Corrosion Fault Diagnosis of Rolling Element Bearing under Constant and Variable Load and Speed Conditions

Sharma, Sanjay; Abed, Wathiq; Sutton, Robert I.; Subudhi, Bidyadhar

doi:10.1016/j.ifacol.2015.12.352

Cited by 19 publications

(10 citation statements)

References 16 publications

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“…Thus, the long-short term memory (LSTM) [173] and the gated recurrent units (GRU) techniques [174] were developed. Almost all found papers, [175][176][177][178][179][180] used the RNN as a tool not only for REB fault diagnosis, but also for prognosis, except Abed et al [175]. Abed et al [175] used dynamic recurrent neural networks (DRNNs) that can learn the dynamics of nonlinear systems, whereas conventional static neural networks cannot.…”

Section: (Deep) Rnn-based Reb Phm Approachesmentioning

confidence: 99%

“…The results showed that the RNN did not work well in a short-term prediction case, but for long-term prediction, the RNN did increase the training speed and achieved good prognostic results. Sharma et al [177] proposed a robust fault analysis method to diagnose and predict the level of fault severity of a REB. They used DWT for feature extraction, and an orthogonal fuzzy neighborhood discriminative analysis (OFNDA) technique for feature reduction.…”

Section: (Deep) Rnn-based Reb Phm Approachesmentioning

confidence: 99%

“…Thus, three categories were proposed in this paper: (1) Statistical approaches, which were divided to LDA-based REB PHM, SVM-based REB PHM, KNN-based REB PHM, ELM-based REB PHM, and other statistical algorithms for REB PHM; (2) NN approaches; and (3) combined methods. Further, DL-based REB PHM techniques were also reviewed and classified into four groups in this paper, as follows: ( [176], [178] Fault prognosis [177], [179], [180], [181] RBM-based DNN approaches DBN-based The DBN is a NN of multiple layers, which has stochastic latent variables (hidden units) and a generative graphical model; it is constructed by stacking multiple…”

Section: Summary and Concluding Remarksmentioning

confidence: 99%

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A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning

et al. 2019

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The objective of this paper is to present a comprehensive review of the contemporary techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs). Data-driven approaches, as opposed to model-based approaches, are gaining in popularity due to the availability of low-cost sensors and big data. This paper first reviews the fundamentals of prognostics and health management (PHM) techniques for REBs. A brief description of the different bearing-failure modes is given, then, the paper presents a comprehensive representation of the different health features (indexes, criteria) used for REB fault diagnostics and prognostics. Thus, the paper provides an overall platform for researchers, system engineers, and experts to select and adopt the best fit for their applications. Second, the paper provides overviews of contemporary REB PHM techniques with a specific focus on modern artificial intelligence (AI) techniques (i.e., shallow learning algorithms). Finally, deep-learning approaches for fault detection, diagnosis, and prognosis for REB are comprehensively reviewed.

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Section: (Deep) Rnn-based Reb Phm Approachesmentioning

confidence: 99%

Section: (Deep) Rnn-based Reb Phm Approachesmentioning

confidence: 99%

Section: Summary and Concluding Remarksmentioning

confidence: 99%

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A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning

et al. 2019

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“…Based on the required magnetic field density in the rotor, the proper magnetic material is chosen to make the rotor. Ferrite magnets are traditionally used to make permanent magnets [6]. As the technology advances, rare earth alloy magnets are gaining popularity.…”

Section: B) Rotormentioning

confidence: 99%

Modeling and Performance Analysis of BLDC Motor under Different Operating Speed Conditions

Karthik¹

2017

ijecs

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Abstract:The modeling and performance analysis of BLDC motor under different operating speed conditions has been presented in this paper. BLDC motors have been gaining attention from various Industrial and household appliance manufacturers, because of its high efficiency, high power density, and low maintenance cost. After many research and developments in the fields of magnetic materials and power electronics, their applications to electric drives have increased to a significant extent. In this paper, the modeling of Brushless DC motor drive system along with control system for speed and current has been presented using MATLAB / SIMULINK. In order to evaluate the model, various cases of simulation studies are carried out. Test results thus obtained show that the model performance is satisfactory.

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“…Several common types of faults in rotating machineries include bearing fault, gear fault, misalignment and imbalance fault [3,4]. Vibration analysis becomes a common condition monitoring method of rotating machinery faults since they can be detected by studying the vibration signal collected on the machine [5].…”

Section: Introductionmentioning

confidence: 99%

Design and development of a modular vibration test rig for combination types of fault in rotating machinery health diagnosis

Silahuddin

Aizuddin

Mohamaddan

et al. 2019

JMES

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As a basis to real application of rotating machineries operation, a test rig imitating the operation is designed for the research environment. The purpose of this study is to design a modular test rig which is able to facilitate different fault component combinations and evaluate the deformation pattern of the fabricated test rig. Rotating machineries face the probability of having simultaneous different faults and the study of this condition is limited. The designed test rig could be arranged into multiple configurations by adding or excluding desired components due to its modularity. This will be useful to study the response of each component during operation as well as the response of combinations of fault components. Included in this study is the analysis of the design, the components of the test rig and the final design as well as the experimental data results of the fabricated test rig. This test rig is beneficial for understanding the vibrational behavior of components especially in educational environment.

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Corrosion Fault Diagnosis of Rolling Element Bearing under Constant and Variable Load and Speed Conditions

Cited by 19 publications

References 16 publications

A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning

A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning

Modeling and Performance Analysis of BLDC Motor under Different Operating Speed Conditions

Design and development of a modular vibration test rig for combination types of fault in rotating machinery health diagnosis

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