Add to ORKGThe paper presents a fuzzy method in fault detection and diagnosis. This method provides a systematic framework to process vague variables and vague knowledge. The supervision of the process requires the treatment of quantitative and qualitative knowledge. Here fuzzy logic approaches are especially attractive for symptom generation with fuzzy thresholds, linguistically described observed symptoms and the approximate reasoning with multi levele fuzzy rule based systems for fault symptom tree structures
A computer assisted fault detection methodology based on a fuzzy qualitative simulation algorithm is...
International audienceNowadays, determining faults in non-stationary environment and that can deal w...
Detecting fault before it deteriorates the system performance is crucial for the reliability and saf...
The task of fault detection is important when dealing with failures of crucial nature. After detecti...
The paper presents an idea of decomposition of diagnostic tasks in complex systems. Such decompositi...
International audienceSupervision of nonlinear and complex processes is of great importance to indus...
International audienceThis paper considers a decision support system dedicated to fault detection an...
Knowledge about the relation between faults and the observed symptoms is necessary for fault isolati...
A method is presented for process fault diagnosis using information from fault tree analysis and unc...
Since the introduction of the industry 4.0 paradigm, manufacturing companies are investing in the de...
Abstract—Fault diagnosis has become an important component in intelligent systems, such as intellige...
This paper focuses on the application of artificial intelligent techniques in fault detection and di...
The inherent characteristics of fuzzy logic theory make it suitable for fault detection and diagnosi...
The thesis proposes a quite novel and easily generalized fault detection and diagnosis (FDD) scheme ...
In developing knowledge-based fuzzy systems it is possible to utilize several different development ...
A computer assisted fault detection methodology based on a fuzzy qualitative simulation algorithm is...
International audienceNowadays, determining faults in non-stationary environment and that can deal w...
Detecting fault before it deteriorates the system performance is crucial for the reliability and saf...
The task of fault detection is important when dealing with failures of crucial nature. After detecti...
The paper presents an idea of decomposition of diagnostic tasks in complex systems. Such decompositi...
International audienceSupervision of nonlinear and complex processes is of great importance to indus...
International audienceThis paper considers a decision support system dedicated to fault detection an...
Knowledge about the relation between faults and the observed symptoms is necessary for fault isolati...
A method is presented for process fault diagnosis using information from fault tree analysis and unc...
Since the introduction of the industry 4.0 paradigm, manufacturing companies are investing in the de...
Abstract—Fault diagnosis has become an important component in intelligent systems, such as intellige...
This paper focuses on the application of artificial intelligent techniques in fault detection and di...
The inherent characteristics of fuzzy logic theory make it suitable for fault detection and diagnosi...
The thesis proposes a quite novel and easily generalized fault detection and diagnosis (FDD) scheme ...
In developing knowledge-based fuzzy systems it is possible to utilize several different development ...
A computer assisted fault detection methodology based on a fuzzy qualitative simulation algorithm is...
International audienceNowadays, determining faults in non-stationary environment and that can deal w...
Detecting fault before it deteriorates the system performance is crucial for the reliability and saf...