Analytical redundancy can be realized by parameter estimation. If historical data are reliable and available at the moment, the parameter estimation problem can be solved as a matrix completion problem. An improved matrix completion algorithm is proposed in the paper, which is based on GROUSE (Grassmannian Rank-One Update Subspace Estimation) algorithm and is modified by adding weight factors to the optimization function. In the improved algorithm, a time dimensional subspace is used to analyze the whole data space and is updated by historical data of the recent few periods. Simulations using actual engine data proves that the approach is feasible for aeroengine analytical redundancy construction.
Matrix Completion Based Aeroengine Analytical Redundancy
2018-08-01
612901 byte
Conference paper
Electronic Resource
English
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