28,005 research outputs found
A distributed networked approach for fault detection of large-scale systems
Networked systems present some key new challenges in the development of fault diagnosis architectures. This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems. The proposed formulation incorporates a synchronization methodology with a filtering approach in order to reduce the effect of measurement noise and time delays on the fault detection performance. The proposed approach allows the monitoring of multi-rate systems, where asynchronous and delayed measurements are available. This is achieved through the development of a virtual sensor scheme with a model-based re-synchronization algorithm and a delay compensation strategy for distributed fault diagnostic units. The monitoring architecture exploits an adaptive approximator with learning capabilities for handling uncertainties in the interconnection dynamics. A consensus-based estimator with timevarying weights is introduced, for improving fault detectability in the case of variables shared among more than one subsystem. Furthermore, time-varying threshold functions are designed to prevent false-positive alarms. Analytical fault detectability sufficient conditions are derived and extensive simulation results are presented to illustrate the effectiveness of the distributed fault detection technique
A Distributed Networked Approach for Fault Detection of Large-scale Systems
Networked systems present some key new challenges in the development of fault diagnosis architectures. This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems. The proposed formulation incorporates a synchronization methodology with a filtering approach in order to reduce the effect of measurement noise and time delays on the fault detection performance. The
proposed approach allows the monitoring of multi-rate systems, where asynchronous and delayed measurements are available.
This is achieved through the development of a virtual sensor scheme with a model-based re-synchronization algorithm and a delay compensation strategy for distributed fault diagnostic units.
The monitoring architecture exploits an adaptive approximator with learning capabilities for handling uncertainties in the interconnection
dynamics. A consensus-based estimator with timevarying weights is introduced, for improving fault detectability in the case of variables shared among more than one subsystem.
Furthermore, time-varying threshold functions are designed to prevent false-positive alarms. Analytical fault detectability sufficient conditions are derived and extensive simulation results are presented to illustrate the effectiveness of the distributed fault detection technique
Causality and Temporal Dependencies in the Design of Fault Management Systems
Reasoning about causes and effects naturally arises in the engineering of
safety-critical systems. A classical example is Fault Tree Analysis, a
deductive technique used for system safety assessment, whereby an undesired
state is reduced to the set of its immediate causes. The design of fault
management systems also requires reasoning on causality relationships. In
particular, a fail-operational system needs to ensure timely detection and
identification of faults, i.e. recognize the occurrence of run-time faults
through their observable effects on the system. Even more complex scenarios
arise when multiple faults are involved and may interact in subtle ways.
In this work, we propose a formal approach to fault management for complex
systems. We first introduce the notions of fault tree and minimal cut sets. We
then present a formal framework for the specification and analysis of
diagnosability, and for the design of fault detection and identification (FDI)
components. Finally, we review recent advances in fault propagation analysis,
based on the Timed Failure Propagation Graphs (TFPG) formalism.Comment: In Proceedings CREST 2017, arXiv:1710.0277
On Fault Diagnosis of random Free-choice Petri Nets
This paper presents an on-line diagnosis algorithm for Petri nets where a priori probabilistic knowledge about the plant operation is available. We follow the method developed by Benveniste, Fabre, and Haar to assign probabilities to configurations in a net unfolding thus avoiding the need for randomizing all concurrent interleavings of transitions. We consider different settings of the diagnosis problem, including estimating the likelihood that a fault may have happened prior to the most recent observed event, the likelihood that a fault will have happened prior to the next observed event. A novel problem formulation treated in this paper considers deterministic diagnosis of faults that occurred prior to the most recent observed event, and simultaneous calculation of the likelihood that a fault will occur prior to the next observed event
Mathematical control of complex systems
Copyright © 2013 ZidongWang et al.This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Formal Design of Asynchronous Fault Detection and Identification Components using Temporal Epistemic Logic
Autonomous critical systems, such as satellites and space rovers, must be
able to detect the occurrence of faults in order to ensure correct operation.
This task is carried out by Fault Detection and Identification (FDI)
components, that are embedded in those systems and are in charge of detecting
faults in an automated and timely manner by reading data from sensors and
triggering predefined alarms. The design of effective FDI components is an
extremely hard problem, also due to the lack of a complete theoretical
foundation, and of precise specification and validation techniques. In this
paper, we present the first formal approach to the design of FDI components for
discrete event systems, both in a synchronous and asynchronous setting. We
propose a logical language for the specification of FDI requirements that
accounts for a wide class of practical cases, and includes novel aspects such
as maximality and trace-diagnosability. The language is equipped with a clear
semantics based on temporal epistemic logic, and is proved to enjoy suitable
properties. We discuss how to validate the requirements and how to verify that
a given FDI component satisfies them. We propose an algorithm for the synthesis
of correct-by-construction FDI components, and report on the applicability of
the design approach on an industrial case-study coming from aerospace.Comment: 33 pages, 20 figure
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