Multiple-stable-state stochastic resonance weak signal detection method based on wavelet and parameter compensation

Abstract

The invention discloses a multiple-stable-state stochastic resonance weak signal detection method based on wavelet and parameter compensation. The method comprises the following steps: implementing parameter compensation on a noise-containing weak signal, and multiplying a signal parameter, a noise parameter and system parameters by a compensation parameter to counteract the influence of a damping term so as to detect a high-frequency weak signal; implementing multiscale wavelet discrete transformation on the compensated signal to obtain multiple signals at different scale frequencies, adjusting the amplitude of the signal at each scale, and implementing reconstruction; implementing multiple-stable-state stochastic resonance treatment on the reconstructed signal so that each frequency section of a to-be-detected signal is enhanced, implementing band-pass filtering resynthesis on the output of each frequency section to obtain an enhanced multi-frequency weak signal, implementing envelope demodulation analysis on the disposed signal, and analyzing an envelope spectrogram to realize the detection on the weak signal. By applying the method, the energy of an output signal can be improved greatly; the multi-frequency weak signal submerged by a strong noise background is favorably extracted; the detection accuracy is high.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a multi-frequency weak signal extraction technology under strong noise background, in particular to a multi-frequency weak signal detection method based on wavelet transform and parameter compensation band-pass multi-stable stochastic resonance. technical background [0002] Weak signals are low-energy signals submerged in a strong noise background. In many fields such as mechanical fault diagnosis, communication, seismic exploration, oil exploration wells, and biomedicine, it is necessary to extract useful signals by detecting weak signals. Therefore, the detection of weak signals has always been a research hotspot. [0003] Since the concept of stochastic resonance (Stochastic Resonance, SR) was proposed by R. Benzi et al. in 1981, SR technology has been widely used in weak signal detection. Compared with traditional weak signal detection technology and m...

AI Technical Summary

Problems solved by technology

[0008] In fact, when dealing with weak signals with extremely low signal-to-noise ratios, the effect of bistable stochastic resonance often fails to meet our expected goals, and it is easy to cause inaccurate diagnostic results and even misdiagnosis.

Images