Fault diagnosis of continuous systems using discrete-event methods

Daigle, Matthew; Koutsoukos, Xenofon; Biswas, Gautam

doi:10.1109/cdc.2007.4434897

Cited by 8 publications

(13 citation statements)

References 15 publications

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“…By including discrete faults, we develop a unified hybrid diagnosis methodology. We also extend our event-based diagnosis framework for continuous systems (Daigle, et al, 2007b) to hybrid systems, and this allows us to establish and verify notions of diagnosability for hybrid systems within our framework. We demonstrate the effectiveness of the approach using a real hybrid system, the Advanced Diagnostics and Prognostics Testbed (ADAPT) (Poll et al, 2007), deployed at NASA Ames Research Center, which is functionally representative of a spacecraft's electrical power system.…”

Section: Introductionmentioning

confidence: 99%

An event-based approach to integrated parametric and discrete fault diagnosis in hybrid systems

Daigle

Koutsoukos

Biswas

2009

Transactions of the Institute of Measurement and Control

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Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems. These systems often exhibit hybrid behaviours, therefore, model-based diagnosis methods have to be based on hybrid system models. Most previous work in hybrid systems diagnosis has focused either on parametric or discrete faults. In this paper, we develop an integrated approach for hybrid diagnosis of parametric and discrete faults by incorporating the effects of both types of faults into our event-based qualitative fault signature framework. The framework allows for systematic design of event-based diagnosers that facilitate diagnosability analysis. Experimental results from a case study performed on an electrical power distribution system demonstrate the effectiveness of the approach.

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Section: Introductionmentioning

confidence: 99%

An event-based approach to integrated parametric and discrete fault diagnosis in hybrid systems

Daigle

Koutsoukos

Biswas

2009

Transactions of the Institute of Measurement and Control

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“…More advanced techniques for fault diagnosis use other information, apart from the binary one, such as the sign of the symptom, the order of the symptom appearance, or the size of the residual [25]- [27]. SQualTrack provides all this information so it can be used in combination with these techniques.…”

Section: Discussionmentioning

confidence: 99%

SQualTrack: A Tool for Robust Fault Detection

Armengol

Vehı́

Saínz

et al. 2009

IEEE Trans. Syst., Man, Cybern. B

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Abstract-One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is SemiQUALitative TRACKing (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project Advanced Decision Support System for Chemical/Petrochemical Manufacturing Processes and are also described in this paper.

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“…However, only few results on fault detection and isolation (FDI) of a network of unmanned vehicles have been developed in the literature. A distributed, model-based, qualitative fault diagnosis scheme is developed in [3] for multi-robot formation. Recently, in [4], a decentralized nonabrupt fault detection scheme is presented for a leader-to-follower formation of unmanned airships.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Fault Detection and Isolation Strategy for a Network of Unmanned Vehicles in Presence of Large Environmental Disturbances

Meskin

Khorasani

Rabbath

2010

IEEE Trans. Contr. Syst. Technol.

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In this brief, the problem of designing and developing a hybrid fault detection and isolation (FDI) scheme for a network of unmanned vehicles (NUVs) that is subject to large environmental disturbances is investigated. The proposed FDI algorithm is a hybrid architecture that is composed of a bank of continuous-time residual generators and a discrete-event system (DES) fault diagnoser. A novel set of residuals is generated so that the DES fault diagnoser empowered by incorporating appropriate combinations of the residuals and their sequential features will robustly detect and isolate faults in the NUVs. Our proposed hybrid FDI algorithm is then applied to actuator fault detection and isolation in a network of quad-rotors. Simulation results demonstrate and validate the performance capabilities of our proposed hybrid FDI algorithm.Index Terms-Fault detection and isolation (FDI), hybrid fault diagnosis, large environmental disturbances, network of unmanned systems.

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Fault diagnosis of continuous systems using discrete-event methods

Cited by 8 publications

References 15 publications

An event-based approach to integrated parametric and discrete fault diagnosis in hybrid systems

An event-based approach to integrated parametric and discrete fault diagnosis in hybrid systems

SQualTrack: A Tool for Robust Fault Detection

A Hybrid Fault Detection and Isolation Strategy for a Network of Unmanned Vehicles in Presence of Large Environmental Disturbances

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