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An OptimizationBased Method for Dynamic Multiple Fault Diagnosis Problem
, 2007
"... Imperfect test outcomes, due to factors such as unreliable sensors, electromagnetic interference, and environmental conditions, manifest themselves as missed detections and false alarms. The main objective of our research on onboard diagnostic inference is to develop nearoptimal algorithms for d ..."
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Cited by 5 (4 self)
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for dynamic multiple fault diagnosis (DMFD) problems in the presence of imperfect test outcomes. Our problem is to determine the most likely evolution of fault states, the one that best explains the observed test outcomes. Here, we develop a primaldual algorithm for solving the DMFD problem by combining
MaxProduct Algorithms for the Generalized Multiple Fault Diagnosis Problem
"... Abstractâ€”In this paper, we study the application of the maxproduct algorithm to the generalized multiple fault diagnosis (GMFD) problem. The GMFD is described by a set of components (or diseases), a set of alarms (or symptoms) and a set of causal dependencies between them. More specifically, given ..."
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Abstractâ€”In this paper, we study the application of the maxproduct algorithm to the generalized multiple fault diagnosis (GMFD) problem. The GMFD is described by a set of components (or diseases), a set of alarms (or symptoms) and a set of causal dependencies between them. More specifically
Diverse Neural Net Solutions to a Fault Diagnosis Problem
 Neural Computing and Applications
, 1996
"... The development of a neural net system for fault diagnosis in a marine diesel engine is described. Nets were trained to classify combustion quality on the basis of simulated data. Three different types of data were used; Pressure, Temperature and Combined Pressure and Temperature. Subsequent to ..."
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The development of a neural net system for fault diagnosis in a marine diesel engine is described. Nets were trained to classify combustion quality on the basis of simulated data. Three different types of data were used; Pressure, Temperature and Combined Pressure and Temperature. Subsequent
Diagnosing multiple faults.
 Artificial Intelligence,
, 1987
"... Abstract 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 ..."
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Cited by 808 (62 self)
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with sequential diagnosis to propose measurements to localize the faults. The normally required conditional probabilities are computed from the structure of the device and models of its components. This capability results from a novel way of incorporating probabilities and information theory into the context
Reaching Agreement in the Presence of Faults
 JOURNAL OF THE ACM
, 1980
"... The problem addressed here concerns a set of isolated processors, some unknown subset of which may be faulty, that communicate only by means of twoparty messages. Each nonfaulty processor has a private value of reformation that must be communicated to each other nonfanlty processor. Nonfaulty proc ..."
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Cited by 653 (8 self)
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The problem addressed here concerns a set of isolated processors, some unknown subset of which may be faulty, that communicate only by means of twoparty messages. Each nonfaulty processor has a private value of reformation that must be communicated to each other nonfanlty processor. Nonfaulty
Efficient dispersal of information for security, load balancing, and fault tolerance
 Journal of the ACM
, 1989
"... Abstract. An Information Dispersal Algorithm (IDA) is developed that breaks a file F of length L = ( F ( into n pieces F,, 1 5 i 5 n, each of length ( F, 1 = L/m, so that every m pieces suffice for reconstructing F. Dispersal and reconstruction are computationally efficient. The sum of the lengths ..."
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Cited by 561 (1 self)
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cations between processors in parallel computers. For the latter problem provably timeefftcient and highly faulttolerant routing on the ncube is achieved, using just constant size buffers. Categories and Subject Descriptors: E.4 [Coding and Information Theory]: nonsecret encoding schemes
A Theory of Diagnosis from First Principles
 ARTIFICIAL INTELLIGENCE
, 1987
"... Suppose one is given a description of a system, together with an observation of the system's behaviour which conflicts with the way the system is meant to behave. The diagnostic problem is to determine those components of the system which, when assumed to be functioning abnormally, will explain ..."
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Cited by 1120 (5 self)
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Suppose one is given a description of a system, together with an observation of the system's behaviour which conflicts with the way the system is meant to behave. The diagnostic problem is to determine those components of the system which, when assumed to be functioning abnormally
Consensus in the presence of partial synchrony
 JOURNAL OF THE ACM
, 1988
"... The concept of partial synchrony in a distributed system is introduced. Partial synchrony lies between the cases of a synchronous system and an asynchronous system. In a synchronous system, there is a known fixed upper bound A on the time required for a message to be sent from one processor to ano ..."
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Cited by 513 (18 self)
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to another and a known fixed upper bound (I, on the relative speeds of different processors. In an asynchronous system no fixed upper bounds A and (I, exist. In one version of partial synchrony, fixed bounds A and (I, exist, but they are not known a priori. The problem is to design protocols that work
Detectability of Discrete Event Systems
"... In this paper, we investigate the detectability problem in discrete event systems. We assume that we do not know initially which state the system is in. The problem is to determine the current and subsequent states of the system based on a sequence of observation. The observation includes partial ev ..."
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Cited by 806 (14 self)
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In this paper, we investigate the detectability problem in discrete event systems. We assume that we do not know initially which state the system is in. The problem is to determine the current and subsequent states of the system based on a sequence of observation. The observation includes partial
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