Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causeseffects)but also deep knowledge (as structural / functional modularization and models on behavior). The paperproposes a unified approach on diagnosis by abduction based on plausibility and relevance criteria multipleapplied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on target conductiveflow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper giveshints on design and building of diagnosis system by abduction, embedding deep and shallow knowledge(according to case) and performing hierarchical fault isolation, along with a case study on a hydraulicinstalla...
A fault diagnosis method for complex dynamic processes and systems is proposed in the paper. It uses...
An application of model-based reasoning and model-based learning to an operative diagnostic domain s...
An abduction-based diagnosis technique for a class of discrete-event systems (DESs), called complex ...
Abstract: Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as patt...
Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern ...
Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes...
The principles of deep modeling are described. There are two approaches to deep modeling: component ...
The use of knowledge-based systems to aid in the diagnosis of faults in physical devices has grown c...
This paper proposes a method to solve the network fault diagnosis problem using the Realistic Abduct...
This paper performs an analysis on the applicability of state-of-the-art fault diagnosis methodologi...
First generation expert systems use judgemental knowledge of the human experts which use heuristic a...
In fault diagnostic expert systems, the knowledge can be either shallow (experience-based) or deep (...
In this paper, we propose a method to solve the network fault diagnosis problem using the realistic ...
This book provides a comprehensive set of characterization, prediction, optimization, evaluation, an...
An application of model-based reasoning and model-based learning to an operative diagnostic domain s...
A fault diagnosis method for complex dynamic processes and systems is proposed in the paper. It uses...
An application of model-based reasoning and model-based learning to an operative diagnostic domain s...
An abduction-based diagnosis technique for a class of discrete-event systems (DESs), called complex ...
Abstract: Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as patt...
Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern ...
Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes...
The principles of deep modeling are described. There are two approaches to deep modeling: component ...
The use of knowledge-based systems to aid in the diagnosis of faults in physical devices has grown c...
This paper proposes a method to solve the network fault diagnosis problem using the Realistic Abduct...
This paper performs an analysis on the applicability of state-of-the-art fault diagnosis methodologi...
First generation expert systems use judgemental knowledge of the human experts which use heuristic a...
In fault diagnostic expert systems, the knowledge can be either shallow (experience-based) or deep (...
In this paper, we propose a method to solve the network fault diagnosis problem using the realistic ...
This book provides a comprehensive set of characterization, prediction, optimization, evaluation, an...
An application of model-based reasoning and model-based learning to an operative diagnostic domain s...
A fault diagnosis method for complex dynamic processes and systems is proposed in the paper. It uses...
An application of model-based reasoning and model-based learning to an operative diagnostic domain s...
An abduction-based diagnosis technique for a class of discrete-event systems (DESs), called complex ...