Online fault diagnosis for nonlinear power systems

Online fault diagnosis for nonlinear power systems

This paper considers the problem of automatic fault diagnosis for transmission lines in large scale power networks. Since faults in transmission lines threatens stability of the entire power network, fast and reliable fault diagnosis is an important problem in transmission line protection. This work is the first paper exploiting sparse signal recovery for the fault-diagnosis problem in power ne...

Fault Diagnosis for Nonlinear Systems

Online Fault Diagnosis of Nonlinear Systems Based on Neurofuzzy Networks

Artificial intelligence techniques such as neural networks and fuzzy logic have been widely used in fault detection and diagnosis. Combining these two techniques, referred to as neurofuzzy networks, provides a powerful tool for modelling. B-spline neurofuzzy networks are used to model the residuals. The weights of the networks are trained online using recursive least squares method. Fuzzy rules...

Fault Diagnosis for Nonlinear Hessenberg Systems

This paper deals with the problem of fault detection and isolation for nonlinear Hessenberg systems. In particular, the first part of the FDI problem associated with the disturbance decoupling transformation is considered. The approach is based on a relation between the relative degree from the unknown input to the output variables for nonlinear Hessenberg systems. The major advantage for this ...

Probabilistic Fault Diagnosis for Nonlinear Stochastic Systems

The paper focuses on fault detection and isolation (FDI) in stochastic nonlinear systems using Bayesian statistics. The main concept of this approach leans on a probabilistic model, which estimates the occurrences of faults by probabilities. The methodology consists in probabilistic mapping of the measured data into a fault variable, which acts as an indicator of considered modes of the systems...