A gas path fault diagnostic model of gas turbines based on changes of blade profiles

Wei, Tingting; Huang, Dan; Li, Yuanfu; Zhang, Huisheng

doi:10.1016/j.engfailanal.2020.104377

Cited by 29 publications

(6 citation statements)

References 25 publications

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“…Co., Ltd., Hangzhou, China) with an accuracy rate of 0.02 mm was employed to capture the full-field geometric profiles and to generate the 3D point cloud model [24]. In addition, the geometric model of this blade was conducted in our previous work and is published in reference [25]. The collected point cloud data were reconstructed to generate a continuous smooth surface model.…”

Section: Reconstructed Geometric Model Of the Turbine Blade Based On ...mentioning

confidence: 99%

Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques

Xiao,

Chen,

Zhang

et al. 2023

Applied Sciences

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Turbine blades are crucial components exposed to harsh conditions, such as high temperatures, high pressures, and high rotational speeds. It is of great significance to accurately predict the life of blades for reducing maintenance cost and improving the reliability of gas turbine systems. A rapid and accurate blade life assessment method holds significant importance in the maintenance plan of gas turbine engines. In this paper, a novel on-line remaining useful life (RUL) prediction method for high-temperature blades is proposed based on 3D reconstruction technology and data-driven surrogate mode. Firstly, the 3D reconstruction technology was employed to establish the geometric model of real turbine blades, and the fluid–thermal–solid analysis under actual operational conditions was carried out in ANSYS software. Six checkpoints were selected to estimate the RUL according to the stress–strain distribution of the blade surface. The maximum equivalent stress was 1481.51 MPa and the highest temperature was 1393.42 K. Moreover, the fatigue-creep lifetime was calculated according to the parameters of the selected checkpoints. The RUL error between the simulation model and commercial software (Control and Engine Health Management (CEHM)) was less than 0.986%. Secondly, different data-driven surrogate models (BP, DNN, and LSTM algorithms) were developed according to the results from numerical simulation. The maximum relative errors of BP, DNN, and LSTM models were 0.030%, 0.019%, and 0.014%. LSTM demonstrated the best performance in predicting the RUL of turbine blades with time-series characteristics. Finally, the LSTM model was utilized for predicting the RUL within a gas turbine real operational process that involved five start–stop cycles.

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Section: Reconstructed Geometric Model Of the Turbine Blade Based On ...mentioning

confidence: 99%

Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques

Xiao,

Chen,

Zhang

et al. 2023

Applied Sciences

Self Cite

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“…In parallel, other research groups, turned their attention into transient engine performance instead of the steady state flow solution, which has traditionally been the gas path analysis theoretical basis. (Dengji Zhou et al, 2020) [6] intended to diagnose gas path faults by analysing how blade profile parameters are changing through time.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative Study of a Powerplant Life Consumption Rate When Installed in Two Different Aircraft Variants

Templalexis¹,

Lionis²,

Christou³

2021

Aerospace

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The Hellenic Air Force (HAF) operates both EMB-145 and EMB-135 LR versions of Embraer aircraft, used in surveillance and civil missions respectively. These aircraft are equipped with the same version of Rolls Royce, AE 3007 turbofan engine. This study aims to quantify and compare the life consumption rate of this engine when installed in each of the two aircraft variants. Two typical missions, one for each variant, were constructed based on mission profile data dictated by the aircraft commanders. For each mission profile segment, corresponding engine data were matched out of the engine recordings archives held by the Hellenic Air Force. The life consumption rate was based on the Low Cycle Fatigue (LCF) and creep cumulative detrimental effect on the rotor blades of the 1st High-Pressure Turbine stage. For the LCF, the rainflow method was used to determine the respective loading cycles, whereas the Larson - Miller parameter method was used to determine the consumed life fractions due to creep. The main conclusion of the study was that the engine when installed in the EMB-145 military variant, is much more loaded. Despite the fact absolute life consumption values could hide a great level of uncertainty, the comparative outcomes wherein errors are, to a certain extent, cancelled out, could be used as a rule of thumb when monitoring engine life consumption rates.

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“…Gas path analysis (GPA) method has been proved to be an efficient approach to diagnosing faults of gas turbine. [16][17][18] GPA method is based on the thermodynamic coupling relationship to obtain the component health parameter SF by the inverse calculation of gas path measurement parameter Z. This fault diagnosis method based on thermodynamic model has advantages of separating fault components and high precision, but it needs accurate model and may lead to inaccurate estimation if deviating from the design condition.…”

Section: Evaluation Indexmentioning

confidence: 99%

A novel integrated modeling approach for filter diagnosis in gas turbine air intake system

Jin

Liu

Tian

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part A:

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Due to the complex and harsh environmental factors, the useful life of the filter in the gas turbine air intake system is usually less than its design life. When the filter is seriously degraded, the power and thermal efficiency of the gas turbine will decrease obviously due to the increase of inlet pressure loss. For evaluating the health condition of filters in the air intake system, this work forms a filter pressure loss model with the defined health index for the filter and five external environmental and control factors. By integrating the gas path component model, the combined model is applied in a real data set and the results show that (i) the proposed health index is efficient in representing the degradation state of the filter, (ii) the influencing factors on the pressure loss are successfully decoupled and their contributions on the pressure are quantitatively estimated, and (iii) the integrated model of filter pressure loss and gas path component can be used to better estimate the deterioration states of the filter as well as the gas turbine performance.

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A gas path fault diagnostic model of gas turbines based on changes of blade profiles

Cited by 29 publications

References 25 publications

Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques

Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques

Comparative Study of a Powerplant Life Consumption Rate When Installed in Two Different Aircraft Variants

A novel integrated modeling approach for filter diagnosis in gas turbine air intake system

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