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

Method for pretreating bridge monitoring signals

A monitoring signal and preprocessing technology, which is applied in the direction of measuring devices, special recording/indicating devices, instruments, etc., can solve the problems that the optimization results depend on the initial value and it is difficult to achieve global optimization

Active Publication Date: 2015-09-09
GUANGZHOU UNIVERSITY
View PDF5 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The K-EMD method adding the Kriging interpolation method can effectively suppress the endpoint effect, but the K-EMD method uses the pattern search method to optimize the relevant model parameters θ, and its optimization results largely depend on the initial value of the parameter θ, which is difficult to achieve global optimization

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
  • Method for pretreating bridge monitoring signals
  • Method for pretreating bridge monitoring signals
  • Method for pretreating bridge monitoring signals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0059] The present application is further described in conjunction with the following examples.

[0060] The embodiment of the present application provides a preprocessing method for bridge monitoring signals, including using an EMD decomposition method (K-EMD) added with Kriging interpolation method to preprocess the bridge monitoring signals. The process of K-EMD involves the optimization of relevant model parameters θ. In the embodiment of the present application, particle swarm optimization (PSO) is used instead of the pattern search method adopted by the original K-EMD to optimize the relevant model parameters θ. The PSO method has the ability of global optimization, avoiding the trap of signal processing falling into the local optimum, and effectively ensuring that the value reaches the global optimum. Moreover, the PSO method does not need to set the initial value of the relevant model parameter θ, but only needs to determine its interval, and the signal to be analyzed ...

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 the bridge field, especially to a method for pretreating bridge monitoring signals. The method includes pretreating bridge monitoring signals with an EMD decomposition method with added Kriging interpolation, wherein particle swarm optimization (PSO) is employed to optimize related model parameter theta involved in a K-EMD process. PSO has overall optimization capability, prevents signal processing from being optimized partially, and ensures the value is overall optimal.

Description

technical field [0001] The present application relates to the field of bridges, in particular to a preprocessing method for bridge monitoring signals. Background technique [0002] The bridge structure health monitoring signal implies the health state information of the structure. Appropriate preprocessing of the signal can effectively improve the signal-to-noise ratio, so that the subsequent information mining can have better results and reflect the structural state faithfully. The GPS system can be used to monitor the health of the bridge structure. The obtained monitoring signal is a non-stationary data set, which contains complex interference information (such as long-period signals and noise). The GPS monitoring signal must be preprocessed to eliminate the interference information. In order to obtain the real dynamic characteristics of the bridge structure. The Empirical Mode Decomposition (EMD) method has unique advantages in non-stationary signal processing, but has...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G01D3/032
Inventor 饶瑞姜晓勇傅继阳刘爱荣张芝芳黄友钦黄永辉
Owner GUANGZHOU UNIVERSITY
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