scholarly journals Data-Driven Models for Gas Turbine Online Diagnosis

Machines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 372
Author(s):  
Iván González Castillo ◽  
Igor Loboda ◽  
Juan Luis Pérez Ruiz
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Data Driven ◽  
Approximation Technique ◽  
Adequate Model ◽  
Simulation Tools ◽  
Turbofan Engines ◽  
The Best Approximation ◽  
Fault Parameters

The lack of gas turbine field data, especially faulty engine data, and the complexity of fault embedding into gas turbines on test benches cause difficulties in representing healthy and faulty engines in diagnostic algorithms. Instead, different gas turbine models are often used. The available models fall into two main categories: physics-based and data-driven. Given the models’ importance and necessity, a variety of simulation tools were developed with different levels of complexity, fidelity, accuracy, and computer performance requirements. Physics-based models constitute a diagnostic approach known as Gas Path Analysis (GPA). To compute fault parameters within GPA, this paper proposes to employ a nonlinear data-driven model and the theory of inverse problems. This will drastically simplify gas turbine diagnosis. To choose the best approximation technique of such a novel model, the paper employs polynomials and neural networks. The necessary data were generated in the GasTurb software for turboshaft and turbofan engines. These input data for creating a nonlinear data-driven model of fault parameters cover a total range of operating conditions and of possible performance losses of engine components. Multiple configurations of a multilayer perceptron network and polynomials are evaluated to find the best data-driven model configurations. The best perceptron-based and polynomial models are then compared. The accuracy achieved by the most adequate model variation confirms the viability of simple and accurate models for estimating gas turbine health conditions.

scholarly journals A Comparative Study on Fault Detection Methods for Gas Turbine Combustion Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 389
Author(s):  
Jinfu Liu ◽  
Zhenhua Long ◽  
Mingliang Bai ◽  
Linhai Zhu ◽  
Daren Yu
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Detection Methods ◽  
Distribution Model ◽  
Outlet Temperature ◽  
Combustion System ◽  
Comparison Results ◽  
Gas Turbine Combustion

As one of the core components of gas turbines, the combustion system operates in a high-temperature and high-pressure adverse environment, which makes it extremely prone to faults and catastrophic accidents. Therefore, it is necessary to monitor the combustion system to detect in a timely way whether its performance has deteriorated, to improve the safety and economy of gas turbine operation. However, the combustor outlet temperature is so high that conventional sensors cannot work in such a harsh environment for a long time. In practical application, temperature thermocouples distributed at the turbine outlet are used to monitor the exhaust gas temperature (EGT) to indirectly monitor the performance of the combustion system, but, the EGT is not only affected by faults but also influenced by many interference factors, such as ambient conditions, operating conditions, rotation and mixing of uneven hot gas, performance degradation of compressor, etc., which will reduce the sensitivity and reliability of fault detection. For this reason, many scholars have devoted themselves to the research of combustion system fault detection and proposed many excellent methods. However, few studies have compared these methods. This paper will introduce the main methods of combustion system fault detection and select current mainstream methods for analysis. And a circumferential temperature distribution model of gas turbine is established to simulate the EGT profile when a fault is coupled with interference factors, then use the simulation data to compare the detection results of selected methods. Besides, the comparison results are verified by the actual operation data of a gas turbine. Finally, through comparative research and mechanism analysis, the study points out a more suitable method for gas turbine combustion system fault detection and proposes possible development directions.

Combustion Tuning for a Gas Turbine Power Plant Using Data-Driven and Machine Learning Approach

2021 ◽  
Vol 143 (3) ◽  
Author(s):  
Suhui Li ◽  
Huaxin Zhu ◽  
Min Zhu ◽  
Gang Zhao ◽  
Xiaofeng Wei
Keyword(s):  
Machine Learning ◽  
Power Plant ◽  
Gas Turbine ◽  
Operating Conditions ◽  
Data Driven ◽  
Ann Model ◽  
Promising Alternative ◽  
Combustion Performance ◽  
Wide Range ◽  
Gas Turbine Power Plant

Abstract Conventional physics-based or experimental-based approaches for gas turbine combustion tuning are time consuming and cost intensive. Recent advances in data analytics provide an alternative method. In this paper, we present a cross-disciplinary study on the combustion tuning of an F-class gas turbine that combines machine learning with physics understanding. An artificial-neural-network-based (ANN) model is developed to predict the combustion performance (outputs), including NOx emissions, combustion dynamics, combustor vibrational acceleration, and turbine exhaust temperature. The inputs of the ANN model are identified by analyzing the key operating variables that impact the combustion performance, such as the pilot and the premixed fuel flow, and the inlet guide vane angle. The ANN model is trained by field data from an F-class gas turbine power plant. The trained model is able to describe the combustion performance at an acceptable accuracy in a wide range of operating conditions. In combination with the genetic algorithm, the model is applied to optimize the combustion performance of the gas turbine. Results demonstrate that the data-driven method offers a promising alternative for combustion tuning at a low cost and fast turn-around.

AI Assisted High Fidelity Multi-Physics Digital Twin of Industrial Gas Turbines

2021 ◽  
Author(s):  
Senthil Krishnababu ◽  
Omar Valero ◽  
Roger Wells
Keyword(s):  
Gas Turbine ◽  
Data Storage ◽  
Gas Turbines ◽  
Building Blocks ◽  
Data Driven ◽  
High Fidelity ◽  
Test Field ◽  
Operating Characteristics ◽  
Digital Twin ◽  
The Impact

Abstract Data driven technologies are revolutionising the engineering sector by providing new ways of performing day to day tasks through the life cycle of a product as it progresses through manufacture, to build, qualification test, field operation and maintenance. Significant increase in data transfer speeds combined with cost effective data storage, and ever-increasing computational power provide the building blocks that enable companies to adopt data driven technologies such as data analytics, IOT and machine learning. Improved business operational efficiency and more responsive customer support provide the incentives for business investment. Digital twins, that leverages these technologies in their various forms to converge physics and data driven models, are therefore being widely adopted. A high-fidelity multi-physics digital twin, HFDT, that digitally replicates a gas turbine as it is built based on part and build data using advanced component and assembly models is introduced. The HFDT, among other benefits enables data driven assessments to be carried out during manufacture and assembly for each turbine allowing these processes to be optimised and the impact of variability or process change to be readily evaluated. On delivery of the turbine and its associated HFDT to the service support team the HFDT supports the evaluation of in-service performance deteriorations, the impact of field interventions and repair and the changes in operating characteristics resulting from overhaul and turbine upgrade. Thus, creating a cradle to grave physics and data driven twin of the gas turbine asset. In this paper, one branch of HFDT using a power turbine module is firstly presented. This involves simultaneous modelling of gas path and solid using high fidelity CFD and FEA which converts the cold geometry to hot running conditions to assess the impact of various manufacturing and build variabilities. It is shown this process can be executed within reasonable time frames enabling creation of HFDT for each turbine during manufacture and assembly and for this to be transferred to the service team for deployment during field operations. Following this, it is shown how data driven technologies are used in conjunction with the HFDT to improve predictions of engine performance from early build information. The example shown, shows how a higher degree of confidence is achieved through the development of an artificial neural network of the compressor tip gap feature and its effect on overall compressor efficiency.

Marine Gas Turbine Performance Model for More Electric Ships

2011 ◽  
Author(s):  
George M. Koutsothanasis ◽  
Anestis I. Kalfas ◽  
Georgios Doulgeris
Keyword(s):  
Gas Turbine ◽  
Fuel Consumption ◽  
Diesel Engines ◽  
Gas Turbines ◽  
Electric Propulsion ◽  
Operating Conditions ◽  
Prime Mover ◽  
Creep Life ◽  
Hull Fouling ◽  
Turbine Performance

This paper presents the benefits of the more electric vessels powered by hybrid engines and investigates the suitability of a particular prime-mover for a specific ship type using a simulation environment which can approach the actual operating conditions. The performance of a mega yacht (70m), powered by two 4.5MW recuperated gas turbines is examined in different voyage scenarios. The analysis is accomplished for a variety of weather and hull fouling conditions using a marine gas turbine performance software which is constituted by six modules based on analytical methods. In the present study, the marine simulation model is used to predict the fuel consumption and emission levels for various conditions of sea state, ambient and sea temperatures and hull fouling profiles. In addition, using the aforementioned parameters, the variation of engine and propeller efficiency can be estimated. Finally, the software is coupled to a creep life prediction tool, able to calculate the consumption of creep life of the high pressure turbine blading for the predefined missions. The results of the performance analysis show that a mega yacht powered by gas turbines can have comparable fuel consumption with the same vessel powered by high speed Diesel engines in the range of 10MW. In such Integrated Full Electric Propulsion (IFEP) environment the gas turbine provides a comprehensive candidate as a prime mover, mainly due to its compactness being highly valued in such application and its eco-friendly operation. The simulation of different voyage cases shows that cleaning the hull of the vessel, the fuel consumption reduces up to 16%. The benefit of the clean hull becomes even greater when adverse weather condition is considered. Additionally, the specific mega yacht when powered by two 4.2MW Diesel engines has a cruising speed of 15 knots with an average fuel consumption of 10.5 [tonne/day]. The same ship powered by two 4.5MW gas turbines has a cruising speed of 22 knots which means that a journey can be completed 31.8% faster, which reduces impressively the total steaming time. However the gas turbine powered yacht consumes 9 [tonne/day] more fuel. Considering the above, Gas Turbine looks to be the only solution which fulfills the next generation sophisticated high powered ship engine requirements.

scholarly journals A Different Approach to Gas Turbine Exhaust Silencing

1974 ◽  
Author(s):  
Marv Weiss
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Heavy Duty ◽  
Unique Method ◽  
Acoustic Testing ◽  
Gas Turbine Exhaust ◽  
Attenuation Values ◽  
Turbine Exhaust

A unique method for silencing heavy-duty gas turbines is described. The Switchback exhaust silencer which utilizes no conventional parallel baffles has at operating conditions measured attenuation values from 20 dB at 63 Hz to 45 dB at higher frequencies. Acoustic testing and analyses at both ambient and operating conditions are discussed.

Advancement in Heated Spin Testing Technologies

2013 ◽  
Author(s):  
Hiroaki Endo ◽  
Robert Wetherbee ◽  
Nikhil Kaushal
Keyword(s):  
High Temperature ◽  
Gas Turbine ◽  
Material Properties ◽  
Gas Turbines ◽  
Multiple Scales ◽  
Thermal Conditions ◽  
Complex Stress ◽  
Operating Conditions ◽  
Mechanical Cycling ◽  
Testing Techniques

An ever more rapidly accelerating trend toward pursuing more efficient gas turbines pushes the engines to hotter and more arduous operating conditions. This trend drives the need for new materials, coatings and associated modeling and testing techniques required to evaluate new component design in high temperature environments and complex stress conditions. This paper will present the recent advances in spin testing techniques that are capable of creating complex stress and thermal conditions, which more closely represent “engine like” conditions. The data from the tests will also become essential references that support the effort in Integrated Computational Materials Engineering (ICME) and in the advances in rotor design and lifing analysis models. Future innovation in aerospace products is critically depended on simultaneous engineering of material properties, product design, and manufacturing processes. ICME is an emerging discipline with an approach to design products, the materials that comprise them, and their associated materials processing methods by linking materials models at multiple scales (Structural, Macro, Meso, Micro, Nano, etc). The focus of the ICME is on the materials; understanding how processes produce material structures, how those structures give rise to material properties, and how to select and/or engineer materials for a given application [34]. The use of advanced high temperature spin testing technologies, including thermal gradient and thermo-mechanical cycling capabilities, combined with the innovative use of modern sensors and instrumentation methods, enables the examination of gas turbine discs and blades under the thermal and the mechanical loads that are more relevant to the conditions of the problematic damages occurring in modern gas turbine engines.

Experience With Large Heavy-Duty Gas Turbine Rotors

1981 ◽  
Author(s):  
O. R. Schmoch ◽  
B. Deblon
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Turbine Rotor ◽  
Strength Properties ◽  
Operating Conditions ◽  
Material Strength ◽  
Heavy Duty ◽  
Turbine Rotors ◽  
Heavy Duty Gas Turbine ◽  
Response To Temperature

The peripheral speeds of the rotors of large heavy-duty gas turbines have reached levels which place extremely high demands on material strength properties. The particular requirements of gas turbine rotors, as a result of the cycle, operating conditions and the ensuing overall concepts, have led different gas turbine manufacturers to produce special structural designs to resolve these problems. In this connection, a report is given here on a gas turbine rotor consisting of separate discs which are held together by a center bolt and mutually centered by radial serrations in a manner permitting expansion and contraction in response to temperature changges. In particular, the experience gained in the manufacture, operation and servicing are discussed.

Experimental and numerical study of flame structure and emissions in a micro gas turbine combustor

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Vedant Dwivedi ◽  
Srikanth Hari ◽  
S. M. Kumaran ◽  
B. V. S. S. S. Prasad ◽  
Vasudevan Raghavan
Keyword(s):  
Gas Turbine ◽  
Rural Areas ◽  
Gas Turbines ◽  
Alternative Fuels ◽  
Numerical Study ◽  
Operating Conditions ◽  
Emission Characteristics ◽  
Nitric Oxides ◽  
Gas Turbine Combustor ◽  
Micro Gas Turbine

Abstract Experimental and numerical study of flame and emission characteristics in a tubular micro gas turbine combustor is reported. Micro gas turbines are used for distributed power (DP) generation using alternative fuels in rural areas. The combustion and emission characteristics from the combustor have to be studied for proper design using different fuel types. In this study methane, representing fossil natural gas, and biogas, a renewable fuel that is a mixture of methane and carbon-dioxide, are used. Primary air flow (with swirl component) and secondary aeration have been varied. Experiments have been conducted to measure the exit temperatures. Turbulent reactive flow model is used to simulate the methane and biogas flames. Numerical results are validated against the experimental data. Parametric studies to reveal the effects of primary flow, secondary flow and swirl have been conducted and results are systematically presented. An analysis of nitric-oxides emission for different fuels and operating conditions has been presented subsequently.

Uncertainty Analysis of Inflow Conditions on an HPT Gas Turbine Nozzle: Effect on Particle Deposition

2020 ◽  
Author(s):  
R. Friso ◽  
N. Casari ◽  
M. Pinelli ◽  
A. Suman ◽  
F. Montomoli
Keyword(s):  
Gas Turbine ◽  
Energy Efficient ◽  
Gas Turbines ◽  
Particle Deposition ◽  
Operating Conditions ◽  
Wide Range ◽  
And Performance ◽  
Gas Turbine Nozzle ◽  
The Impact ◽  
Inflow Conditions

Abstract Gas turbines (GT) are often forced to operate in harsh environmental conditions. Therefore, the presence of particles in their flow-path is expected. With this regard, deposition is a problem that severely affects gas turbine operation. Components’ lifetime and performance can dramatically vary as a consequence of this phenomenon. Unfortunately, the operating conditions of the machine can vary in a wide range, and they cannot be treated as deterministic. Their stochastic variations greatly affect the forecasting of life and performance of the components. In this work, the main parameters considered affected by the uncertainty are the circumferential hot core location and the turbulence level at the inlet of the domain. A stochastic analysis is used to predict the degradation of a high-pressure-turbine (HPT) nozzle due to particulate ingestion. The GT’s component analyzed as a reference is the HPT nozzle of the Energy-Efficient Engine (E3). The uncertainty quantification technique used is the probabilistic collocation method (PCM). This work shows the impact of the operating conditions uncertainties on the performance and lifetime reduction due to deposition. Sobol indices are used to identify the most important parameter and its contribution to life. The present analysis enables to build confidence intervals on the deposit profile and on the residual creep-life of the vane.

Principles of Imitation for the Loading of the Test Bench for Gas Turbines of Gas Pumping Units, Adequate to Real Conditions

2021 ◽  
Vol 13 (24) ◽  
pp. 13678
Author(s):  
Anton Petrochenkov ◽  
Aleksandr Romodin ◽  
Vladimir Kazantsev ◽  
Aleksey Sal’nikov ◽  
Sergey Bochkarev ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Power Plants ◽  
Simulation Models ◽  
Turbine Rotor ◽  
Operating Conditions ◽  
Automation System ◽  
Model Free ◽  
Gas Pumping ◽  
Pumping Units

The purpose of the study is to analyze the prospects for the development of loading methods for gas turbines as well as to develop a mathematical model that adequately describes the real operating conditions of the loading system at various loads and rotation speeds. A comparative analysis of the most common methods and technical means of loading the shafts of a free turbine at gas turbine plants intended for operation as part of gas pumping units is presented. Based on the results of the analysis, the expediency of using the loading model “Free Power Turbine Rotor–Hydraulic Brake” as a load simulation is shown. Recommendations for the creation of an automation system for the load testing of power plants have been developed. Mathematical models and Hardware-in-the-Loop simulation models of power plants have been developed and tested. One of the most important factors that predetermine the effectiveness of the loading principle is the possibility of software implementation of the loading means using software control systems that provide the specified loading parameters of the gas turbine.

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