Abstract
Tidal harmonic constants are necessary data for the evaluation of tidal model, tidal prediction and chart datum. Compared with the wavelet multi-scale analysis model, a new method is put forward to detect and locate tidal discrete and continuous gross error. Based on the properties of the wavelets, the wavelet suitable for detecting the gross error of tidal is selected. And taking db6 wavelet as an example, the feasibility and effectiveness of this method are proved by experiments. The results show that the method can not only simultaneously detect and locate discrete gross error and continuous gross based on high frequency information, and can detect and locate the systematic deviation caused by the zero drift according to the low frequency information. Experimental result shows that the method is more simple, the efficiency and accuracy of detecting and locating gross error are improved.
Highlights
The application of wavelet analysis is very extensive, and wavelet analysis mainly uses the self-similarity, multi-resolution analysis of wavelet function and the function of mathematical microscope to process nonstationary signals [1][2]
The point numbers of the five mutation values are 114, 250, 266, 492, and 650, corresponding to the point number that was previously added to the gross error, and their absolute value is greater than 3
In this example, after the tidal level signal is decomposed by 6 layers using the db6 wavelet, 5 coarse errors can be quickly and accurately detected based on the high frequency information d1
Summary
The application of wavelet analysis is very extensive, and wavelet analysis mainly uses the self-similarity, multi-resolution analysis of wavelet function and the function of mathematical microscope to process nonstationary signals [1][2]. The wavelet transform is used to detect and analyze the singularity of ECG signals [3]; the fault detection and diagnosis of machinery are performed; the image is compressed, merged, denoised and watermarked [4][5]. The most striking feature of non-stationary signals is that the statistical properties of the signal change over time. The observed tides level of the tide station is changed with time. F (t) is a non-periodic function and the statistical characteristics change with time, so the tide level signal is a non-stationary signal. The low-frequency subspace obtained for each decomposition can be repeatedly and repeatedly decomposed using a similar process.
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