Data processing: measuring – calibrating – or testing – Measurement system – Performance or efficiency evaluation
Reexamination Certificate
2002-08-13
2004-08-17
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system
Performance or efficiency evaluation
C709S241000
Reexamination Certificate
active
06778943
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of Invention
This invention is directed to the systems and methods for on-line distributed fault diagnosis of qualitative systems using precompiled finite state automata.
2. Description of Related Art
Finite state automata are used in a wide variety of technical fields, such as fault diagnosis, as a graphic representation for describing regular sequences of events or actions. For example, finite state automata are used to capture qualitative descriptions of the behavior of components of systems, as is often described in the literature, such as “Coordinated Decentralized Protocols for Failure Diagnosis of Discrete Event Systems”, by R. Debouk et al., Discrete Event Dynamic Systems: Theory and Applications, 10(1/2): 33-86, January 2000, or “Active Diagnosis of Discrete-Event Systems”, by M. Sampath et al., in Proc. 36
th
CDC, pages 2976-2983, San Diego, USA, December 1997.
Such finite state automata model the sequences of actions that are possible or allowable. One type of action or failure results in one set of possible states, while a different failure produces different states. When sensors are used to observe the resulting state, these observations are used to constrain the model to those actions that are consistent with the observations. Weighting or costs can be assigned to certain actions. Probability analysis can then be used on the finite state automata to determine which of the allowable states is most likely to occur.
SUMMARY OF THE INVENTION
Currently, most model-based diagnostic approaches are either purely centralized or partially centralized. Purely centralized approaches use a central diagnostic system that receives all information and that executes a diagnosis algorithm. In contrast, partly centralized approaches use a set of local diagnostic systems and a central coordinator that controls the information exchange among the local diagnostic systems. For a large system, routing information to or through a centralized processing unit is vulnerable to failure of the central processing unit and or of the communication system connecting the central processing unit to the sensors or the local diagnostic systems. In addition, centralized schemes limit the amount of processing to that provided by the single centralized processing unit. This limits the scalability of centralized diagnostic approaches in terms of the complexity of the physical system that can be diagnosed in a given period of time.
This invention provides systems and methods that perform distributed fault diagnosis.
This invention separately provides diagnostic systems and methods that include models of the physical system being diagnosed.
This invention separately provides systems and methods that utilize finite state automata to enable fast local diagnosis.
This invention separately provides systems and methods that implement local diagnostic analysis.
This invention separately provides systems and methods that provide communication between local diagnostic analyses over distributed networks.
This invention further provides systems and methods that construct local diagnoses and global diagnoses from the local diagnoses.
This invention separately provides systems and methods that apply probabilistic reasoning to determine a next optimal measurement position.
In various exemplary embodiments, the systems and methods according to this invention use finite state automata to model the possible states of local components given the local sensor readings and potential inputs from other components. In various exemplary embodiments, potential states are found during diagnosis of the local component, given one or more sensor observations made of any behavior. This state information is then distributed to other components. Potential states are then found during diagnosis of the local component, given state information provided concerning the states of other components. In various exemplary embodiments, probabilistic reasoning is used to determine when it is effective to use high cost sensor observations, communications and/or distributed diagnostic systems as part of the global diagnosis process.
These and other features and advantages of this invention are described in, or are apparent from, the following detailed description of various exemplary embodiments of the systems and methods according to this invention.
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Sampath, M., et al., “Active Diagnosis of Discrete-Event Systems,”IEEE Transactions on Automatic Control, vol. 43, No. 7, Jul. 1998, pp. 908-929.
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Koutsoukos Xenofon
Kurien James A.
Su Rong
Charioui Mohamed
Xerox Corporation
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