3D fluid–structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

Saeed, Rashid A.; Galybin, A.N.; Попов, В. В.

doi:10.1016/j.ymssp.2012.08.004

Cited by 49 publications

(25 citation statements)

References 35 publications

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“…A sajátfrekvenciák meghatározása csővezeték rendszerek vizsgálata esetén is sok esetben képezik a kiértékelés alapját [6][7][8][9]. Korábbi munkák folyadékszállító csővezetékeket vizsgáltak transzfer-mátrix módszerrel és meghatározták a rendszer saját frekvenciáit [10,11].…”

Section: Csövek Rezgésdiagnosztikai Vizsgálataunclassified

Csövek keresztmetszet-szűkülésének modellezése és rezgésdiagnosztikai vizsgálata

Kocsis¹,

Horvath²

2016

MTK

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In this work model experiments and vibration diagnostic tests were performed on stainless steel and PVC pipes. Reduction in inner diameter of pipes, as a characteristic failure (for example limescale deposition) was modeled in the introduced test series. To this end, the different phases of deposition are artificially simulated in the model experiments. Characterization of the degradation of the pipes was performed by vibration based measurements.

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Section: Csövek Rezgésdiagnosztikai Vizsgálataunclassified

Csövek keresztmetszet-szűkülésének modellezése és rezgésdiagnosztikai vizsgálata

Kocsis¹,

Horvath²

2016

MTK

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“…However, these two methods are just adjustments of outputs to reach a comprehensive result, and they can't act as structural damage feature extractors for identification usage. The principal component analysis (PCA) has been applied to extract features and reduce the dimensionality of the obtained Frequency Response Function (FRF) data (Saeed et al, 2013). Similar to PCA analysis, interval modeling technique is used in this paper as structural damage feature extractor.…”

Section: Integrated Approach Using Interval Modeling Techniquementioning

confidence: 99%

“…In most studies, WT was used as an effective signal analysis tool and brings damage-incurred singularities into prominence, addressing features of damage and enabling a solution to damage identification (Cao, Cheng, Su, & Xu, 2012). ANFIS can be fed into extracted features in order to identify the size and position of the damage and to estimate structural operating conditions (Saeed, Galybin, & Popov, 2013).…”

Section: Introductionmentioning

confidence: 99%

An integrated approach for structural damage identification using wavelet neuro-fuzzy model

Zhu

Deng

Zhang

2013

Expert Systems with Applications

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“…It has been shown that the combination of genetic algorithms with fuzzy inference systems possesses enormous advantages. Another integration of multi-intelligent techniques has also been carried out in recent years [15].…”

Section: Introductionmentioning

confidence: 99%

Crack Detection of Fan Blade Based on Natural Frequencies

Gao

et al. 2018

International Journal of Rotating Machinery

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A simple method was developed to detect damage based on a discrete mathematical model for fan blades using changes in natural frequencies combined with a fluid-structure analysis. In addition, a numerical approach was developed for the fluid-structure analysis. The results of numerical simulation provided the natural frequency data for each mode under different locations and sizes of a single crack in a blade. A fault database was built using Matlab. The damage of a blade was detected using the changes in natural frequencies. This study will assist in investigating the effect of a crack on a structure from different perspectives; the simulation results show the effectiveness of this approach.

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3D fluid–structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

Cited by 49 publications

References 35 publications

Csövek keresztmetszet-szűkülésének modellezése és rezgésdiagnosztikai vizsgálata

Csövek keresztmetszet-szűkülésének modellezése és rezgésdiagnosztikai vizsgálata

An integrated approach for structural damage identification using wavelet neuro-fuzzy model

Crack Detection of Fan Blade Based on Natural Frequencies

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