Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 69, Issue 5, Pages 5257-5266Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2021.3084177
Keywords
Frequency estimation; Estimation; Fault diagnosis; Blades; Time-frequency analysis; Time-domain analysis; Interpolation; Fault diagnosis (FD); frequency estimation; gap metric; subspace method; unmanned aerial vehicle (UAV)
Categories
Funding
- Ministry of Science and Technology of the People's Republic of China [2020YFA0711200]
- National Natural Science Foundation of China [62073104]
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This article proposes a novel time-domain frequency estimation approach based on the subspace identification method and verifies its effectiveness in frequency estimation and fault diagnosis performance through numerical simulations and experimental measurements.
In this article, a novel time-domain frequency estimation approach is proposed based on the well-known subspace identification method. Differing from the fast Fourier transformation method, the nonlinear identification for frequency estimation is reformulated into the eigenvalue identification problem, which avoids the spectrum peak search. The recursive frequency estimation approach is proposed based on the updating/downdating of the Cholesky decomposition, where the extended observability matrix can be identified from a small matrix with lower computation cost. In addition, a gap metric-oriented performance indicator is proposed as a test statistic for fault detection as well as the evaluation of fault severity. The effectiveness of the proposed methods is verified for frequency estimation and fault diagnosis performance through numerical simulations and the experimental measurements from a laboratory unmanned aerial vehicle rig with partial blade damage.
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