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Project

A general strategy for load and parameter identification for helicopter main rotor systems

This PhD project assesses the problem of load and parameter identification for helicopter-related applications. The proposed solution is the use of a Virtual Sensing strategy which estimates unmeasured quantities by readily combining experimental and numerical data of the analyzed system. In particular, a Kalman-based methodology will be investigated and further developed with the aim to advance the state-of-the-art of this technique and explore its performance and feasibility for helicopter rotor applications. To this end, the applicability of the proposed strategies will be tested on three industrial case scenarios: i) design phase of the helicopter, ii) flight-test (validation and qualification), iii) operation (system monitoring). The final goal of this research project is to offer a potential industrial tool for the system identification problem improving the methodologies currently adopted from aerospace companies.
Date:1 Jan 2019 →  20 Aug 2022
Keywords:Kalman Filter, main rotor modeling, helicopters, inverse load and parameter identification
Project type:PhD project