Friday, October 4, 2013

A Distributed Networked Approach to Fault Diagnosis of Large-Scale Systems

Here it  deals with a class of systems that are becoming ubiquitous in the current and future    "distributed world" made by countless "nodes",which can be cities, computers, people, etc., and interconnected by a dense web of transportation, communication, or social  ties.The     term "network", describing such a collection of nodes and  links, nowadays has become     commonplace thanks to our extensive reliance on "connections of interdependent     systems"   in our everyday life,for building complex technical  systems, infrastructures and  so on. 

In an     increasingly "smarter" planet, it  is expected that such interconnected systems will be safe,    reliable, available 24/7,and of low-cost maintenance.Therefore, health monitoring and fault     diagnosis are of customary importance to ensure high levels of safety, performance,    reliability, dependability, and availability. For example, in the case of industrial plants,faults     and malfunctions can result in off-specification  production,increased operating costs,     production line shutdown,danger conditions for humans, detrimental environmental impact,    and so on.Faults and malfunctions need to be detected promptly and their source and    severity should be diagnosed so that corrective actions can be taken as soon as possible. 


In  the talk, an adaptive approximation-based distributed and networked fault diagnosis   approach for large-scale nonlinear systems will be dealt  with, by exploiting a "divide et    impera" approach in which the overall diagnosis problem is  decomposed into smaller    sub-problems, which can be solved within “local” computation and communication    architectures.The distributed detection,  isolation and identification task  is broken  down    and  assigned  to a network of "Local Diagnostic Units", each having a "local view" of he    system.    These local diagnostic units are allowed to communicate with each other through an    information network  to cooperate on the diagnosis of system components that may be    shared or interconnected.

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