Diagnostic tasks require determining the differences between a model of an artifact and the artifact itself. The differences between the manifested behavior of the artifact and the predicted behavior of the model guide the search for the differences between the artifact and its model. The diagnostic procedure presented in this paper is model-based, inferring the behavior of the composite device...

Due to large search spaces, diagnosis of combinational circuits is often practical for finding only single and double faults. In principle, system models can be compiled into a tractable representation (such as DNNF) on which faults of arbitrary cardinality can be found efficiently. For large circuits, however, compilation can become a bottleneck due to the large number of variables necessary t...

This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...

this paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. the methodology is based on a modified sliding mode observer (smo) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. the faults are reconstructed using the equivalent output error i...

Multiple timing faults, although detectable individually, can hide each other’s faulty behavior making the faulty system indistinguishable from a non-faulty one. A set of graph augmentations are introduced for single timing faults. The fault detection capability of the augmentations is analyzed in the presence of multiple timing faults and shown that multiple occurrences of a class of timing fa...

recently different approaches have been developed in the field of sensor fault diagnostics based on auto-associative neural network (aann). in this paper we present a novel algorithm called self reconstructing auto-associative neural network (s-aann) which is able to detect and isolate single faulty sensor via reconstruction. we have also extended the algorithm to be applicable in multiple faul...

This paper presents two new fault models for networked systems. These are more realistic and generalized systems in the sense that they can represent effects of at node network levels. At layer, uncertain lines modeled using a Markov chain with complex transition probabilities simultaneously stochastic behavior Bernoulli process. A output feedback-based controller, which is two-mode dependent c...