Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Vibration signal-based early fault prognosis: Status quo and applications
Abstract To implement Prognostics and Health Management (PHM) for industrial systems, it
is paramount to conduct early fault prognosis on the systems to ensure the stability and …
is paramount to conduct early fault prognosis on the systems to ensure the stability and …
Review of research on signal decomposition and fault diagnosis of rolling bearing based on vibration signal
J Li, W Luo, M Bai - Measurement Science and Technology, 2024 - iopscience.iop.org
Rolling bearings are critical components that are prone to faults in the operation of rotating
equipment. Therefore, it is of utmost importance to accurately diagnose the state of rolling …
equipment. Therefore, it is of utmost importance to accurately diagnose the state of rolling …
Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
Effective fault diagnosis has long been a research topic in the prognosis and health
management of rotary machinery engineered systems due to the benefits such as safety …
management of rotary machinery engineered systems due to the benefits such as safety …
Weak fault feature extraction of rolling bearings based on improved ensemble noise-reconstructed EMD and adaptive threshold denoising
Extracting weak fault features under noise interference is crucial for the fault diagnosis of
rolling bearings at an early stage. In this paper, a new method based on improved ensemble …
rolling bearings at an early stage. In this paper, a new method based on improved ensemble …
Vibration-based intelligent fault diagnosis for roller bearings in low-speed rotating machinery
L Song, H Wang, P Chen - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a new signal feature extraction and fault diagnosis method for fault
diagnosis of low-speed machinery. Statistic filter (SF) and wavelet package transform (WPT) …
diagnosis of low-speed machinery. Statistic filter (SF) and wavelet package transform (WPT) …
Intelligent fault diagnosis of rotating machinery using improved multiscale dispersion entropy and mRMR feature selection
X Yan, M Jia - Knowledge-Based Systems, 2019 - Elsevier
Intelligent fault diagnosis of rotating machinery is essentially a pattern recognition problem.
Meanwhile, effective feature extraction from the raw vibration signal is an important …
Meanwhile, effective feature extraction from the raw vibration signal is an important …
Fault feature extraction of rotating machinery using a reweighted complete ensemble empirical mode decomposition with adaptive noise and demodulation analysis
L Wang, Y Shao - Mechanical systems and signal processing, 2020 - Elsevier
Fault feature extraction is crucial to detect failures as earlier as possible in fault diagnosis of
rotating machinery. Due to the influence of environment noise and interference, the signal to …
rotating machinery. Due to the influence of environment noise and interference, the signal to …
Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions
Incipient fault diagnosis of a bearing requires robust feature representation for an accurate
condition-based monitoring system. Existing fault diagnosis schemes are mostly confined to …
condition-based monitoring system. Existing fault diagnosis schemes are mostly confined to …
Application of a new EWT-based denoising technique in bearing fault diagnosis
The vibration signal analysis is a popular method for extracting sensitive fault features. The
vibration signals are usually contaminated by noise, and therefore the extracted features …
vibration signals are usually contaminated by noise, and therefore the extracted features …
Classification of epilepsy EEG signals using DWT-based envelope analysis and neural network ensemble
Epilepsy is a neurological disorder of brain which is characterized by recurrent disorders.
And people with epilepsy and their families frequently suffer from stigma and discrimination …
And people with epilepsy and their families frequently suffer from stigma and discrimination …