Real Time Prognostic Strategies: Application to Gas Turbines

2011 ◽  
Vol 312-315 ◽  
pp. 601-606
Author(s):  
M. Yadegari
Keyword(s):  
Real Time ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Health Management ◽  
System Behavior ◽  
Industrial Sectors ◽  
Healthy Working ◽  
The World ◽  
Short And Long Term

Gas turbines are increasingly deployed throughout the world to provide electrical and mechanical power in consumer and industrial sectors. A health management system can incorporate prognostic algorithms to effectively interpret and determine the healthy working span of a gas turbine. The research project’s objective is to develop real-time monitoring and prediction algorithms for simple cycle natural gas turbines to forecast short and long term system behavior.

Real Time Prognostic Strategies With Application to Stationary Gas Turbines

2006 ◽  
Author(s):  
Rajat Sekhon ◽  
Hany Bassily ◽  
John Wagner
Keyword(s):  
Real Time ◽  
Gas Turbines ◽  
Health Management ◽  
Sensory Information ◽  
Prognostic Information ◽  
Maintenance Schedule ◽  
Plant Behavior ◽  
Industrial Sectors ◽  
Parallel Fashion ◽  
Transient And Steady State

Stationary gas turbines are increasingly deployed throughout the world to provide electrical and mechanical power in consumer and industrial sectors. The efficiency of these complex multi-domain systems is dependent on the turbine's design, established operating envelope, environmental conditions, and maintenance schedule. A real time health management strategy can enhance overall plant reliability through the continual monitoring of transient and steady-state system operations. The availability of sensory information for control system needs often allow diagnostic/prognostic algorithms to be executed in a parallel fashion which warn of impending system degradations. Specifically, prognostic strategies estimate the future plant behavior which leads to minimized maintenance costs through timely repairs, and hence, improved reliability. In this paper, statistical and wavelet prognostic methods are presented to forecast system health. For the statistical approach, a multi-dimensional empirical description reveals dominant data trends and estimates future behavior. The wavelet approach uses second order Daubechies wavelet coefficients to generate signal approximations that forecast future plant operation. Experimental data has been collected on a Solar Mercury 50 stationary gas turbine. The monitored plant signals were analyzed to identify prognostic information for preventative action recommendations. Representative results are presented and discussed to compare the overall performance of each prognostic algorithm.

Dynamic Gas Turbine Condition Monitoring Scheme With Multi-Part Neural Network

2020 ◽  
Author(s):  
Zhouzheng Li ◽  
Kun Feng ◽  
Binbin Yan
Keyword(s):  
Neural Network ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Health Management ◽  
Fault Analysis ◽  
Performance Data ◽  
Sensor Data ◽  
Integrated Network ◽  
The Neural Network

Abstract Gas turbines are high value industrial assets with significant roles in various kinds of industrial processes, health management systems are therefore important for helping maintaining gas turbines’ stability in long-term operations. With more and more performance data able to be collected by sensors and the new machine learning methods developed, researchers are able to build more powerful digital models to monitor the gas turbine. This paper introduces a performance parameters alarm scheme for gas turbine using an adaptive state following model. The proposed scheme consist of 3 parts: Part 1, a dynamically adaptive multi-part neural network trained using performance data that can simulate different parts of gas turbine and output “normal” sensor data to make comparison with the actual data collected; Part 2, a group of thresholds set according to system noise that flags sudden failures by sensing performance parameter outliers, this also decides which data should be used to update the neural network; Part 3, a recorder for “reference point” outputs that can reflect change of the gas turbine’s status and detect long-term degradation. Unlike traditional approaches, the proposed adaptive states following model separates long term degradation and short term sudden failure, therefore both faults can be detected more accurately. The core of the proposed method is that physical properties are embedded into the neural network as constraints to regulate training and make the model more interpretable. In our scheme, a gas turbine is divided into 4 parts referencing the equipment’s physical mechanism, they are simulated digitally by 4 sub corresponding networks, which are then combined into the proposed integrated network. The proposed scheme achieves an overall pleasing result and shows potential in gas turbine fault analysis.

Issues and Challenges of Asian Development

Worldview ◽  
1975 ◽  
Vol 18 (7-8) ◽  
pp. 36-39
Author(s):  
Saburo Okita
Keyword(s):  
Growth Opportunities ◽  
Asian Development ◽  
Good Shape ◽  
Monetary System ◽  
The Social ◽  
The World ◽  
Short And Long Term ◽  
Oil Crisis ◽  
Complicated Nature

The economy of Southeast Asia has been in relatively good shape in spite of the instability of the world monetary system, trade deficits, and the worldwide oil crisis. There are promising factors for economic growth, opportunities for employment, and possibilities of rising income. But Asian development presents short-and long-term problems of a very complicated nature. One of the most serious problems is inflation and its impact on the social and political programs of individual countries. At the same time, there are severe shortages of basic commodities, such as oil and food. My own country, Japan, is among those affected.

Editorial

2009 ◽  
Vol 11 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Manasi Kumar ◽  
Erica Burman
Keyword(s):  
Millennium Development Goals ◽  
Health Management ◽  
The Political ◽  
Special Issue ◽  
Wide Range ◽  
Critical Approaches ◽  
Development Goals ◽  
Short And Long Term ◽  
Primary Focus

We welcome readers to the first special issue (11.1) of the Journal of Health Management. We hope the readers find the articles and various reviews enriching and provocative, both in terms of the range of ideas and critical approaches addressed. The key theme of this double issue concerns the political limits of mega-development projects such as the Millennium Development Goals (MDGs). The primary focus of the articles collected here is to provide an insightful, constructive and in-depth critique of the United Nations (UN) MDGs along with critical deliberations on their short- and long-term implications not only for health management but also for a wide range of issues around development and social change.

scholarly journals Inlet Air Fogging of Marine Gas Turbine in Power Output Loss Compensation

2015 ◽  
Vol 22 (4) ◽  
pp. 53-58 ◽  
Author(s):  
Zygfryd Domachowski ◽  
Marek Dzida
Keyword(s):  
Gas Turbine ◽  
Power Output ◽  
Gas Turbines ◽  
Evaporative Cooling ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Output Loss ◽  
Direct Evaporative Cooling ◽  
Loss Compensation ◽  
The World

Abstract The use of inlet air fogging installation to boost the power for gas turbine engines is widely applied in the power generation sector. The application of fogging to mechanical drive is rarely considered in literature [1]. This paper will cover some considerations relating to its application for gas turbines in ship drive. There is an important evaporative cooling potential throughout the world, when the dynamic data is evaluated, based on an analysis of coincident wet and dry bulb information. This data will allow ships’ gas turbine operators to make an assessment of the economics of evaporative fogging. The paper represents an introduction to the methodology and data analysis to derive the direct evaporative cooling potential to be used in marine gas turbine power output loss compensation.

A Modular Code for Real Time Dynamic Simulation of Gas Turbines in Simulink

2002 ◽  
Vol 128 (3) ◽  
pp. 506-517 ◽  
Author(s):  
S. M. Camporeale ◽  
B. Fortunato ◽  
M. Mastrovito
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Gas Turbine ◽  
Dynamic Behavior ◽  
Gas Turbines ◽  
Simulation Software ◽  
Computational Time ◽  
High Fidelity ◽  
Time Step ◽  
The Mathematical Model

A high-fidelity real-time simulation code based on a lumped, nonlinear representation of gas turbine components is presented. The code is a general-purpose simulation software environment useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of gas turbine engines. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft aero-derivative industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

scholarly journals Influences on Attitudes Regarding Potential COVID-19 Vaccination in the United States

Vaccines ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 582 ◽  
Author(s):  
Kendall Pogue ◽  
Jamie L. Jensen ◽  
Carter K. Stancil ◽  
Daniel G. Ferguson ◽  
Savannah J. Hughes ◽  
...  
Keyword(s):  
United States ◽  
Structural Equation Modeling ◽  
Side Effects ◽  
Structural Equation ◽  
The United States ◽  
Equation Modeling ◽  
Vaccine Acceptance ◽  
The World ◽  
Short And Long Term

The COVID-19 pandemic continues to ravage the world, with the United States being highly affected. A vaccine provides the best hope for a permanent solution to controlling the pandemic. However, to be effective, a vaccine must be accepted and used by a large majority of the population. The aim of this study was to understand the attitudes towards and obstacles facing vaccination with a potential COVID-19 vaccine. To measure these attitudes a survey was administered to 316 respondents across the United States by a survey corporation. Structural equation modeling was used to analyze the relationships of several factors with attitudes toward potential COVID-19 vaccination. Prior vaccine usage and attitudes predicted attitudes towards COVID-19 vaccination. Assessment of the severity of COVID-19 for the United States was also predictive. Approximately 68% of all respondents were supportive of being vaccinated for COVID-19, but side effects, efficacy and length of testing remained concerns. Longer testing, increased efficacy and development in the United States were significantly associated with increased vaccine acceptance. Messages promoting COVID-19 vaccination should seek to alleviate the concerns of those who are already vaccine-hesitant. Messaging directed at the benefits of vaccination for the United States as a country would address the second predictive factor. Enough time should be taken to allay concerns about both short- and long-term side effects before a vaccine is released.

scholarly journals A Real-Time Degradation Model for Hardware in the Loop Simulation of Fuel Cell Gas Turbine Hybrid Systems

2015 ◽  
Author(s):  
Valentina Zaccaria ◽  
Alberto Traverso ◽  
David Tucker
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Gas Turbine ◽  
Hybrid Systems ◽  
Current Density ◽  
Gas Turbines ◽  
Hardware In The Loop ◽  
Fuel Utilization ◽  
Time Operation ◽  
The Impact

The theoretical efficiencies of gas turbine fuel cell hybrid systems make them an ideal technology for the future. Hybrid systems focus on maximizing the utilization of existing energy technologies by combining them. However, one pervasive limitation that prevents the commercialization of such systems is the relatively short lifetime of fuel cells, which is due in part to several degradation mechanisms. In order to improve the lifetime of hybrid systems and to examine long-term stability, a study was conducted to analyze the effects of electrochemical degradation in a solid oxide fuel cell (SOFC) model. The SOFC model was developed for hardware-in-the-loop simulation with the constraint of real-time operation for coupling with turbomachinery and other system components. To minimize the computational burden, algebraic functions were fit to empirical relationships between degradation and key process variables: current density, fuel utilization, and temperature. Previous simulations showed that the coupling of gas turbines and SOFCs could reduce the impact of degradation as a result of lower fuel utilization and more flexible current demands. To improve the analytical capability of the model, degradation was incorporated on a distributed basis to identify localized effects and more accurately assess potential failure mechanisms. For syngas fueled systems, the results showed that current density shifted to underutilized sections of the fuel cell as degradation progressed. Over-all, the time to failure was increased, but the temperature difference along cell was increased to unacceptable levels, which could not be determined from the previous approach.

Research and Development of Practical Industrial Cogeneration Technology in Japan

2000 ◽  
Author(s):  
Toshiaki Abe ◽  
Takashi Sugiura ◽  
Shuji Okunaga ◽  
Katsuhiro Nojima ◽  
Yasukata Tsutsui ◽  
...  
Keyword(s):  
Research And Development ◽  
Gas Turbine ◽  
High Temperatures ◽  
Gas Turbines ◽  
High Efficiency ◽  
Development Project ◽  
Term Operation ◽  
Resistance To Heat

This paper presents an overview of a development project involving industrial cogeneration technology using 8,000-kW class hybrid gas turbines in which both metal and ceramics are used in parts subject to high temperatures in order to achieve high efficiency and low pollution. The development of hybrid gas turbines focuses mainly on the earlier commercialization of the turbine system. Stationary parts such as combustor liners, transition ducts, and first-stage turbine nozzles (stationary blades) are expected to be fabricated from ceramics. The project aims at developing material for these ceramic parts that will have a superior resistance to heat and oxidation. The project also aims at designing and prototyping a hybrid gas turbine system to analyze the operation in order to improve the performance. Furthermore, the prototyped hybrid gas turbine system will be tested for long-term operation (4,000 hours) to verify that the system can withstand commercialization. Studies will be conducted to ensure that the system’s soundness and reliability are sufficient for industrial cogeneration applications.

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