Fault Diagnosis of Bearing by Utilizing LWT‐SPSR‐SVD‐Based RVM with Binary Gravitational Search Algorithm

Fei, Sheng-wei

doi:10.1155/2018/8385021

Cited by 5 publications

(2 citation statements)

References 23 publications

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“…Glowacz [20] also analyzed acoustic-based fault diagnoses of commutator motors wherein acoustic signals were found to be in the range of 88.4-94.6%. Fei [21] performed a fault diagnosis method of bearing by utilizing lifting wavelet transform (LWT)-self-adaptive phase space reconstruction (SPSR)-singular value decomposition (SVD) based relevance vector machine (RVM) with the binary gravitational search algorithm. The results demonstrated that the method could achieve higher diagnostic accuracy for bearing.…”

Section: Introductionmentioning

confidence: 99%

Flow and Fast Fourier Transform Analyses for Tip Clearance Effect in an Operating Kaplan Turbine

et al. 2019

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The Kaplan turbine is an axial propeller-type turbine that can simultaneously control guide vanes and runner blades, thus allowing its application in a wide range of operations. Here, turbine tip clearance plays a crucial role in turbine design and operation as high tip clearance flow can lead to a change in the flow pattern, resulting in a loss of efficiency and finally the breakdown of hydro turbines. This research investigates tip clearance flow characteristics and undertakes a transient fast Fourier transform (FFT) analysis of a Kaplan turbine. In this study, the computational fluid dynamics method was used to investigate the Kaplan turbine performance with tip clearance gaps at different operating conditions. Numerical performance was verified with experimental results. In particular, a parametric study was carried out including the different geometrical parameters such as tip clearance between stationary and rotating chambers. In addition, an FFT analysis was performed by monitoring dynamic pressure fluctuation on the rotor. Here, increases in tip clearance were shown to occur with decreases in efficiency owing to unsteady flow. With this study’s focus on analyzing the flow of the tip clearance and its effect on turbine performance as well as hydraulic efficiency, it aims to improve the understanding on the flow field in a Kaplan turbine.

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Section: Introductionmentioning

confidence: 99%

Flow and Fast Fourier Transform Analyses for Tip Clearance Effect in an Operating Kaplan Turbine

et al. 2019

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“…Rolling bearing is one of the parts of rotating machinery, which are widely used and easily damaged in mechanical equipment [ 1 , 2 , 3 , 4 ]. The running state of rolling bearings will directly affect the production efficiency and safety of the equipment.…”

Section: Introductionmentioning

confidence: 99%

Optimized Adaptive Local Iterative Filtering Algorithm Based on Permutation Entropy for Rolling Bearing Fault Diagnosis

Zhang

2018

Entropy

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The characteristics of the early fault signal of the rolling bearing are weak and this leads to difficulties in feature extraction. In order to diagnose and identify the fault feature from the bearing vibration signal, an adaptive local iterative filter decomposition method based on permutation entropy is proposed in this paper. As a new time-frequency analysis method, the adaptive local iterative filtering overcomes two main problems of mode decomposition, comparing traditional methods: modal aliasing and the number of components is uncertain. However, there are still some problems in adaptive local iterative filtering, mainly the selection of threshold parameters and the number of components. In this paper, an improved adaptive local iterative filtering algorithm based on particle swarm optimization and permutation entropy is proposed. Firstly, particle swarm optimization is applied to select threshold parameters and the number of components in ALIF. Then, permutation entropy is used to evaluate the mode components we desire. In order to verify the effectiveness of the proposed method, the numerical simulation and experimental data of bearing failure are analyzed.

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Adapted Gravitational Search Algorithm Using Multiple Populations to Solve Exam Timetable Scheduling Problems

Wijaya¹,

Maedjaja²

2019

2019 International Congress on Applied Information Technology (AIT)

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Fault Diagnosis of Bearing by Utilizing LWT‐SPSR‐SVD‐Based RVM with Binary Gravitational Search Algorithm

Cited by 5 publications

References 23 publications

Flow and Fast Fourier Transform Analyses for Tip Clearance Effect in an Operating Kaplan Turbine

Flow and Fast Fourier Transform Analyses for Tip Clearance Effect in an Operating Kaplan Turbine

Optimized Adaptive Local Iterative Filtering Algorithm Based on Permutation Entropy for Rolling Bearing Fault Diagnosis

Adapted Gravitational Search Algorithm Using Multiple Populations to Solve Exam Timetable Scheduling Problems

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