Add to ORKGA fault diagnosis scheme for unknown nonlinear dynamic systems with modules of residual generation and residual evaluation is considered. Main emphasis is placed upon designing a bank of neural networks with dynamic neurons that model a system diagnosed at normal and faulty operating points.To improve the quality of neural modelling, two optimization problems are included in the construction of such dynamic networks: searching for an optimal network architecture and the network training algorithm. To find a good solution, the effective well-known cascade-correlation algorithm is adapted here. The residuals generated by a bank of neural models are then evaluated by means of pattern classification. To illustrate the effectiveness of our appro...
This paper presents a novel approach for the detection of faults for a class of nonlinear systems wh...
This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems...
Recent approaches to fault detection and isolation (FDI) for dynamic systems using methods of integr...
The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The ma...
The possibilities offered by neural networks for system identification and fault diagnosis problems ...
The paper focuses on the problem of fault detection and isolation for dynamic processes using select...
A locally recurrent neural network based fault detection and isolation approach is presented. A mode...
The field of fault detection and diagnosis deals with the design of computer-based automated systems...
This chapter provides an overview on different fault diagnosis strategies, with particular attention...
The complexity of technological processes needs the study and development of computer based fault de...
Part 15: Environmental and Earth Applications of AIInternational audienceA locally recurrent neural ...
Fault diagnosis and identification (FDI) have been widely developed during recent years. Model--bas...
In this work a model--based procedure exploiting analytical redundancy via state estimation techn...
This thesis focuses on the neural networks and their application in the fault monitoring. A neural n...
This report focuses on the neural networks and their application in the fault monitoring. A neural ...
This paper presents a novel approach for the detection of faults for a class of nonlinear systems wh...
This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems...
Recent approaches to fault detection and isolation (FDI) for dynamic systems using methods of integr...
The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The ma...
The possibilities offered by neural networks for system identification and fault diagnosis problems ...
The paper focuses on the problem of fault detection and isolation for dynamic processes using select...
A locally recurrent neural network based fault detection and isolation approach is presented. A mode...
The field of fault detection and diagnosis deals with the design of computer-based automated systems...
This chapter provides an overview on different fault diagnosis strategies, with particular attention...
The complexity of technological processes needs the study and development of computer based fault de...
Part 15: Environmental and Earth Applications of AIInternational audienceA locally recurrent neural ...
Fault diagnosis and identification (FDI) have been widely developed during recent years. Model--bas...
In this work a model--based procedure exploiting analytical redundancy via state estimation techn...
This thesis focuses on the neural networks and their application in the fault monitoring. A neural n...
This report focuses on the neural networks and their application in the fault monitoring. A neural ...
This paper presents a novel approach for the detection of faults for a class of nonlinear systems wh...
This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems...
Recent approaches to fault detection and isolation (FDI) for dynamic systems using methods of integr...