020 - Elsevier
Water demand forecasting can promote the rational use of water resources and alleviate the
pressure on water demand. By analyzing the use of water resources, this paper establishes …
pressure on water demand. By analyzing the use of water resources, this paper establishes …
Maximum average kurtosis deconvolution and its application for the impulsive fault feature enhancement of rotating machinery
Blind deconvolution (BD) is a popular tool for vibration analysis, which has been extensively
studied to extract useful information from contaminative signals for the diagnosis of rotating …
studied to extract useful information from contaminative signals for the diagnosis of rotating …
Non-negative multi-label feature selection with dynamic graph constraints
Y Zhang, Y Ma - Knowledge-Based Systems, 2022 - Elsevier
Feature selection can combat dimension disasters and improve the performance of
classification algorithms, so multi-label feature selection is an essential part of multi-label …
classification algorithms, so multi-label feature selection is an essential part of multi-label …
Review of fault detection techniques for predictive maintenance
D Divya, B Marath, MB Santosh Kumar - Journal of Quality in …, 2023 - emerald.com
Purpose This study aims to bring awareness to the developing of fault detection systems
using the data collected from sensor devices/physical devices of various systems for …
using the data collected from sensor devices/physical devices of various systems for …