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Related Experiment Video

Updated: Nov 16, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Distributed Intermittent Fault Detection for Linear Stochastic Systems Over Sensor Network.

Yichun Niu, Li Sheng, Ming Gao

    IEEE Transactions on Cybernetics
    |February 19, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new method for detecting intermittent faults (IFs) in sensor networks. The approach uses a novel moving-horizon estimator to accurately pinpoint fault times and affected nodes, improving system reliability.

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    Area of Science:

    • Control Systems Engineering
    • Networked Systems
    • Fault Detection and Diagnosis

    Background:

    • Intermittent faults (IFs) pose significant challenges in linear stochastic systems, especially within sensor networks due to their unpredictable nature.
    • Existing moving horizon estimation algorithms struggle with the smearing effect of IFs, compromising detection accuracy.
    • Distributed detection of nondeterministic IFs requires robust algorithms capable of handling time-varying fault characteristics.

    Purpose of the Study:

    • To develop a novel residual generator for distributed intermittent fault detection in sensor networks.
    • To enhance the moving-horizon estimator by incorporating an unreliability index to mitigate the smearing effect of IFs.
    • To establish global detectability conditions and a cooperative decision-making strategy for guaranteed IF detection.

    Main Methods:

    • Design of a novel residual generator based on the moving-horizon estimator.
    • Regulation of weight matrices in the quadratic cost function using an unreliability index.
    • Application of matrix transformation and statistical theory for parameter estimation and fault analysis.
    • Development of a cooperative decision-making strategy for consolidated detection results.

    Main Results:

    • A novel moving-horizon estimator effectively suppresses the smearing effect of intermittent faults.
    • The proposed method achieves distributed detection of IFs with guaranteed accuracy in terms of appearance/disappearance times and affected nodes.
    • Global detectability conditions are established to prevent detection result collisions in sensor networks.
    • An illustrative example validates the feasibility and effectiveness of the developed fault detection strategy.

    Conclusions:

    • The developed method provides a robust solution for intermittent fault detection in linear stochastic sensor networks.
    • The novel approach enhances system reliability by accurately identifying fault occurrences and their impact.
    • The cooperative decision-making strategy ensures a single, reliable detection outcome, crucial for system control and maintenance.