Wavelet analysis-based signal processing method
A technology of signal processing and wavelet analysis, applied in the field of signal processing, can solve problems such as susceptibility to noise interference, identification and judgment of the nature of vibration emission sources, etc., and achieve the effect of improving prediction accuracy
Inactive Publication Date: 2018-02-23
GUANGXI TEACHERS EDUCATION UNIV
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Problems solved by technology
At present, the most commonly used parameter analysis method in the method of analyzing vibration signals is extremely susceptible to noise interference, and ultimately has a great impact on the identification and judgment of the nature of the vibration emission source. New analysis methods are needed to effectively overcome this limitation of the parameter analysis method. shortcoming
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Embodiment Construction
[0016] The present invention will be further described below in conjunction with the examples, but not as a basis for limiting the present invention.
[0017] A signal processing method based on wavelet analysis, comprising the following steps:
[0018] S1. Load data preprocessing: According to the actual situation of the historical load, the wavelet function with tight support and high regularity is used to decompose the preprocessed actual historical load data series by three-level wavelet, and the prediction error is minimized as the standard. After several data experiments, the wavelet base of db4 is finally used to decompose it in three scales, and four subsequences dl, d2, d3 and e3 are obtained respectively, where e3 is a low-frequency sequence, and dl, d2 and d3 are high-frequency detail sequences;
[0019] S2. Regression analysis and prediction of base load components: For the low-frequency approximate sequence e3 reflecting the system base load and the high-frequency...
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The invention provides a wavelet analysis-based signal processing method. The method comprises the following steps of: S1, load data preprocessing: carrying out three-level wavelet decomposition on apreprocessed practical history load data by adoption of a wavelet function with compact support and high regularity according to the practical condition of a history load; S2, regression analysis andprediction of a base load component: respectively constructing corresponding regression analysis models to predict a low-frequency approximate sequence e3 and high-frequency detail components d3 and d2 reflecting a system base load; S3, trend extrapolation prediction of a variable component: predicting a d1 component which is strong in randomness and short in periodicity by adoption of a trend extrapolation prediction method which is good at ultra-short period sequence prediction; and S4, result analysis and correction: carrying out precision analysis of the prediction. According to the method, better load prediction methods such as wavelet analysis, regression analysis and the like are combined to form a new prediction model, so that optimization and mutual complementation are carried outto achieve the aim of further improving the prediction precision.
Description
technical field [0001] The invention relates to the technical field of signal processing, in particular to a signal processing method based on wavelet analysis. Background technique [0002] Signal processing has become an important part of contemporary science and technology. The purpose of signal processing is accurate analysis, correct diagnostic code compression and quantization, fast transmission and storage, accurate reconstruction or recovery, and for stable signals, processing The ideal tool is still Fourier analysis, but most of the signals encountered in practical applications are non-stationary, and wavelet analysis provides an effective processing tool for analyzing such non-stationary signals. At present, the most commonly used parameter analysis method in the method of analyzing vibration signals is extremely susceptible to noise interference, and ultimately has a great impact on the identification and judgment of the nature of the vibration emission source. Ne...
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Login to View More IPC IPC(8): G06K9/00
CPCG06F2218/06
Inventor 吴迪许贵林李玲胡宝清
Owner GUANGXI TEACHERS EDUCATION UNIV