A method and device for extracting effective information from active periodic signals

Abstract

The invention provides a method and device for extracting effective information in an active cycle signal. The method comprises the steps of S1, based on a frequency domain frequency spectrum of an original signal, utilizing frequency spectrum values of adjacent frequency of effective frequency in the original signal to conduct preprocessing on the effective frequency to obtain a preprocessed frequency spectrum; S2, utilizing discrete wavelet transform to separate the preprocessed frequency spectrum into a high frequency component and a low frequency component; S3, reconstructing a high frequency envelope curve and a low frequency envelope curve of the high frequency component after analysis envelope to obtain an envelope curve of an overall frequency spectrum curve; S4, based on the envelope curve of the overall frequency spectrum curve, conducting noise rating and extracting an effective signal. According to the method for effectively extracting information in the active cycle signal, signal-to-noise ratio numerical values of different frequency signals can be obtained, and effective signal information which is in accordance with a production requirement is extracted in this way; the method and device can be applied to all cycle signals, and particularly have a good effect on influence rating of non-cycle noise which is not easy to separate in the cycle signal.

Description

technical field [0001] The invention relates to the field of periodic signal processing, and more specifically, to a method and device for extracting effective information from active periodic signals. Background technique [0002] At present, periodic signals are widely used, including vibration periodic signals, electromagnetic periodic signals, mechanical periodic signals, and so on. In most cases, periodic signals are composed of a main frequency signal and many harmonic signals. In practical applications, different compositional characteristics reflect different physical meanings. By mining the characteristics of different frequencies in these signals, many problems can be solved. practical application problems. However, in practical applications, signals are always affected by various noises. When the interference is complex, it becomes very difficult to extract effective signals, that is, signals with high SNR. [0003] With the further expansion of the human activi...

AI Technical Summary

Problems solved by technology

When the noise is very large, only the main frequency part of the signal is often extracted, or the harmonic components with large energy are extracted through experience. Sometimes the signal extracted according to experience is a signal that does not meet the quality requirements. There is no standard to guide the effective data. extract

Images