Residual Life Prediction of Gas-Engine Turbine Blades Based on Damage Surrogate-Assisted Modeling

Vasilyev, Boris; Nikolaev, Sergei; Raevskiy, Mikhail; Belov, Sergei; Uzhinsky, Ighor

doi:10.3390/app10238541

Cited by 7 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Throughout the entire process, the stress and temperature of the turbine vanes varied continuously, while the selected transient points could only reflect the stress and temperature information at the current moment. To obtain the stress and temperature information of the turbine vane throughout the entire operation, this study employed the damage surrogate model proposed by Boris Vasilyev et al [22]. The model was trained using the power, rotational speed, fuel flow rate, and cross-sectional parameters of the gas turbine components at the selected 220 typical transient points as inputs and the stress and temperature information of critical points obtained from finite element calculations as outputs.…”

Section: Application To Components and Resultsmentioning

confidence: 99%

An Online Fatigue Damage Evaluation Method for Gas Turbine Hot Components

Zhu,

Dai,

Zhang

et al. 2023

Energies

View full text Add to dashboard Cite

The failure of gas turbines’ hot components due to fatigue significantly affects their efficient and stable operation. Conducting online damage assessment of components subjected to complex cyclic loads based on the working conditions of gas turbines can provide real-time reflection of component fatigue damage and achieve the purpose of predictive maintenance. In this study, we propose an online cycle counting method that considers temperature fluctuations during the cycle process. Our method is based on the four-point online rainflow counting method by coupling the counting variable with time, introducing the concept of the duration time for full cycles and half cycles, and incorporating a characteristic temperature that better represents the temperature information during the cycle process. With reference to the characteristic temperature, our proposed method comprehensively considers the form and parameters of subsequent life assessment models. This paper provides a detailed explanation of the proposed method and applies it to the fatigue damage assessment of turbine vanes in a micro gas turbine, thereby verifying its accuracy and applicability.

show abstract

Section: Application To Components and Resultsmentioning

confidence: 99%

An Online Fatigue Damage Evaluation Method for Gas Turbine Hot Components

Zhu,

Dai,

Zhang

et al. 2023

Energies

View full text Add to dashboard Cite

show abstract

“…Journal of Sensors multilevel model for an automotive braking system with 3-D finite element analysis, 0-D multidomain circuit simulation, and reduced-order modelling [30]. Vasilyev et al propose a coupling modelling method that can be efficiently utilised to estimate gas-turbine-engine blades' residual life with thermalsolid integrated analysis and ensemble machine learning [72]. Hybrid-method-based DT can swiftly calculate and predict the outcomes of multilevel or complex machines.…”

Section: Methods Type Methodsmentioning

confidence: 99%

“…On the other hand, it can acquire realtime load of components and calculate the accumulative damage based on digital twin. Upon getting the load, the RUL can be obtained by using a damage estimation model of the specific failure mode, such as accumulated wear of a braking system [30], fatigue crack length of aircraft wings [46], thermal mechanic fatigue of turbine blisks [73], and creep damage of turbine blades [72]. These methods are based on reduced order modelling to build a quick mapping model from performance monitoring parameters to thermal or structural loads of key components.…”

Section: (D) Rul Predictionmentioning

confidence: 99%

Digital Twin-Driven Machine Condition Monitoring: A Literature Review

et al. 2022

View full text Add to dashboard Cite

Digital twin (DT), aiming to characterise behaviors of physical entities by leveraging the virtual replica in real time, is an emerging technology and paradigm at the forefront of the Industry 4.0 revolution. The implementation of DT in predictive maintenance has facilitated its growth. As a major component of predictive maintenance, condition monitoring (CM) has great potential to combine with DT. To describe the state-of-the-art of DT-driven CM, this paper delivers a systematic review on the theoretical and practical development of DT in advancing CM. The evolution of concepts, main research areas, applied domains, and related key technologies are summarised. The driver of DT for CM is detailed in three aspects: data support, capability enhancement, and maintenance mode shift. The implementation process of DT-driven CM is introduced from the classification of DT modelling and the extension of monitoring algorithms. Finally, current challenges and opportunities for future research are discussed especially concerning the barriers and gaps in data management, high-fidelity modelling, behavior characterisation, framework standardisation, and uncertainty quantification.

show abstract

“…It is able to predict how long the blades will last, which helps O&M make decisions that try to prevent major failures. This was selected as a stand-in model and method for estimating a turbine blade's remaining life [5]. Throughout the course of the blades' lifespan, maintenance planning may be optimized by utilizing this model in conjunction with a predictive maintenance decision framework.…”

Section: Literature Reviewmentioning

confidence: 99%

Failure analysis of gas turbine in first stage turbine blades in an urban power plant

Hassan,

Sindi,

Mohamed

et al. 2024

J., eng., them. sci.

View full text Add to dashboard Cite

The Combined Cycle Power Plants (CCPP) are widely known as the most efficient power plants. The concept of CCPP represented in Brayton and Rankin cycles combined to achieve the highest efficiency in power generation. During the fact finding, while performing the major outage, at 77,521 running hours some of the turbine blades at 1st stage found suffering from severe damages and sulfuric acid thick layer accumulated in the cooling airfoils. The blades were new, also known as the most essential and costly component installed after Hot Gas Path Inspection (HGPI) at 42,000 running hours. The main objective of this work is to study the surrounding parameters that directly affect the lifetime of the turbine blades. Furthermore, XRD analysis for new and used turbine blades are studied as well as the EDS analysis for the coating layers which are used to enhance the surface life of gas turbine blades. Corrective maintenance, on the other hand, has been undertaken to overcome the performance deterioration caused by wear, which is the result of any machine or plant’s operation. A gas turbine cannot be run reliably unless wear reserves are checked and, if necessary, restored during inspections and maintenance operations. These are performed to determine the machine's condition and the necessary condition-based repairs. The principal types of gas turbine inspection have been investigated and presented, including minor inspection, hot gas inspection, extended-scope hot gas path examination, and major inspection. Lifetime extension (LTE) measures are derived from these inspection types and go beyond the scope of a major inspection. Nondestructive testing is performed on the gas turbine’s key components. Furthermore, due to the high degree of contamination in the fuel, the turbine section must be cleaned at regular intervals. As a result of the examinations, replacement, and refurbishment intervals for important components, as well as outage time, could be recommended.

show abstract

Residual Life Prediction of Gas-Engine Turbine Blades Based on Damage Surrogate-Assisted Modeling

Cited by 7 publications

References 17 publications

An Online Fatigue Damage Evaluation Method for Gas Turbine Hot Components

An Online Fatigue Damage Evaluation Method for Gas Turbine Hot Components

Digital Twin-Driven Machine Condition Monitoring: A Literature Review

Failure analysis of gas turbine in first stage turbine blades in an urban power plant

Contact Info

Product

Resources

About