Fault Isolation for an Industrial Gas Turbine With a Model-Based Diagnosis Approach

Larsson, Emil; Åslund, Jan; Frisk, Erik; Eriksson, Lars

doi:10.1115/gt2010-22511

Cited by 8 publications

(13 citation statements)

References 20 publications

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“…The FDI-system is based on hypothesis testing and there is one hypothesis for each sensor and actuator failure. Such an approach is standard in general diagnosis methodology (Blanke et al, 2003) and similar approach was also utilized in Larsson et al (2010); . Thus, let H i , i 1, .…”

Section: Fault Isolation Methodsmentioning

confidence: 99%

“…The diagnosis model is derived from a model which is similar, and validated against a reference model (Idebrant and Näs, 2003) used by SIT for performance analysis. The two model concepts used for diagnosis and performance analysis are first presented in Larsson et al (2010) and further improved in Larsson et al (2014a). In the diagnosis model D i , concepts related to component degradation and fault diagnosis are introduced which are not considered in the model used for performance analysis.…”

Section: Gas Turbine Diagnosis Modelingmentioning

confidence: 99%

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Model Based Diagnosis and Supervision of Industrial Gas Turbines

Larsson¹

2014

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Supervision of performance in gas turbine applications is important in order to achieve: (i) reliable operations, (ii) low heat stress in components, (iii) low fuel consumption, and (iv) efficient overhaul and maintenance. To obtain good diagnosis performance it is important to have tests which are based on models with high accuracy. A main contribution of the thesis is a systematic design procedure to construct a fault detection and isolation (FDI) system which is based on complex nonlinear models. These models are preliminary used for simulation and performance evaluations. Thus, is it possible to use these models also in the FDI-system and which model parts are necessary to consider in the test design? To fulfill the requirement of an automated design procedure, a thermodynamic gas turbine package GTLib is developed. Using the GTLib framework, a gas turbine diagnosis model is constructed where component deterioration is introduced. In the design of the test quantities, equations from the developed diagnosis models are carefully selected. These equations are then used to implement a Constant Gain Extended Kalman filter (CGEKF) based test quantity. The number of equations and variables which the test quantity is based on is significantly reduced compared to the original reference model. The test quantity is used in the FDI-system to supervise the performance and the turbine inlet temperature which is used in the controller. An evaluation is performed using experimental data from a gas turbine site. The case study shows that the designed FDI-system can be used when the decision about a compressor wash is taken. When the FDI-system is augmented with more test quantities it is possible to diagnose sensor and actuator faults at the same time the performance is supervised. Slow varying sensor and actuator bias faults are difficult diagnose since they appear in a similar manner as the performance deterioration, but the FDI-system has the ability to detect these faults. Finally, the proposed model based design procedure can be considered when an FDI-system of an industrial gas turbine is constructed.iii Populärvetenskaplig sammanfattning Diagnostik och prestandaövervakning förekommer inom många industriella applikationer. Detta område är viktigt att beakta för att: (i) upprätthålla hög tillförlitlighet, (ii) undvika onödig belastning på komponenter, (iii) minimera energiförbrukningen, och (iv) effektivt kunna planera underhåll. Eftersom prestandan i en applikation oftast inte är direkt mätbar behövs metoder för att kunna skatta dessa prestandaparametrar utifrån kända mätsignaler. Detta kan vara svårt eftersom: (i) sambandet mellan mätsig-naler och prestandaparametrar kan vara komplicerat, (ii) mätsignaler innehåller brus, och (iii) mätsignaler kan vara opålitliga och visa ett felaktigt värde. Dessa aspekter bör beaktas när ett diagnos-och övervakningssystem utvecklas. Eftersom många system är komplexa kan det vara nödvändigt att ha effektiva och automatiserade metoder för att skatta prestanda och bestämma diag...

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Section: Fault Isolation Methodsmentioning

confidence: 99%

Section: Gas Turbine Diagnosis Modelingmentioning

confidence: 99%

Model Based Diagnosis and Supervision of Industrial Gas Turbines

Larsson¹

2014

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“…The performance model is validated against a reference model [10] developed by Siemens Industrial Turbomachinery AB in Finspång, Sweden. The two models used for diagnosis and performance calculation are first presented in [9] and are further elaborated in [8]. In the present work, the previous developed diagnosis model methodology is utilized where different configurations are considered.…”

Section: Gas Turbine Diagnosis Modelsmentioning

confidence: 99%

“…The advantage with the diagnosis model is the ability to generate test quantities T i used in the FDI system. The test generation procedure is first presented in [9] and then summarized in [8].…”

Section: Gas Turbine Diagnosis Modelsmentioning

confidence: 99%

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Fault Tolerant Supervision of an Industrial Gas Turbine

Larsson

Åslund

Frisk

et al. 2013

Volume 4: Ceramics; Concentrating Solar Power Plants; Controls, Diagnostics and Instrumentation; Education; Electric Power; Fan

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Supervision of the performance of an industrial gas turbine is important since it gives valuable information of the process health and makes efficient determination of compressor wash intervals possible. Slowly varying sensor faults can easily be misinterpreted as performance degradations and result in an unnecessary compressor wash. Here, a diagnostic algorithm is carefully combined with non-linear state observers to achieve fault tolerant performance estimation. The proposed approach is evaluated in an experimental case study with six months of measurement data from a gas turbine site. The investigation shows that faults in all gas path instrumentation sensors are detectable and isolable. A key result of the case study is the ability to detect and isolate a slowly varying sensor fault in the discharge temperature sensor after the compressor. The fault is detected and isolated before the wash condition of the compressor is triggered, resulting in fault tolerant estimation of compressor health parameters.

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A physics-based framework for online surface roughness assessment for high-pressure turbines

Liu

2021

Chinese Journal of Aeronautics

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Fault Isolation for an Industrial Gas Turbine With a Model-Based Diagnosis Approach

Cited by 8 publications

References 20 publications

Model Based Diagnosis and Supervision of Industrial Gas Turbines

Model Based Diagnosis and Supervision of Industrial Gas Turbines

Fault Tolerant Supervision of an Industrial Gas Turbine

A physics-based framework for online surface roughness assessment for high-pressure turbines

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