Vector-based deterioration index for gas turbine gas-path prognostics modeling framework

Kiaee, Mehrdad; Tousi, Abolghasem M.

doi:10.1016/j.energy.2020.119198

Cited by 14 publications

(7 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, the analysis will be continued to find a probable pattern of parameters variation that make it possible to isolate and identify the MGT components degradations. Since examined degradation maybe happen and rise gradually during engine operation, 8,48,49 and MGT demand load usually varies during hours of a day and days of the year, 15,18,50 both degradation severity and load fraction of operating point are important in diagnostics process. So the effects of the examined degradations on the above four mentioned parameters are considered under different fault severities and shaft speeds.…”

Section: Monitoring Parameters Variation Patternmentioning

confidence: 99%

“…Accordingly, some specific study on the MGT components damage is necessary to understand degradation effects in the engine behavior. 12,13,18,20…”

Section: Introductionmentioning

confidence: 99%

“…8,14 Many studies investigate different aspects of the large gas turbine performance deterioration. However, the MGTs as a newer technology which has been commercialized since the early 2000s, 15,16 has a small portion of the studies in the area of degradations in the gas turbines, 17,18 and sufficient data is lacking about the performance deterioration of this engine type. 19 Moreover, the commercial MGT has some different features compared to the conventional large gas turbine, such as variable speed operating line and recuperative cycle.…”

Section: Introductionmentioning

confidence: 99%

“…Accordingly, some specific study on the MGT components damage is necessary to understand degradation effects in the engine behavior. 12,13,18,20 The investigation of Gomes et al 20 indicates that MGT shows higher sensitivity to component degradation. In Ref.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A methodology for identifying the most suitable measurements for engine level and component level gas path diagnostics of a micro gas turbine

Talebi

Tousi

Madadi

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

Recently, the utilization of micro gas turbines in smart grids are rising that makes the part-load operation principal situation of the engine service. This leads to faster life consumption that increases the importance of the diagnostics process. Gas path analysis is an effective method for gas turbine diagnostics. Complex dynamics of gas turbine induces challenging conditions to perform applicable gas path analysis. This study aims to facilitate MGT gas path diagnostics through reducing the number of monitoring parameters and preparation a pattern for engine level and component level health assessment in both full and part load operation of a recuperated micro gas turbine. To attain this goal a model is proposed to simulate MGT off-design performance which is validated against experimental data in healthy and degraded operation modes. Fouling in compressor, turbine and recuperator and erosion in compressor and turbine as the most common degradations in the gas turbine are considered. The fault simulation is performed by changing the health parameters of gas path components. According to the result investigation, a matrix comprises deviation contours of four parameters, Power, fuel flow, compressor discharge pressure, and exhaust gas temperature is presented and analyzed. The analysis shows that monitoring these parameters makes it possible to perform engine level and component level diagnostics through evaluating a binary code (generated by mentioned parameter variations) against the fault effects pattern in different load fractions and fault severities. The simulation also showed that the most power drop occurred under the compressor fouling by about 8.7% while the most reduction in thermal efficiency is observed under recuperator fouling by about 7.84%. Furthermore, the investigation showed the maximum decrease in the surge margin induced by the compressor fouling during the lower part-load operation by about 45.7% while in the higher loads created by the turbine fouling by about 14%.

show abstract

Section: Monitoring Parameters Variation Patternmentioning

confidence: 99%

“…Accordingly, some specific study on the MGT components damage is necessary to understand degradation effects in the engine behavior. 12,13,18,20…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A methodology for identifying the most suitable measurements for engine level and component level gas path diagnostics of a micro gas turbine

Talebi

Tousi

Madadi

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

show abstract

“…And Li et al [2] estimated the fatigue reliability of a turbine using collaborative multi-agent modeling, to improve the calculation precision and the efficiency of the simulation of fatigue reliability estimation for the turbine rotor, this modeling approach makes it possible to have high efficiency and high precision for estimating the fatigue reliability of the studied turbine rotor. Also, Kiaee and Tousi [3] determined the deterioration indices based on a modeling of the prognosis of the gas path of gas turbines, this study allows to improve knowledge on the monitoring of the state of the studied turbine with an increase of 3.29%, and the average remaining useful life of this turbine.…”

Section: Introductionmentioning

confidence: 99%

Reliability Modeling Using an Adaptive Neuro-Fuzzy Inference System: Gas Turbine Application

Hadroug

Hafaifa

Iratni

et al. 2021

Fuzzy Information and Engineering

View full text Add to dashboard Cite

Recently, the development of the industry requires monitoring and follow-up of the working conditions of the facilities, to determine the reliability, availability, and durability of these systems, for objectively estimating the service life of these installations with reduced maintenance costs. In this sense, this work proposes a novel approach to reliability modeling, to determine failure assessment indicators based on an adaptive neuro-fuzzy inference system applied on a gas turbine. This is in order to describe the behavior of this rotating machine and to estimate their operating safety parameters, to improve its performance in terms of maintainability, availability, and operational safety with effective durability. The application of fuzzy rules to reliability estimation with practical implementations is innovative, making it possible to provide solutions to problems of reliable identification of gas turbines in their complex operating environments.

show abstract

Johnson’s SU distribution using Gray Wolf Optimizer algorithm for fitting gas turbine reliability data

Charrak,

Djeddi,

Hafaifa

et al. 2024

Life Cycle Reliab Saf Eng

View full text Add to dashboard Cite

Vector-based deterioration index for gas turbine gas-path prognostics modeling framework

Cited by 14 publications

References 50 publications

A methodology for identifying the most suitable measurements for engine level and component level gas path diagnostics of a micro gas turbine

A methodology for identifying the most suitable measurements for engine level and component level gas path diagnostics of a micro gas turbine

Reliability Modeling Using an Adaptive Neuro-Fuzzy Inference System: Gas Turbine Application

Johnson’s SU distribution using Gray Wolf Optimizer algorithm for fitting gas turbine reliability data

Contact Info

Product

Resources

About