Subway tunnel segment service performance detection method based on wave velocity determination

Abstract

The present invention relates to a subway tunnel segment service performance detection method based on wave velocity determination. According to the method, on the basis of hollow tubular structure modality dispersion analysis based on a thin-walled shell theory, propagation laws and propagation velocities of various elastic waves in a tubular structure are determined; a wired testing system is adopted or a wired testing system is matched with an internet-of-things technology to reasonably set an acceleration and a velocity sensor; and vibration signals are dynamically collected through specific hammer and other pulse wave excitation manners, and frequency phase characteristics of the signals are determined through HHT (Hilbert-Huang transformation) and other signal post-treatment manners so as to extract wave velocities of specific bending waves and compression waves to determine a structure service performance between various detection points.

Description

technical field [0001] The invention is applicable to the health detection of hollow tubular structures such as subway tunnels and underground pipelines, and determines the service performance of the structure by testing wave velocity and elastic modulus, and specifically relates to a method for detecting service performance of subway tunnel segments based on wave velocity measurement. Background technique [0002] In recent years, my country's urban rail transit construction is in a stage of rapid development. According to the data released by the Ministry of Housing and Urban-Rural Development, as of 2009, about 50 rail transit lines are under construction in 15 cities including Beijing and Shanghai. It ranks first in the world, with an operating mileage of 1,154km; by 2015, 22 cities including Beijing, Shanghai, and Guangzhou will build 79 new rail transit lines, with a total investment of 882.003 billion yuan and a total operating mileage of 2,260km. The scale will rank fi...

AI Technical Summary

Problems solved by technology

[0004] Therefore, it is very important to detect the service status of structures. In the past, detection methods such as rebound hammers can only detect points, which are extremely inefficient and are not suitable for large-scale structure detection. Therefore, many scholars and technicians at home and abroad intend to Will integrate civil structure and information (microelectronic sensors, wireless self-organizing sensor network) and other disciplines to develop a health monitoring system to judge the service performance of the structure

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