Gas turbine gas path diagnostics: A review

Fentaye, Amare Desalegn; Gilani, Syed I.U.; Baheta, Aklilu Tesfamichael

doi:10.1051/matecconf/20167400005

Cited by 14 publications

(10 citation statements)

References 44 publications

(59 reference statements)

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“…Two of the well-known variants of this method are physics-based and data-driven GPA. Numerous comprehensive review articles explore existing GPA approaches (both physics-based and data-driven) and their relative performance [16][17][18][19][20]. In these articles, the comparative pros and cons of different approaches are examined based on attributes such as reliability, accuracy, model complexity, computational efficiency, the ability to cope with noise and bias, and number of measurements required for diagnostics.…”

Section: Review On Performance Based Gas Path Diagnosticsmentioning

confidence: 99%

Diagnostics-Oriented Modelling of Micro Gas Turbines for Fleet Monitoring and Maintenance Optimization

Rahman

Zaccaria²,

Zhao³

et al. 2018

Processes

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The market for the small-scale micro gas turbine is expected to grow rapidly in the coming years. Especially, utilization of commercial off-the-shelf components is rapidly reducing the cost of ownership and maintenance, which is paving the way for vast adoption of such units. However, to meet the high-reliability requirements of power generators, there is an acute need of a real-time monitoring system that will be able to detect faults and performance degradation, and thus allow preventive maintenance of these units to decrease downtime. In this paper, a micro gas turbine based combined heat and power system is modelled and used for development of physics-based diagnostic approaches. Different diagnostic schemes for performance monitoring of micro gas turbines are investigated.

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Section: Review On Performance Based Gas Path Diagnosticsmentioning

confidence: 99%

Diagnostics-Oriented Modelling of Micro Gas Turbines for Fleet Monitoring and Maintenance Optimization

Rahman

Zaccaria²,

Zhao³

et al. 2018

Processes

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“…While condition assessment is almost mandatory to tackle and treat important problems for all industrial equipment, this review is focused on industrial gas turbines (GTs). GTs are some of the most expensive devices in aircraft and industrial applications, where a huge amount of money is invested in operational and maintenance actions [7]. Hence, it is mandatory to have a good health management strategy in order to avoid economic, environmental, and security defects.…”

Section: Introductionmentioning

confidence: 99%

Machine-Learning-Based Condition Assessment of Gas Turbines—A Review

2021

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Condition monitoring, diagnostics, and prognostics are key factors in today’s competitive industrial sector. Equipment digitalisation has increased the amount of available data throughout the industrial process, and the development of new and more advanced techniques has significantly improved the performance of industrial machines. This publication focuses on surveying the last decade of evolution of condition monitoring, diagnostic, and prognostic techniques using machine-learning (ML)-based models for the improvement of the operational performance of gas turbines. A comprehensive review of the literature led to a performance assessment of ML models and their applications to gas turbines, as well as a discussion of the major challenges and opportunities for the research on these kind of engines. This paper further concludes that the combination of the available information captured through the collectors and the ML techniques shows promising results in increasing the accuracy, robustness, precision, and generalisation of industrial gas turbine equipment.

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“…However, these assumptions result in substantial inaccuracy in the process of degradation evaluation. 8,14…”

Section: Introductionmentioning

confidence: 99%

“…However, these assumptions result in substantial inaccuracy in the process of degradation evaluation. 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.…”

Section: Introductionmentioning

confidence: 99%

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:

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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%.

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Gas turbine gas path diagnostics: A review

Cited by 14 publications

References 44 publications

Diagnostics-Oriented Modelling of Micro Gas Turbines for Fleet Monitoring and Maintenance Optimization

Diagnostics-Oriented Modelling of Micro Gas Turbines for Fleet Monitoring and Maintenance Optimization

Machine-Learning-Based Condition Assessment of Gas Turbines—A Review

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

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