Parameter Estimation and Performance Seeking of a Marine Gas Turbine Based on Extended Kalman Filter

2020 ◽  
Author(s):  
Zhitao Wang ◽  
Junxin Zhang ◽  
Wanling Qi ◽  
Shuying Li
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Gas Turbine ◽  
Extended Kalman Filter ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Stable Operation ◽  
Health State ◽  
Sqp Algorithm ◽  
And Performance

Abstract Marine gas turbines have been widely used and developed in the field of marine power. It is important to make them operated safely and efficiently. In this paper, a marine triaxial gas turbine is taken as an example to study the method of estimating the health state of the gas path using extended Kalman filter (EKF). To verify the accuracy of EKF, a comparison was made between linearized Kalman filtering (LKF) and EKF. In addition, the sequential quadratic programming (SQP) algorithm is used to seek the performance in case of gas path abnormal. The combination of parameter estimation and performance seeking forms a comprehensive method for diagnosis and optimization of marine gas turbines. The results show that the EKF method is an effective method for combining nonlinear systems with traditional Kalman filter. EKF has a good estimation effect on the gas path health state under different operating conditions. Also, the marine triaxial gas turbine achieved the target performance under the constraints of the SQP algorithm. Performance seeking restores the output power of the marine gas turbine and reduces the inlet and outlet temperatures of turbines. It can effectively prevent the problem of excessive combustion and ensure the safe and stable operation of the marine gas turbine.

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.

Heavy Duty Gas Turbine Simulation: Global Performances Estimation and Secondary Air System Modifications

2006 ◽  
Author(s):  
Carlo Carcasci ◽  
Bruno Facchini ◽  
Stefano Gori ◽  
Luca Bozzi ◽  
Stefano Traverso
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Cooling System ◽  
Energy System ◽  
Operating Conditions ◽  
Coupled Analysis ◽  
Ambient Conditions ◽  
Air System ◽  
Secondary Air ◽  
And Performance

This paper reviews a modular-structured program ESMS (Energy System Modular Simulation) for the simulation of air-cooled gas turbines cycles, including the calculation of the secondary air system. The program has been tested for the Ansaldo Energia gas turbine V94.3A, which is one of the more advanced models in the family Vx4.3A with a rated power of 270 MW. V94.3A cooling system has been modeled with SASAC (Secondary Air System Ansaldo Code), the Ansaldo code used to predict the structure of the flow through the internal air system. The objective of the work was to investigate the tuning of the analytical program on the basis of the data from design and performance codes in use at Ansaldo Energy Gas Turbine Department. The results, both at base load over different ambient conditions and in critical off-design operating points (full-speed-no-load and minimum-load), have been compared with APC (Ansaldo Performance Code) and confirmed by field data. The coupled analysis of cycle and cooling network shows interesting evaluations for components life estimation and reliability during off-design operating conditions.

Novel Method to Predict Non-Measured Parameters of Industrial Gas Turbines Using Kalman Filter Technique

2019 ◽  
Author(s):  
Jae Hong Lee ◽  
Tong Seop Kim ◽  
Do Won Kang ◽  
Jeong Lak Sohn ◽  
Jung Ho Lee
Keyword(s):  
Kalman Filter ◽  
Life Cycle ◽  
Gas Turbine ◽  
Case Studies ◽  
Gas Turbines ◽  
New Method ◽  
Stable Operation ◽  
Inlet Temperature ◽  
Analysis Program ◽  
Model Based

Abstract Gas turbines are most widely used for power generation and operate under various conditions and loads. Gas turbine control is important to cope with various situations, and the turbine inlet temperature (TIT) is the most important parameter because it is directly related to the power output and life cycle of the turbine. Thus, precise prediction and control of the TIT are important in terms of the stable operation and life cycle management of gas turbines. This paper proposes a new method to predict non-measured parameters such as the air flow and TIT using Kalman filter techniques. The Kalman filter is widely used for estimating the instantaneous state of a system and can estimate non-measured parameters. The Kalman filter algorithm was implemented in a gas turbine analysis program using MATLAB. The reliability of the new method was verified through various case studies using virtual data and real operating data. The results were compared with those of a model-based gas turbine diagnostics program. The computing time of the Kalman filter and model-based diagnostics program were also compared to confirm the capability of the new method. The results indicate that the new method is more suitable for diagnostics and monitoring applications than the model-based analysis program. Finally, two case studies were performed to confirm the feasibility of the new method using two virtual datasets. The results confirm that the Kalman filter can predict the non-measured parameters precisely.

Fusing unscented Kalman filter for performance monitoring and fault accommodation in gas turbine

2016 ◽  
Vol 232 (3) ◽  
pp. 556-570 ◽  
Author(s):  
Feng Lu ◽  
Yafan Wang ◽  
Jinquan Huang ◽  
Yihuan Huang ◽  
Xiaojie Qiu
Keyword(s):  
Kalman Filter ◽  
Gas Turbine ◽  
Extended Kalman Filter ◽  
Kalman Filters ◽  
Performance Monitoring ◽  
Unscented Kalman Filter ◽  
Estimation Accuracy ◽  
Health State ◽  
Sensor Failure ◽  
Turbine Performance

The Kalman filter is widely utilized for gas turbine health monitoring due to its simplicity, robustness, and suitability for real-time implementations. The most common Kalman filter for linear systems is linearized Kalman filter, and for nonlinear systems are extended Kalman filter and unscented Kalman filter. These algorithms have proven their capabilities to estimate gas turbine performance variations with a good accuracy, and the studies are done provided that all sensor measurements are available. In this paper, a nonlinear fusion approach with consistent diagnostic mechanism based on unscented Kalman filter is proposed, especially for gas turbine performance monitoring in the case of sensor failure. The architecture of fusion method comprises a set of local unscented Kalman filters and an information mixer. The local unscented Kalman filters are utilized to estimate health parameters of various component combinations, and the results are then transferred to the mixer for the integrated estimation of global health state in fusion structure. The consistent fault diagnosis and isolation logic is designed based on the fusion architecture and combined with the fusing unscented Kalman filter, called an improved fusing unscented Kalman filter. A systematic comparison of the generic linearized Kalman filter, extended Kalman filter, and unscented Kalman filter to their fusion filter kinds is presented for engine health estimation of gradual deterioration and abrupt fault. The studies show that the fusing unscented Kalman filter evidently outperforms the fusing linearized Kalman filter and fusing extended Kalman filter, while the fusing Kalman filters have slightly better estimation accuracy than the basic Kalman filters. In addition, the proposed methodology can reach the reliable performance monitoring with measurement uncertainty while the conventional Kalman filters collapse.

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.

scholarly journals Comprehensive Thermodynamic Analysis of the Humphrey Cycle for Gas Turbines with Pressure Gain Combustion

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3521 ◽  
Author(s):  
Panagiotis Stathopoulos
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Combustion Process ◽  
Ideal Gas ◽  
Point Of View ◽  
Pressure Gain Combustion ◽  
Combustion Technology ◽  
Secondary Air ◽  
And Performance ◽  
The Impact

Conventional gas turbines are approaching their efficiency limits and performance gains are becoming increasingly difficult to achieve. Pressure Gain Combustion (PGC) has emerged as a very promising technology in this respect, due to the higher thermal efficiency of the respective ideal gas turbine thermodynamic cycles. Up to date, only very simplified models of open cycle gas turbines with pressure gain combustion have been considered. However, the integration of a fundamentally different combustion technology will be inherently connected with additional losses. Entropy generation in the combustion process, combustor inlet pressure loss (a central issue for pressure gain combustors), and the impact of PGC on the secondary air system (especially blade cooling) are all very important parameters that have been neglected. The current work uses the Humphrey cycle in an attempt to address all these issues in order to provide gas turbine component designers with benchmark efficiency values for individual components of gas turbines with PGC. The analysis concludes with some recommendations for the best strategy to integrate turbine expanders with PGC combustors. This is done from a purely thermodynamic point of view, again with the goal to deliver design benchmark values for a more realistic interpretation of the cycle.

scholarly journals Gas Turbine Health State Determination: Methodology Approach and Field Application

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Michele Pinelli ◽  
Pier Ruggero Spina ◽  
Mauro Venturini
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Field Measurements ◽  
Field Application ◽  
Diagnostic Process ◽  
Health State ◽  
Gas Compression ◽  
State Determination ◽  
Measurement Validation ◽  
Machine Health

A reduction of gas turbine maintenance costs, together with the increase in machine availability and the reduction of management costs, is usually expected when gas turbine preventive maintenance is performed in parallel to on-condition maintenance. However, on-condition maintenance requires up-to-date knowledge of the machine health state. The gas turbine health state can be determined by means of Gas Path Analysis (GPA) techniques, which allow the calculation of machine health state indices, starting from measurements taken on the machine. Since the GPA technique makes use of field measurements, the reliability of the diagnostic process also depends on measurement reliability. In this paper, a comprehensive approach for both the measurement validation and health state determination of gas turbines is discussed, and its application to a 5 MW gas turbine working in a natural gas compression plant is presented.

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