To monitor the normal working state, abrupt fault state and soft fault state of the electronic serves of UAVs, an on-line monitoring method is designed, which is based on Kalman filter and à trous algorithm is used in wavelet transform. Meanwhile, the simulation and verification of this method has been done according to actual observation data. The results indicate that using Kalman filter to estimate the state of electronic servo can efficiently track the actual output. Compared with SPRT (Sequential Probability Ratio Test), using wavelet transform to analysis the residual frequency can rapidly and efficiently detect and locate the fault of electronic servo.
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