Bearing fault diagnosis using multiclass support vector machines with binary particle swarm optimization and regularized Fisher’s criterion
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Intelligent Manufacturing"
DOI: 10.1007/s10845-014-0987-3
Abstract: Condition monitoring of rotating machinery has attracted more and more attention in recent years in order to reduce the unnecessary breakdowns of components such as bearings and gears which suffer frequently from failures. Vibration based… read more here.
Keywords: binary particle; regularized fisher; support vector; bearing fault ... See more keywords
Medical rolling bearing fault prognostics based on improved extreme learning machine
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Combinatorial Optimization"
DOI: 10.1007/s10878-019-00494-y
Abstract: The problem studied in this article:the random selection of the input weight and the implicit layer bias of the extreme learning machine leads to the instability of the medical rolling bearing fault prediction result of… read more here.
Keywords: fault; learning machine; bearing fault; eem elm ... See more keywords
On bearing fault diagnosis by nonlinear system resonance
Sign Up to like & getrecommendations! Published in 2019 at "Nonlinear Dynamics"
DOI: 10.1007/s11071-019-05305-x
Abstract: The response of a nonlinear system may present strong resonance under a periodic excitation. Based on the nonlinear system resonance, a method of bearing fault diagnosis is proposed in this paper. The system resonance is… read more here.
Keywords: system; resonance; bearing fault; system resonance ... See more keywords
Rolling Element Bearing Fault Diagnosis for Complex Equipment Based on FIFD and PNN
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Failure Analysis and Prevention"
DOI: 10.1007/s11668-020-01072-9
Abstract: The bearing fault feature for complex equipment in early failure period is so weak and susceptible to complicated transmission path and random noise that it’s very difficult to be extracted, so Fast Iterative Filtering Decomposition… read more here.
Keywords: bearing fault; fault; complex equipment; pnn ... See more keywords
A rolling bearing fault diagnosis strategy based on improved multiscale permutation entropy and least squares SVM
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Mechanical Science and Technology"
DOI: 10.1007/s12206-017-0514-5
Abstract: A novel rolling bearing fault diagnosis strategy is proposed based on Improved multiscale permutation entropy (IMPE), Laplacian score (LS) and Least squares support vector machine-Quantum behaved particle swarm optimization (QPSO-LSSVM). Entropy-based concepts have attracted attention… read more here.
Keywords: fault; entropy; bearing fault; rolling bearing ... See more keywords
Rolling bearing fault diagnosis using adaptive deep belief network with dual-tree complex wavelet packet.
Sign Up to like & getrecommendations! Published in 2017 at "ISA transactions"
DOI: 10.1016/j.isatra.2017.03.017
Abstract: Automatic and accurate identification of rolling bearing fault categories, especially for the fault severities and compound faults, is a challenge in rotating machinery fault diagnosis. For this purpose, a novel method called adaptive deep belief… read more here.
Keywords: adaptive deep; fault; bearing fault; rolling bearing ... See more keywords
Weighted low-rank sparse model via nuclear norm minimization for bearing fault detection
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Sound and Vibration"
DOI: 10.1016/j.jsv.2017.03.044
Abstract: Abstract It is a fundamental task in the machine fault diagnosis community to detect impulsive signatures generated by the localized faults of bearings. The main goal of this paper is to exploit the low-rank physical… read more here.
Keywords: fault; nuclear norm; fault detection; bearing fault ... See more keywords
A new l0-norm embedded MED method for roller element bearing fault diagnosis at early stage of damage
Sign Up to like & getrecommendations! Published in 2018 at "Measurement"
DOI: 10.1016/j.measurement.2018.06.016
Abstract: Abstract Minimum entropy deconvolution (MED) has been widely applied to extract the repetitive transients. Its effectiveness for bearing fault diagnosis, however, might be undermined by the drawbacks: 1) it prefers a solution of a single… read more here.
Keywords: norm embedded; bearing fault; fault diagnosis;
Semi-random subspace with Bi-GRU: Fusing statistical and deep representation features for bearing fault diagnosis
Sign Up to like & getrecommendations! Published in 2020 at "Measurement"
DOI: 10.1016/j.measurement.2020.108603
Abstract: Abstract Statistical features and deep representation features have been widely used in bearing fault diagnosis. These two kinds of features have their superiorities, however, few studies have explored combining them and considering their heterogeneousness. Therefore,… read more here.
Keywords: random subspace; bearing fault; semi random; representation features ... See more keywords
Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images
Sign Up to like & getrecommendations! Published in 2021 at "Measurement"
DOI: 10.1016/j.measurement.2021.109196
Abstract: Abstract The bearings are the crucial components of rotating machines in an industrial firm. Unplanned failure of these components not only increases the downtime, but also leads to production loss. This paper presents a non-invasive… read more here.
Keywords: neural network; diagnosis rotating; bearing fault; bearing ... See more keywords
Intelligent bearing fault diagnosis based on Teager energy operator demodulation and multiscale compressed sensing deep autoencoder
Sign Up to like & getrecommendations! Published in 2021 at "Measurement"
DOI: 10.1016/j.measurement.2021.109452
Abstract: Abstract Accurate fault diagnosis is essential to ensure the stability and reliability of machine systems. Deep learning (DL) techniques have demonstrated potential in realizing intelligent fault diagnosis. However, the obtained bearing signals in the actual… read more here.
Keywords: diagnosis; bearing fault; intelligent bearing; fault diagnosis ... See more keywords