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12 April 2021 Application of the sliding innovation filter for fault detection and diagnosis of an electromechanical system
Mohammad A. AlShabi, S. Andrew Gadsden, Mamdouh El Haj Assad, Bassam Khuwaileh
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Proceedings Volume 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX; 1175607 (2021) https://doi.org/10.1117/12.2587341
Event: SPIE Defense + Commercial Sensing, 2021, Online Only
Abstract
This brief work introduces the use of the relatively new sliding innovation filter in the field of fault detection and diagnosis. This important area is part of signal processing techniques that are widely used in industrial practice, telecommunications, optical systems, and robotics, to name a few. This filter overcomes robustness issues during faults caused by modeling uncertainties. This brief work explores the properties and quality of the filter outputs applied on an electromechanical system. The results are compared with the well-known and studied Kalman Filter.
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Mohammad A. AlShabi, S. Andrew Gadsden, Mamdouh El Haj Assad, and Bassam Khuwaileh "Application of the sliding innovation filter for fault detection and diagnosis of an electromechanical system", Proc. SPIE 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX, 1175607 (12 April 2021); https://doi.org/10.1117/12.2587341
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KEYWORDS
Filtering (signal processing)
Optical networks
Robotics
Signal processing
Systems modeling
Telecommunications
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