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Journals / Turkish Journal of Electrical Engineering and Computer Science / 2014 / Cilt: 22 - Sayı: 2

Luenberger observer-based sensor fault detection: online application to DC motor

Alkan ALKAYA
İlyas EKER
Pages
363–370
Publication Date
2014-05-16
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The experimental results demonstrate that this approach could significantly detect the time and size of the faults.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Fault detection and diagnosis (FDD) are very important for engineering systems in industrial applications.
📊
Key Findings & Data:One of the most popular approaches is model-based fault detection.
💡
Conclusion & Impact:The experimental results demonstrate that this approach could significantly detect the time and size of the faults.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Fault detection · observer · DC motor

Abstract

Fault detection and diagnosis (FDD) are very important for engineering systems in industrial applications. One of the most popular approaches is model-based fault detection. Recently, many techniques have been proposed in the FDD area. However, there are still very few reported applications or real-time implementations of the schemes. This paper presents online sensor FDD based on the model-based approach using a Luenberger observer and experimental application on a permanent magnet DC motor. Different kinds of faults are simulated on the motor and experiments are performed to detect the faults. The experimental results demonstrate that this approach could significantly detect the time and size of the faults.

Özet

Fault detection and diagnosis (FDD) are very important for engineering systems in industrial applications. One of the most popular approaches is model-based fault detection. Recently, many techniques have been proposed in the FDD area. However, there are still very few reported applications or real-time implementations of the schemes. This paper presents online sensor FDD based on the model-based approach using a Luenberger observer and experimental application on a permanent magnet DC motor. Different kinds of faults are simulated on the motor and experiments are performed to detect the faults. The experimental results demonstrate that this approach could significantly detect the time and size of the faults.

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Cite This Article

ALKAYA, A., EKER, İ. (2014). Luenberger observer-based sensor fault detection: online application to DC motor. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 22 - Sayı: 2, 363–370. https://ajindex.com/articles/188533

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