A brief review of acoustic and vibration signal-based fault detection for belt conveyor idlers using machine learning models
Due to increasing demands for ensuring the safety and reliability of a system, fault detection
(FD) has received considerable attention in modern industries to monitor their machines …
(FD) has received considerable attention in modern industries to monitor their machines …
Solving multiobjective fuzzy job-shop scheduling problem by a hybrid adaptive differential evolution algorithm
The job-shop scheduling problem (JSP) is NP hard, which has very important practical
significance. Because of many uncontrollable factors, such as machine delay or human …
significance. Because of many uncontrollable factors, such as machine delay or human …
Role of image feature enhancement in intelligent fault diagnosis for mechanical equipment: A review
Y Sun, W Wang - Engineering Failure Analysis, 2023 - Elsevier
In the modern manufacturing industry, mechanical equipment plays a crucial role.
Equipment working in harsh environments for a long time is more likely to break down …
Equipment working in harsh environments for a long time is more likely to break down …
Attention-based multiscale denoising residual convolutional neural networks for fault diagnosis of rotating machinery
CNN-based fault diagnosis approaches have achieved promising results in improving the
safety and reliability of rotating machinery. Most of the existing CNN models are developed …
safety and reliability of rotating machinery. Most of the existing CNN models are developed …
Snake optimization-based variable-step multiscale single threshold slope entropy for complexity analysis of signals
Y Li, B Tang, S Jiao, Q Su - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Slope entropy (SloEn) is an effective complexity analysis measure of signals that has been
applied to many areas in recent years. Whereas SloEn can only reflect the complexity …
applied to many areas in recent years. Whereas SloEn can only reflect the complexity …
Early fault diagnosis of rotating machinery based on composite zoom permutation entropy
C Ma, Y Li, X Wang, Z Cai - Reliability Engineering & System Safety, 2023 - Elsevier
Fault diagnosis of rotating machinery serves an important role in informing system operation
and predictive maintenance decisions. To quantify the fault information from vibrational …
and predictive maintenance decisions. To quantify the fault information from vibrational …
A two-phase-based deep neural network for simultaneous health monitoring and prediction of rolling bearings
Simultaneous health monitoring and remaining useful life (RUL) prediction are important
objectives in ensuring operational reliability and efficient maintenance of rolling bearings …
objectives in ensuring operational reliability and efficient maintenance of rolling bearings …
Hierarchical diversity entropy for the early fault diagnosis of rolling bearing
Intelligent fault diagnosis provides great convenience for the prognostic and health
management of the rotating machinery. Recently, the multiscale diversity entropy has been …
management of the rotating machinery. Recently, the multiscale diversity entropy has been …
Multivariate multiscale dispersion Lempel–Ziv complexity for fault diagnosis of machinery with multiple channels
Abstract Lempel–Ziv complexity (LZC), as a nonlinear feature in information science, has
shown great promise in detecting correlations and capturing dynamic changes in single …
shown great promise in detecting correlations and capturing dynamic changes in single …
Dynamic time warping using graph similarity guided symplectic geometry mode decomposition to detect bearing faults
J Guo, Z Si, Y Liu, J Li, Y Li, J Xiang - Reliability Engineering & System …, 2022 - Elsevier
A bearing's health state is closely linked to the reliable operation of rotating machinery. In
this context, dynamic time warping (DTW) is an excellent fault classifier due to its …
this context, dynamic time warping (DTW) is an excellent fault classifier due to its …