Abstract
With the trend toward reusable launchers, there is a need to develop health monitoring systems for electromechanical actuators (EMAs) performing nozzle orientation. To tune such a health monitoring system, data sets reproducing EMA operation in healthy and faulty modes are needed. Besides, effect of production variability and thermal dependency should also be accounted for. In this paper, a systematic approach to determine an EMA model from which appropriate data sets can be generated is presented. The focus is on mechanical faults such as high friction level that may lead to jamming and excessive backlash. From available experimental data sets recorded on a fleet of EMA, gray box identification is used to estimate the friction parameters including their confidence level for the different EMAs. Production variability is then characterized by showing that each parameter estimate is represented by a Gaussian distribution at a given temperature. Next thermal effects are accounted for through a Gaussian process characterizing parameter variability with respect to temperature. Validation of the model is finally performed with EMA healthy operation data.
Issue Section:
Research Papers
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