A Universal Fault Classification for Gas Turbine Diagnosis Under Variable Operating Conditions

2007 ◽  
Vol 24 (1) ◽  
Author(s):  
Igor Loboda ◽  
Yakov Feldshteyn
Keyword(s):  
Gas Turbine ◽  
Operating Conditions ◽  
Fault Classification ◽  
Variable Operating Conditions

Gas Turbine Diagnostics Under Variable Operating Conditions

2007 ◽  
Author(s):  
Igor Loboda ◽  
Yakov Feldshteyn ◽  
Sergiy Yepifanov
Keyword(s):  
Gas Turbine ◽  
Health Monitoring ◽  
Correct Diagnosis ◽  
Diagnostic System ◽  
Diagnostic Technique ◽  
Operating Conditions ◽  
Diagnostic Process ◽  
Ambient Conditions ◽  
Operating Points ◽  
Variable Operating Conditions

Operating conditions (control variables and ambient conditions) of gas turbine plants and engines vary considerably. The fact that health monitoring has to be uninterrupted creates the need for a run time diagnostic system to operate under any conditions. The diagnostic technique described in this paper utilizes the thermodynamic models in order to simulate gaspath faults and uses neural networks for the faults localization. This technique is repeatedly executed and the diagnoses are registered. On the basis of these diagnoses and beforehand known faults, the correct diagnosis probabilities are then calculated. The present paper analyses the influence of the operating conditions on a diagnostic process. In the technique, different options are simulated of a diagnostic treatment of the measured values obtained under variable operating conditions. The mentioned above probabilities help to compare these options. The main focus of the paper is on the so called multipoint (multimode) diagnosis that groups the data from different operating points (modes) to set only a single diagnosis.

A Generalized Fault Classification for Gas Turbine Diagnostics on Steady States and Transients

2006 ◽  
Author(s):  
Igor Loboda ◽  
Sergey Yepifanov ◽  
Yakov Feldshteyn
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Steady State ◽  
Gas Turbine ◽  
Correct Diagnosis ◽  
Diagnostic Techniques ◽  
Operating Conditions ◽  
Fault Classification ◽  
Diagnostic Process ◽  
Transient Operation

Gas turbine diagnostic techniques are often based on the recognition methods using the deviations between actual and expected thermodynamic performances. The problem is that the deviations depend on real operating conditions. However, our studies show that such a dependency can be reduced. In this paper, we propose the generalized fault classification that is independent of the operating conditions. To prove this idea, the averaged probabilities of the correct diagnosis are computed and compared for two cases: the proposed classification and the traditional one based on the fixed operating conditions. The probabilities are calculated through a stochastic modeling of the diagnostic process, in which a thermodynamic model generates deviations that are induced by the faults. Artificial neural networks recognize these faults. The proposed classification principle has been realized for both, steady state and transient operation of the gas turbine units. The results show that the acceptance of the generalized classification practically does not reduce the diagnosis trustworthiness.

Research on Prediction of NOx Emission Performance of Marine Gas Turbine Under Variable Operating Conditions

2020 ◽  
Author(s):  
Jian Li ◽  
Zhitao Wang ◽  
Tielei Li ◽  
Shuying Li
Keyword(s):  
Gas Turbine ◽  
Chemical Reactor ◽  
Operating Conditions ◽  
Nox Emissions ◽  
Chemical Reactor Network ◽  
Computational Fluid Dynamics Cfd ◽  
Reactor Network ◽  
D Model ◽  
Operating Points ◽  
Variable Operating Conditions

Abstract With the global warming, many countries pay more attention to environmental pollution. The NOx emissions has become an important index when gas turbine designed. This paper provides a method for predicting NOx emissions of marine gas turbine under variable operating conditions. Firstly build the 3-D model of combustor. The characteristic regions of combustor were divided according to the reaction principle. Then build the chemical reactor network (CRN) models of different characteristic regions. According to the NOx emissions of several specific operating points simulated by computational fluid dynamics (CFD), fit the relation between residence time and operating conditions by Newton interpolation in the CRN models. Then the prediction model of NOx emissions of gas turbine was established by using neural network. The NOx emissions under 0.7∼1.0 working conditions and 0.019∼0.023 fuel-air ratios can be predicted efficiently.

Investigations of Road Wear Caused by Studded Tires

2014 ◽  
Vol 42 (1) ◽  
pp. 2-15
Author(s):  
Johannes Gültlinger ◽  
Frank Gauterin ◽  
Christian Brandau ◽  
Jan Schlittenhard ◽  
Burkhard Wies
Keyword(s):  
Traffic Safety ◽  
Test Bench ◽  
Operating Conditions ◽  
Test Method ◽  
Analytical Models ◽  
The Road ◽  
Driving Speed ◽  
Major Factors ◽  
Tire Friction ◽  
Variable Operating Conditions

ABSTRACT The use of studded tires has been a subject of controversy from the time they came into market. While studded tires contribute to traffic safety under severe winter conditions by increasing tire friction on icy roads, they also cause damage to the road surface when running on bare roads. Consequently, one of the main challenges in studded tire development is to reduce road wear while still ensuring a good grip on ice. Therefore, a research project was initiated to gain understanding about the mechanisms and influencing parameters involved in road wear by studded tires. A test method using the institute's internal drum test bench was developed. Furthermore, mechanisms causing road wear by studded tires were derived from basic analytical models. These mechanisms were used to identify the main parameters influencing road wear by studded tires. Using experimental results obtained with the test method developed, the expected influences were verified. Vehicle driving speed and stud mass were found to be major factors influencing road wear. This can be explained by the stud impact as a dominant mechanism. By means of the test method presented, quantified and comparable data for road wear caused by studded tires under controllable conditions can be obtained. The mechanisms allow predicting the influence of tire construction and variable operating conditions on road wear.

Treatment system response to transient AOX (adsorbable organic halogen) loadings

1997 ◽  
Vol 35 (2-3) ◽  
pp. 85-91
Author(s):  
D. A. Barton ◽  
J. D. Woodruff ◽  
T. M. Bousquet ◽  
A. M. Parrish
Keyword(s):  
Paper Industry ◽  
Model Development ◽  
Operating Conditions ◽  
System Response ◽  
Additional Information ◽  
Organic Halogen ◽  
Aox Removal ◽  
Variable Operating Conditions ◽  
Plant Shutdown

If promulgated as proposed, effluent guidelines for the U.S. pulp and paper industry will impose average monthly and maximum daily numerical limits of discharged AOX (adsorbable organic halogen). At this time, it is unclear whether the maximum-day variability factor used to establish the proposed effluent guidelines will provide sufficient margin for mills to achieve compliance during periods of normal but variable operating conditions within the pulping and bleaching processes. Consequently, additional information is needed to relate transient AOX loadings with final AOX discharges. This paper presents a simplistic dynamic model of AOX decay during treatment. The model consists of hydraulic characterization of an activated sludge process and a first-order decay coefficient for AOX removal. Data for model development were acquired by frequent collection of influent and effluent samples at a bleach kraft mill during a bleach plant shutdown and startup sequence.

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.

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