Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Weak signal detection of multi-scale noise-modulated stochastic resonance

A technology containing noisy signals and signals, which is applied in the field of weak signal detection of multi-scale noise-adjusted stochastic resonance, and can solve problems such as inability to perform frequency conversion at the same time, reduced time resolution of output signals, and ineffectiveness.

Inactive Publication Date: 2019-03-08
CHONGQING UNIV OF POSTS & TELECOMM
View PDF2 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since these techniques work directly in the frequency domain, the time resolution of the output signal may be reduced compared to the original signal, and simultaneous frequency translation cannot be performed if multiple frequency signals are detected
The second type of method uses scale normalization technology, which can avoid the problem of time-domain distortion, but it may not be effective for weak signals submerged in noise of different scales

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Weak signal detection of multi-scale noise-modulated stochastic resonance
  • Weak signal detection of multi-scale noise-modulated stochastic resonance
  • Weak signal detection of multi-scale noise-modulated stochastic resonance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The implementation of the present invention will be further described below in conjunction with the accompanying drawings and specific examples.

[0018] Step 1: The underdamped second-order stochastic resonance model is as follows:

[0019]

[0020] in for the noise, is a periodic signal, r is a damping coefficient, and U(x) is a potential function. Substitute into formula (1) to get:

[0021]

[0022] The following is a theoretical analysis of the output signal-to-noise ratio of the second-order stochastic resonance with small parameters. For simplicity, let r = 0, dx / dt=y, then formula (2) is transformed into:

[0023]

[0024] The output signal-to-noise ratio of the second-order enhanced stochastic resonance is obtained by derivation:

[0025]

[0026] The variation law of the second-order stochastic resonance signal-to-noise ratio with the noise intensity is compared with that of the first-order stochastic resonance. figure 1 Shown: Through th...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a weak signal detection method for multi-scale noise-regulated stochastic resonance, belonging to the signal processing field. Aiming at the problem that the output of generalstochastic resonance system does not resonate at multiple frequencies at the same time, the influence mechanism of multi-scale noise reduction on stochastic resonance is studied, and a wavelet packettransform (WPT)-based method for noise-tuned stochastic resonance (NTSR) is proposed. The noise inherent in the signal is tuned into multi-scale noise by WPT, so that the noise can be tuned more carefully. The method is based on wavelet packet transform (WPT). The new method is used to overcome the limitation of the traditional parameter adjustment method, stochastic resonance detection based onWPT multi-scale noise adjustment has a good performance in rotating machinery multi-transient fault signal detection, which has a certain guiding significance and practical value. The method can further improve the output signal-to-noise ratio and achieve multi-frequency detection.

Description

technical field [0001] The invention belongs to the related fields of weak signal detection and the like, and in particular relates to a weak signal detection method for adjusting stochastic resonance by multi-scale noise. Aiming at the problem that the output of the general stochastic resonance system does not resonate at multiple frequencies at the same time, the influence mechanism of multi-scale noise reduction on stochastic resonance is studied, and a multi-scale noise based on Wavelet Packet Transform (WPT) is proposed. Adjust the stochastic resonance method to adjust the inherent noise in the signal into multi-scale noise through WPT, so as to adjust the noise more carefully. The new method is used to overcome the limitations of traditional parameter adjustment methods and realize the detection of stochastic resonance multi-frequency components. Background technique [0002] Weak signal detection is a comprehensive technology, involving information theory, nonlinear ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00
CPCG06F2218/06G06F2218/10
Inventor 贺利芳吴瑕江川王琳胡达云张天骐
Owner CHONGQING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com