Fault feature extraction method based on optimized sparse decomposition algorithm for AUV with weak thruster fault
Sign Up to like & getrecommendations! Published in 2021 at "Ocean Engineering"
DOI: 10.1016/j.oceaneng.2021.109013
Abstract: Abstract This paper investigates fault feature extraction for autonomous underwater vehicles (AUVs) with weak thruster fault. When the conventional feature extraction method based on time-frequency domain decomposition is used to extract the weak fault feature… read more here.
Keywords: decomposition; thruster; feature; extraction ... See more keywords
A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery
Sign Up to like & getrecommendations! Published in 2017 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2017.02.036
Abstract: Abstract Singular value decomposition (SVD), as an effective signal denoising tool, has been attracting considerable attention in recent years. The basic idea behind SVD denoising is to preserve the singular components (SCs) with significant singular… read more here.
Keywords: fault feature; feature; weak fault; signal denoising ... See more keywords
Optimal periodicity-enhanced group sparse for bearing incipient fault feature extraction
Sign Up to like & getrecommendations! Published in 2023 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/accc4c
Abstract: Efficient and automatic fault feature extraction of rotating machinery, especially for incipient faults is a challenging task of great significance. In this article, an optimal periodicity-enhanced group sparse method is proposed. Firstly, a period sequence… read more here.
Keywords: group; fault feature; group sparse; periodicity ... See more keywords
Low-Rank Enforced Fault Feature Extraction of Rolling Bearings in a Complex Noisy Environment: A Perspective of Statistical Modeling of Noises
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3165281
Abstract: The fault feature extraction of rolling element bearings is of critical interest for fault diagnosis. The fault impulses are always buried in strong and complex background noise, which makes it hard to detect the fault… read more here.
Keywords: noise; low rank; feature extraction; fault ... See more keywords
Fault Feature Recovery With Wasserstein Generative Adversarial Imputation Network With Gradient Penalty for Rotating Machine Health Monitoring Under Signal Loss Condition
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3168898
Abstract: Rotating machine health monitoring systems sometimes suffer from large segments of continuous missing data in practical applications, which may lead to incorrect health assessments and maintenance decisions. However, current signal loss recovery methods are sometimes… read more here.
Keywords: loss; feature recovery; fault; fault feature ... See more keywords
Research on Fault Feature Extraction Method Based on NOFRFs and Its Application in Rotor Faults
Sign Up to like & getrecommendations! Published in 2019 at "Shock and Vibration"
DOI: 10.1155/2019/3524948
Abstract: Rub-impact between the rotating and static parts is a more common fault. The occurrence of faults is often accompanied by the generation of nonlinear phenomena. However, it is difficult to find out because the nonlinear… read more here.
Keywords: fault feature; fault; research fault; method ... See more keywords
An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds
Sign Up to like & getrecommendations! Published in 2020 at "Shock and Vibration"
DOI: 10.1155/2020/1745184
Abstract: The compressive sensing (CS) theory provides a new slight to the big-data problem led by the Shannon sampling theorem in rolling element bearings condition monitoring, where the measurement matrix of CS tends to be designed… read more here.
Keywords: fault feature; mcm; compressive sensing; matrix ... See more keywords
Automatic Bearing Fault Feature Extraction Method via PFDIC and DBAS
Sign Up to like & getrecommendations! Published in 2021 at "Mathematical Problems in Engineering"
DOI: 10.1155/2021/6655081
Abstract: Determining the embedded dimension of a singular value decomposition Hankel matrix and selecting the singular values representing the intrinsic information of fault features are challenging tasks. Given these issues, this work presents a singular value… read more here.
Keywords: fault feature; fault; feature extraction; method ... See more keywords
An iterative morphological difference product wavelet for weak fault feature extraction in rolling bearing fault diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "Structural Health Monitoring"
DOI: 10.1177/14759217221086314
Abstract: Weak fault feature extraction is of great significance to the fault diagnosis of rolling bearing. At the early stage of defects, fault features are usually weak and easily submerged in strong background noise, which makes… read more here.
Keywords: wavelet; rolling bearing; fault; difference ... See more keywords
EEMD-Based cICA method for single-channel signal separation and fault feature extraction of gearbox
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Vibroengineering"
DOI: 10.21595/jve.2017.18115
Abstract: This paper proposes a novel fault feature extraction method with the aim of extracting the fault feature submerged in the single-channel observation signal. The proposed method integrates the strengths of the constrained independent component analysis… read more here.
Keywords: fault feature; single channel; feature extraction; method ... See more keywords
Incipient Fault Feature Enhancement of Rolling Bearings Based on CEEMDAN and MCKD
Sign Up to like & getrecommendations! Published in 2023 at "Applied Sciences"
DOI: 10.3390/app13095688
Abstract: A rolling bearing vibration signal fault feature enhancement method based on adaptive complete ensemble empirical mode decomposition with adaptive noise algorithm (CEEMDAN) and maximum correlated kurtosis deconvolution (MCKD) is proposed to address the issue that… read more here.
Keywords: feature enhancement; feature; mckd; fault ... See more keywords