Add to ORKGThis thesis provides a detailed investigation on performance-based data-driven automatic condition monitoring of industrial gas turbine engines for fault detection, isolation and prognosis to improve the maintenance strategy of this critical equipment
International audienceGas turbines are critical to the operation of most industrial plants, and thei...
ABSTRACT: One key aspect when developing a robust health management system for turbines is the devel...
Researches show that probability-statistical methods application, especially at the early stage of t...
Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of app...
Effective fault detection, estimation, and isolation are essential for the safety and reliability of...
Abstract: The paper focuses on the application of neuro-fuzzy techniques in fault detection and isol...
The industrial machinery reliability represents a critical factor in order to assure the proper oper...
In the paper, Neuro-Fuzzy Systems (NFSs) for gas turbine diagnostics are studied and developed. The ...
In the paper, neuro-fuzzy systems (NFSs) for gas turbine diagnostics are studied and developed. The ...
[[abstract]]In this paper, an adaptive neuro-fuzzy inference system (ANFIS) was proposed for conditi...
In a free energy market the reduction of operating costs becomes a primary goal and, in this context...
Abstract: This paper present a methodology for fault diagnosis in power transformers using an Adap...
Monitoring and predicting machine components ' faults play an important role in maintenance act...
Effective fault diagnosis approach in gas turbines is crucial for ensuring reliable and efficient op...
A fuzzy system is developed using a linearized performance model of the gas turbine engine for perfo...
International audienceGas turbines are critical to the operation of most industrial plants, and thei...
ABSTRACT: One key aspect when developing a robust health management system for turbines is the devel...
Researches show that probability-statistical methods application, especially at the early stage of t...
Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of app...
Effective fault detection, estimation, and isolation are essential for the safety and reliability of...
Abstract: The paper focuses on the application of neuro-fuzzy techniques in fault detection and isol...
The industrial machinery reliability represents a critical factor in order to assure the proper oper...
In the paper, Neuro-Fuzzy Systems (NFSs) for gas turbine diagnostics are studied and developed. The ...
In the paper, neuro-fuzzy systems (NFSs) for gas turbine diagnostics are studied and developed. The ...
[[abstract]]In this paper, an adaptive neuro-fuzzy inference system (ANFIS) was proposed for conditi...
In a free energy market the reduction of operating costs becomes a primary goal and, in this context...
Abstract: This paper present a methodology for fault diagnosis in power transformers using an Adap...
Monitoring and predicting machine components ' faults play an important role in maintenance act...
Effective fault diagnosis approach in gas turbines is crucial for ensuring reliable and efficient op...
A fuzzy system is developed using a linearized performance model of the gas turbine engine for perfo...
International audienceGas turbines are critical to the operation of most industrial plants, and thei...
ABSTRACT: One key aspect when developing a robust health management system for turbines is the devel...
Researches show that probability-statistical methods application, especially at the early stage of t...