Fuzzy Diagnostic Strategy Implementation for Gas Turbine Vibrations Faults Detection: Towards a Characterization of Symptom–fault Correlations

Hadroug, Nadji; Hafaifa, Ahmed; Alili, Bachir; Iratni, Abdelhamid; Chen, Xiaoqi

doi:10.1007/s42417-021-00373-z

Cited by 21 publications

(10 citation statements)

References 47 publications

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“…Rauber_2021 [219] Samuel_2005 * [33] Vives_2020 [216] Random Forest Rauber_2021 [219] Li_2016b [249] Fuzzy predictive model Hadroug_2021 [250] Malla_2019 * [3] Str ączkiewicz_2015 [251] Saravanan_2009 [252] Da Silva_2017 [253] Sharma_2021 * [25] Decision Trees (DTs) Lipinski_2020 [254] Joshuva_2017a [112] Tabaszewski_2020 [255] Yang_2005 [256] Yang_2000 [257] Song_2018 [181] Dempster-Shafer (D-S) evidence theory Khazaee_2014 [258] Khazaee_2012 [259] Multi-Sensor Data fusion Safizadeh_2014 [260] Khazaee_2012 [259] Stief_2017 [261] Sharma_2021 * [25] Hybrid classifier based on SVM and ANN Sharma_2021 * [25] Hybrid classifier based on Principal Component Analysis (PCA) and ANN Liu_2008 [262] Devendiran_2015 [104] De Moura_2011 [263] Bendjama_2010 [264] Others Stefanoiu_2019 [265] Yan_2019 [199] Liu_2014 [266] Zhang_2021b [267] Avendaño-Valencia_2017 [268] Jayaswal and Wadhwani, in 2009 [31], reviewed the techniques successfully implemented for the automated fault diagnosis of bearings until that time, and refer to expert systems developed with multilayer perceptron (MLP), radial basis function (RBF) and probabilistic neural network (PNN). More recently, Tao et al, in 2019 [222], adopted a multilayer gated recurrent unit (MGRU) method for gear fault diagnosis; a comparison with long short-term memory (LSTM), multilayer LSTM (MLSTM), and support vector machine (SVM) LSTM, MLSTM, GRU, and SVM models, based on an experimental analysis, revealed improved accuracy with the MGRU network.…”

Section: Multiscale Convoluted Neural Network (Mscnn)mentioning

confidence: 99%

“…In the table, the nomenclature for categories and sub-categories of phases, components, and topics reflect the previously introduced legend. Bajaj_2022 [276] x p3 x Xu_2022 [277] x p4 x x Ye_2021a [244] x p3 x Ahmed_2021 [172] x x p2 x x Mufazzal_2021 [278] x p4 x Yang_2021 [110] x p2 x x x x x Moghadam_2021 [193] x p2 x x Saucedo-Dorantes_2021 [173] x p2 x x x x Espinoza-Sepulveda_2021 [279] x p4 x x Kalista_2021 [73] x p1 x x x Zhang_2021a [280] x p4 x x Zhang_2021b [267] x p3 x x Meng_2021 [59] x p1 x x Tiwari_2021 [95] x p1 x x Tatsis_2021 [281] x p4 x x Leaman_2021 [282] x p5 x x Ou_2021 [283] x p5 x x Espinoza_2021 [226] x x p3 x x Wang_2021 [233] x p3 x x x Goyal_2021 [60] x p1 x x Bai_2021a [203] x p2 x x x Yu_2021 [75] x p1 x x Papathanasopoulos_2021 [66] x p1 x x Sharma_2021 [25] x p1 x x x Rauber_2021 [219] x p3 x x Laval_2021 [76] x p1 x x x x Shao_2021 [158] x x p2 x x Rafiq_2021 [166] x p2 x x x x Zhao_2021 [77] x p1 x x Gómez_2021 [284] x p1 x x Jablon_2021 [197] x p2 x x Barusu_2021 [62] x p1 x x x x Hadroug_2021 [250] x p3 x Hou_2021 [35] x x p1 x x Yuan_2021 [285] x p5 x Ye_2021b [245] x p3 x x x Tingarikar_2021 [286] x p4 x Ribeiro_2021 [287] x p2 x Peng_2021 [288] x x p2 x x x Gu_2021 …”

Section: Appendix Amentioning

confidence: 99%

See 1 more Smart Citation

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

et al. 2022

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Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal functioning states are related to specific patterns that can be extracted from vibration signals. Extensively studied issues concern the different methodologies used for carrying out the main phases (signal measurements, pre-processing and processing, feature selection, and fault diagnosis) of a malfunction automatic diagnosis. In addition, vibration-based condition monitoring has been applied to a number of different mechanical systems or components. In this review, a systematic study of the works related to the topic was carried out. A preliminary phase involved the analysis of the publication distribution, to understand what was the interest in studying the application of the method to the various rotating machineries, to identify the interest in the investigation of the main phases of the diagnostic process, and to identify the techniques mainly used for each single phase of the process. Subsequently, the different techniques of signal processing, feature selection, and diagnosis are analyzed in detail, highlighting their effectiveness as a function of the investigated aspects and of the results obtained in the various studies. The most significant research trends, as well as the main innovations related to the various phases of vibration-based condition monitoring, emerge from the review, and the conclusions provide hints for future ideas.

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Section: Multiscale Convoluted Neural Network (Mscnn)mentioning

confidence: 99%

Section: Appendix Amentioning

confidence: 99%

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

et al. 2022

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“…An analysis of the diagnostic of effective power and efficiency of the GTU was proposed in [7][8][9]. In recent years, the usage of computer neural networks has been growing for parametric analysis of the technical systems state [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive Acoustic Monitoring of Gas Turbine Units by Fiber Optic Sensors

Stepanov

Zhirnov

Sazonkin

et al. 2022

Sensors

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In this article, we study the possibility of gas turbine unit (GTU) monitoring using interferometric fiber optic sensors. We used the Mach–Zehnder interferometer (MZI) scheme, which can be easily implemented and simply installed on the turbine, and also allows us to solve the problem of phase unwrapping conveniently. In this research, the following main steps were carried out: an experimental scheme based on the MZI was assembled, and its sensitive arm was fixed on the GTU under study; data on various operation modes of the GTU was collected; the data were subjected to frequency FFT analysis, based on which the main rotational speeds of the turbine were identified. With FFT analysis, we also demonstrated multiples harmonics, which appear in the case of GTU after operating time, caused by the number of blades. The possibility of GTU monitoring and analysis using a non-invasive compact fiber-optic sensor is demonstrated: spectral analysis is used to detect the rotor speed, as well as the presence or absence of high-order multiple frequencies indicating blade and bearing defects, which are determined by the number of GTU’s blades and rolling bearing used as turbines rotor supports.

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“…or precision instruments (optical interferometers, space telescopes, etc.) with complex vibration isolation systems [19][20][21][22][23][24][25], a single-stage vibration isolation system often leads to resonant peaks and standing wave effects at high frequencies [26][27][28][29], which cannot meet the vibration isolation requirements. A dual-stage vibration isolation system draws great interest owing to its better high-frequency effect and higher stability [30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Performance and Optimization of a Dual-Stage Vibration Isolation System Using Bio-Inspired Vibration Isolators

Huang

Shi²,

Dong³

et al. 2022

Applied Sciences

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This paper thoroughly investigates the performance and multi-parameter optimization of a dual-stage vibration isolation system with bio-inspired isolators (BI-DSVI) under different base excitations. The dynamic equations of the BI-DSVI are derived. Then, the optimization problem is defined, where three types of base excitation (translation and rotations around the two horizontal axes) are studied. The optimization results show that the vibration transmissibility can be greatly reduced (more than 30 dB) by multi-parameter optimization, and an optimal configuration of structural parameters exists for the bio-inspired isolators. The effective vibration isolation bandwidth is significantly widened. Finally, the paper thoroughly discusses the influence of the structural parameters of the bio-inspired isolators and the base excitation types on the vibration isolation performance. The parameter studies provide useful guidelines for the application of the bio-inspired isolator in dual-stage vibration isolation.

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Fuzzy Diagnostic Strategy Implementation for Gas Turbine Vibrations Faults Detection: Towards a Characterization of Symptom–fault Correlations

Cited by 21 publications

References 47 publications

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

Non-Invasive Acoustic Monitoring of Gas Turbine Units by Fiber Optic Sensors

Performance and Optimization of a Dual-Stage Vibration Isolation System Using Bio-Inspired Vibration Isolators

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