Linear EMA HM Using Oil Detection

Current health monitoring descriptions often base on assumptions on how a degraded component behaves. Bearing and gear frequencies quite often play a role in this classic health monitoring. Even with a perfect monitoring, a positive result can only be given as soon as damage has occurred. The presented method detects the availability of oil in the actuator and can therefore predict upcoming damages that are caused by a lack of oil

Real-time model- and harmonics based actuator health monitoring

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

EMA Health Monitoring: An overview.

This paper presents an overview of the last decade of work on Electromechanical Actuators (EMA) Health Monitoring (HM) of the industrial cooperation between Liebherr- Aerospace in Lindenberg and the DLR Institute of System Dynamics and Control. The efforts on simulation of damage, (component) testing and development of HM algorithms will be presented

Automated Measurment of Backlash and Stiffness in Electro-Mechanical Flight Control Actuation

Electro-mechanical actuation of primary flight control surfaces is expected to increase the efficiency of future commercial aircraft. More specifically, the effort and cost of manufacture and maintenance will be reduced due to the omission of hydraulic supply and actuation systems. However, backlash is inherent to electro-mechanical actuation, whereas it does not occur in conventional hydraulic servo-actuation. Due to wear, backlash increases over the lifetime. With regard to electro-mechanical actuation of primary flight control surfaces, excessive backlash can cause detrimental effects such as limit cycle oscillations or, as a worst case, lead to jamming. Therefore, efficient and simple-to-deploy methods for monitoring backlash are sought after. This paper describes time domain methods for automated measurement of backlash and stiffness that use available sensor signals of an electro-mechanical aileron actuation system. So far, feasibility of the methods has been verified by experiments on appropriate test benches