Real-time model- and harmonics based actuator health monitoring

Kurzfassung

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.