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Systems and methods for failure prediction, diagnosis and remediation using data acquisition and feedback for a distributed electronic system

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TLDR
In this article, real-time failure prediction and diagnoses of electronic systems operating in a network environment can be achieved by using monitoring data, feedback data, and pooling of failure data from a plurality of electronic devices.
Abstract
By using monitoring data, feedback data, and pooling of failure data from a plurality of electronic devices, real-time failure prediction and diagnoses of electronic systems operating in a network environment can be achieved. First, the diagnostic system requests data on the state of a machine and/or its components and collections thereof as part of the machine's normal operation. Secondly, real-time processing of the data either at the machine site or elsewhere in the distributed network allows for predicting or diagnosing system failures. Having determined and/or predicted a system failure, a communication to one or more remote observers in the network allows the remote observers to view the diagnostic information and/or required action to repair the failure. Furthermore, interrogation of either the particular electronic system, or a database containing data on similar electronic systems by the diagnostic server allows the diagnostic server to refine original diagnoses based on this population data to achieve a comprehensive failure predication/diagnosing system.

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References
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Journal ArticleDOI

Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results

Paul M. Frank
- 01 May 1990 - 
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.
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