A Health Monitoring (HM) method, optimized for low computational power realtime computers, is presented for the detection of faults in an Electro Mechanical Actuator (EMA). The method is based on 5 steps: 1. Pre-processing of the sensor data using Kalman filtering, 2. Generating residuals, 3. Selection of the usable data for detection, 4. Harmonic analysis to identify the faults and increase the sensitivity and 5. Decision making to classify the faults. The method is tested on simulation data.
Real-time model- and harmonics based actuator health monitoring
2017 ; Hamburg, Germany
2017-02-01
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
11.0401 Integrating Model-Based Diagnostics with Simulation for Real Time Health Monitoring
British Library Conference Proceedings | 2002
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