The cutoff angle frequency of the digital filter is configured by the user, and the order of the Butterworth filter is fixed to 10th order in consideration of the resource limitation and actual demand of the signal analysis module. Therefore, for different cutoff angle frequencies, it is necessary to construct a filter parameter sequence ak, bi in the recursive model before the filtering operation. The process of constructing this parameter sequence adopts bilinear transformation method, that is, the required 10th order Butterworth analog filter H(s) is obtained according to the configured cutoff angle frequency, and then obtained by bilinear transformation of S domain and Z domain. The digital filter system functions H(z) to determine the parameters required for the digitally filtered difference equation. The overall process of the digital analysis of the signal analysis module, the signal sequence Y(n) obtained after digital filtering will be used for the next step.
The overall frequency of the configurable digital filtering process, the introduction of synchronous resampling and the realization of the vibration signal of the wind turbine have a clear periodicity, and the discrete distribution of the spectral energy is concentrated at 1/2, 1, 2, 3 times the rotational speed. Equal frequency point. When the generator is in normal operation, its speed is fluctuating in a strict sense, especially in the rising and falling stages. The corresponding vibration signals in these states are non-stationary signals and do not directly satisfy the stationarity of the Fourier transform. Required, therefore not suitable for analysis using conventional spectrum analysis.
The signal acquisition board uses equal time difference sampling for the vibration signal. If the vibration signal obtained by sampling the time difference is directly subjected to FFT, the default vibration signal is a stationary signal, but due to the actual situation of the speed fluctuation, the obtained spectrum will have a frequency. The problem of domain leakage, that is, part of the energy of the signal at the multiplier point leaks to the entire spectrum, causing the measured value at the feature point to be smaller than the true value.
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