Artificial neural networks (ANN) constitute a powerful class of nonlinear function approximate. ANN has been widely used in pattern recognition, prediction and classification. The application of wavelets in the fields of engineering has grown rapidl
For the improvement of reliability, safety and efficiency advanced methods of supervision, fault-detection and fault diagnosis become increasingly important formany technical processes. This holds especially for safety related processes like aircraft
This work presents an on-line diagnosis algorithm for dynamic systems that combines model based diagnosis and machine learning techniques. The Possible Conflicts method is used to perform consistency based diagnosis. Possible conflicts are in charge
Machine Learning for Automated Diagnosis of Distributed Systems Performance Machine Learning for Automated Diagnosis of Distributed Systems Performance
As the complexity of commercial cellular networks grows, there is an increasing need for automated methods detecting and diagnosing cells not only in complete outage but with degraded performance as well. Root cause analysis of the detected anomalie
The purpose of fault diagnosis in mobile ad hoc network is to have each fault-free node to determine the state of all nodes in the system. This paper proposes a fault diagnosis algorithm based on the approach proposed in [1] for diagnosing nodes in
Expert guidance on theory and practice in condition-based intelligent machine fault diagnosis and failure prognosis Intelligent Fault Diagnosis and Prognosis for Engineering Systems gives a complete presentation of basic essentials of fault diagnosi
