Model Based Diagnosis and Supervision of Industrial Gas Turbines

Larsson, Emil

doi:10.3384/diss.diva-106256

Cited by 9 publications

(11 citation statements)

References 53 publications

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“…Similarly, the fault diagnostics effectiveness of GPA and AI approaches have been compared and their pros and cons identified based on case studies by Kong [93]. Larsson [107] developed a systematic design procedure to construct non-linear MB fault diagnosis method for industrial GTs. In another study, Jasmani et al [80], devised a new measurement parameter selection scheme by combining analytical approach and measurement subset concept.…”

Section: Non-linear Gpa (Nlgpa)mentioning

confidence: 99%

A Review on Gas Turbine Gas-Path Diagnostics: State-of-the-Art Methods, Challenges and Opportunities

et al. 2019

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Gas-path diagnostics is an essential part of gas turbine (GT) condition-based maintenance (CBM). There exists extensive literature on GT gas-path diagnostics and a variety of methods have been introduced. The fundamental limitations of the conventional methods such as the inability to deal with the nonlinear engine behavior, measurement uncertainty, simultaneous faults, and the limited number of sensors available remain the driving force for exploring more advanced techniques. This review aims to provide a critical survey of the existing literature produced in the area over the past few decades. In the first section, the issue of GT degradation is addressed, aiming to identify the type of physical faults that degrade a gas turbine performance, which gas-path faults contribute more significantly to the overall performance loss, and which specific components often encounter these faults. A brief overview is then given about the inconsistencies in the literature on gas-path diagnostics followed by a discussion of the various challenges against successful gas-path diagnostics and the major desirable characteristics that an advanced fault diagnostic technique should ideally possess. At this point, the available fault diagnostic methods are thoroughly reviewed, and their strengths and weaknesses summarized. Artificial intelligence (AI) based and hybrid diagnostic methods have received a great deal of attention due to their promising potentials to address the above-mentioned limitations along with providing accurate diagnostic results. Moreover, the available validation techniques that system developers used in the past to evaluate the performance of their proposed diagnostic algorithms are discussed. Finally, concluding remarks and recommendations for further investigations are provided.

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Section: Non-linear Gpa (Nlgpa)mentioning

confidence: 99%

A Review on Gas Turbine Gas-Path Diagnostics: State-of-the-Art Methods, Challenges and Opportunities

et al. 2019

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“…Backup turbine units of industrial CHP plants with high flexibility characteristics can prove economically efficient when used for meeting the system peak load and as a paid-for system emergency reserve. An important prerequisite for the wide application of small-and medium-sized combined-cycle CHP plants is the possibility of adding them onto existing industrial gas-powered boiler houses in case of the renovation, expansion, or modernization of the latter [56,57].…”

Section: Type Of Installationmentioning

confidence: 99%

Rational Behavior of an Enterprise in the Energy Market in a Circular Economy

et al. 2019

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In order to ensure their market sustainability, it is essential for energy-intensive industrial companies to address the issues of efficient energy use. Companies that are prepared to embrace tariff hikes, structural changes in fuel and energy markets, and a shortage of energy resources have a wider range of options to respond to the new challenges posed by the external environment and to reduce their risks. This task becomes particularly relevant in the context of the development of the circular economy that is aimed at resource optimization, energy conservation, zero-waste manufacturing, and business models that are based on maximum operational efficiency. This study aims to develop a methodology for rational behavior of the energy consumer in the context of the circular economy. The concept of “rational behavior” is defined by the authors as the intention to make the maximum use of the advantages and potential of energy markets in order to reduce the cost of energy supply, increase the level of electrification in industrial production, and use the capabilities of their own energy business. The article describes the main principles of rational behavior that serve as the foundation for effective implementation of various strategies (that of the seller, buyer, or both) in a company. A link is shown between rational behavior and energy market potential management in a company as a mix of technological, economic, and organizational activities performed by the energy consumer in a competitive market and effective market risk management. Forms of off-grid power supply and conditions for their application in manufacturing, for example, mini-combined heat and power (CHP) plants and quadgeneration plants at large metallurgical facilities were analyzed.

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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%

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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Model Based Diagnosis and Supervision of Industrial Gas Turbines

Cited by 9 publications

References 53 publications

A Review on Gas Turbine Gas-Path Diagnostics: State-of-the-Art Methods, Challenges and Opportunities

A Review on Gas Turbine Gas-Path Diagnostics: State-of-the-Art Methods, Challenges and Opportunities

Rational Behavior of an Enterprise in the Energy Market in a Circular Economy

Fault Tolerant Supervision of an Industrial Gas Turbine

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