CN112362752A - Acoustic emission technology-based abnormal state monitoring and damage identification method for key stress part of swivel bridge - Google Patents
Acoustic emission technology-based abnormal state monitoring and damage identification method for key stress part of swivel bridge Download PDFInfo
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- CN112362752A CN112362752A CN202011153900.1A CN202011153900A CN112362752A CN 112362752 A CN112362752 A CN 112362752A CN 202011153900 A CN202011153900 A CN 202011153900A CN 112362752 A CN112362752 A CN 112362752A
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/14—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object using acoustic emission techniques
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Abstract
The invention provides a method for monitoring abnormal states and identifying damages of key stress parts of a swivel bridge based on an acoustic emission technology, which comprises the following steps: selecting key points, collecting signals, preprocessing the signals, deeply processing the signals, positioning abnormal stress points, comparing damaged sound waves, repairing the damaged sound waves, and archiving and warehousing the damaged sound waves. The beneficial effects are that: the abnormal state monitoring and damage identification method of the key stress part of the swivel bridge based on the acoustic emission technology is characterized in that an acoustic emission sensor is arranged at the key stress point of the bridge and is used for monitoring, so that a stress point damage signal can be conveniently and timely acquired, and the position of the damage stress point can be quickly positioned; and processing the acoustic wave signals of the damaged stress points, comparing the processed acoustic wave signals with historical cases of a resource library, quickly making a preprocessing scheme, and making an independent processing scheme for the difference points while performing conventional repair work.
Description
Technical Field
The invention relates to the technical field of bridge stress point damage detection, in particular to a method for monitoring abnormal states and identifying damage of key stress parts of a swivel bridge based on an acoustic emission technology.
Background
Most bridge failures occur during the operation period, and the main reasons for the failures are as follows: design defects, construction errors, poor operation management, hydrogeology and natural disasters. The main risk factors that specifically cause bridge dye failure are accidental collisions, construction errors and vehicle overloading, accounting for 25%, 21.9% and 13.5% of the total, respectively.
At present, health monitoring of a bridge structure mainly focuses on monitoring of the overall state of the structure, and usually, characteristic parameters such as modal frequency, vibration mode and the like for describing the health state of the structure are extracted based on structural dynamic response, so that the damage state of the bridge structure is judged and early warned on the basis, rapid positioning of the damage part is difficult to achieve, and a treatment plan cannot be made in time.
Disclosure of Invention
The invention aims to provide a method for monitoring abnormal states and identifying damage of key stress parts of a swivel bridge based on an acoustic emission technology, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a method for monitoring abnormal states and identifying damages of key stress parts of a swivel bridge based on an acoustic emission technology comprises the following steps:
the method comprises the following steps: selecting key points, selecting abnormal state monitoring points according to main stress positions of the bridge, monitoring abnormal states of the stress positions at a cable tower, a main beam, each inclined zipper and each bridge pier of the cable-stayed bridge, mounting an acoustic emission sensor at each selected stress position, and arranging an anti-electromagnetic interference device near a mounting point;
step two: signal collection, when fatigue conditions such as fracture, deformation, crack generation at a joint part and the like occur at a certain part of a bridge, an acoustic emission sensor arranged at the part can detect an acoustic emission signal, convert the acoustic emission signal into an electric signal and input the electric signal to a signal collector;
step three: signal preprocessing, after the signal collector collects the electric signals output by the acoustic emission sensor, the signal collector simply preprocesses the electric signals, if abnormal events (such as acoustic emission signals with high intensity are detected) occur in the preprocessing result, the acoustic emission signals are sent to an acoustic emission signal processor through a CAN bus transceiver for further analysis and processing;
step four: the method comprises the following steps of performing signal deep processing, wherein acoustic emission signals (obtained through an algorithm) sent by each acoustic emission data collector and received by an acoustic emission signal processor are further analyzed to obtain fatigue (process) conditions of each part of a bridge, and the analysis results are sent to a monitoring platform system through the Internet;
step five: positioning abnormal stress points, wherein a monitoring platform system receives health condition information of each part of the bridge sent by an acoustic emission signal processor through the Internet, displays the health condition of the bridge in real time, positions the part if an abnormal condition occurs at a certain part of the bridge, and generates an alarm signal to remind a staff on duty to perform further processing;
step six: the method comprises the steps of carrying out damage sound wave comparison, comparing a sound wave signal detected by an abnormal stress point with a sound wave signal with the highest historical similarity in a resource library, identifying the damage condition of the stress point, extracting an emergency treatment scheme in the resource library, carrying out deep analysis on the difference part of the sound wave signals, and setting a perfect treatment scheme;
step seven: repairing damage, namely monitoring the damaged stress point of the bridge in real time through an unmanned aerial vehicle, constructing and repairing by constructors according to a processing scheme, and writing repairing records in detail in the construction process;
step eight: and (4) archiving and warehousing, after repairing the damaged stress point, analyzing and recording the sound wave information of the damaged stress point, and transmitting the repaired scheme of the damaged stress point to a resource library for recording, so that the comparison of the damaged stress point in the future is facilitated and the pre-recorded plan is extracted in time.
Preferably, in the first step, the number of the acoustic emission sensors installed at each force bearing point is two, and the type of the acoustic emission sensors is selected to be RL 1.
Preferably, in step two, the signal acquisition frequency is once every ten seconds.
Preferably, in step eight, the archiving and warehousing is network communication writing such as a cloud server, and may also be writing through a local communication port (USB, internet access, etc.) of the module.
Compared with the prior art, the invention has the beneficial effects that:
1. the abnormal state monitoring and damage identification method of the key stress part of the swivel bridge based on the acoustic emission technology is characterized in that an acoustic emission sensor is arranged at the key stress point of the bridge and is used for monitoring, so that a stress point damage signal can be conveniently and timely acquired, and the position of the damage stress point can be quickly positioned;
2. the invention provides a method for monitoring abnormal states of key stress parts of a swivel bridge and identifying damage based on an acoustic emission technology, which is used for processing acoustic signals of damaged stress points and then comparing the processed acoustic signals with historical cases of a resource library, quickly making a preprocessing scheme, and making an independent processing scheme for difference points while performing conventional repair work.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that: a method for monitoring abnormal states and identifying damages of key stress parts of a swivel bridge based on an acoustic emission technology comprises the following steps:
the method comprises the following steps: selecting key points, selecting abnormal state monitoring points according to main stress positions of the bridge, monitoring abnormal states of the stress positions at a cable tower, a main beam, each inclined zipper and each bridge pier of the cable-stayed bridge, mounting an acoustic emission sensor at each selected stress position, and arranging an anti-electromagnetic interference device near a mounting point;
step two: signal collection, when fatigue conditions such as fracture, deformation, crack generation at a joint part and the like occur at a certain part of a bridge, an acoustic emission sensor arranged at the part can detect an acoustic emission signal, convert the acoustic emission signal into an electric signal and input the electric signal to a signal collector;
step three: signal preprocessing, after the signal collector collects the electric signals output by the acoustic emission sensor, the signal collector simply preprocesses the electric signals, if abnormal events (such as acoustic emission signals with high intensity are detected) occur in the preprocessing result, the acoustic emission signals are sent to an acoustic emission signal processor through a CAN bus transceiver for further analysis and processing;
step four: the method comprises the following steps of performing signal deep processing, wherein acoustic emission signals (obtained through an algorithm) sent by each acoustic emission data collector and received by an acoustic emission signal processor are further analyzed to obtain fatigue (process) conditions of each part of a bridge, and the analysis results are sent to a monitoring platform system through the Internet;
step five: positioning abnormal stress points, wherein a monitoring platform system receives health condition information of each part of the bridge sent by an acoustic emission signal processor through the Internet, displays the health condition of the bridge in real time, positions the part if an abnormal condition occurs at a certain part of the bridge, and generates an alarm signal to remind a staff on duty to perform further processing;
step six: the method comprises the steps of carrying out damage sound wave comparison, comparing a sound wave signal detected by an abnormal stress point with a sound wave signal with the highest historical similarity in a resource library, identifying the damage condition of the stress point, extracting an emergency treatment scheme in the resource library, carrying out deep analysis on the difference part of the sound wave signals, and setting a perfect treatment scheme;
step seven: repairing damage, namely monitoring the damaged stress point of the bridge in real time through an unmanned aerial vehicle, constructing and repairing by constructors according to a processing scheme, and writing repairing records in detail in the construction process;
step eight: and (4) archiving and warehousing, after repairing the damaged stress point, analyzing and recording the sound wave information of the damaged stress point, and transmitting the repaired scheme of the damaged stress point to a resource library for recording, so that the comparison of the damaged stress point in the future is facilitated and the pre-recorded plan is extracted in time.
In the first step, the number of the acoustic emission sensors installed at each stress point is two, and the type of the acoustic emission sensors is RL 1; in the second step, the signal acquisition frequency is once every ten seconds; in the step eight, the archiving and warehousing are network communication writing of the cloud server and the like, and can also be local communication port (USB, internet access and the like) writing of the module.
The invention has the advantages that: the abnormal state monitoring and damage identification method of the key stress part of the swivel bridge based on the acoustic emission technology is characterized in that an acoustic emission sensor is arranged at the key stress point of the bridge and is used for monitoring, so that a stress point damage signal can be conveniently and timely acquired, and the position of the damage stress point can be quickly positioned; and processing the acoustic wave signals of the damaged stress points, comparing the processed acoustic wave signals with historical cases of a resource library, quickly making a preprocessing scheme, and making an independent processing scheme for the difference points while performing conventional repair work.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (4)
1. A method for monitoring abnormal states and identifying damages of key stress parts of a swivel bridge based on an acoustic emission technology is characterized by comprising the following steps:
the method comprises the following steps: selecting key points, selecting abnormal state monitoring points according to main stress positions of the bridge, monitoring abnormal states of the stress positions at a cable tower, a main beam, each inclined zipper and each bridge pier of the cable-stayed bridge, mounting an acoustic emission sensor at each selected stress position, and arranging an anti-electromagnetic interference device near a mounting point;
step two: signal collection, when fatigue conditions such as fracture, deformation, crack generation at a joint part and the like occur at a certain part of a bridge, an acoustic emission sensor arranged at the part can detect an acoustic emission signal, convert the acoustic emission signal into an electric signal and input the electric signal to a signal collector;
step three: signal preprocessing, after the signal collector collects the electric signals output by the acoustic emission sensor, the signal collector simply preprocesses the electric signals, if abnormal events (such as acoustic emission signals with high intensity are detected) occur in the preprocessing result, the acoustic emission signals are sent to an acoustic emission signal processor through a CAN bus transceiver for further analysis and processing;
step four: the method comprises the following steps of performing signal deep processing, wherein acoustic emission signals (obtained through an algorithm) sent by each acoustic emission data collector and received by an acoustic emission signal processor are further analyzed to obtain fatigue (process) conditions of each part of a bridge, and the analysis results are sent to a monitoring platform system through the Internet;
step five: positioning abnormal stress points, wherein a monitoring platform system receives health condition information of each part of the bridge sent by an acoustic emission signal processor through the Internet, displays the health condition of the bridge in real time, positions the part if an abnormal condition occurs at a certain part of the bridge, and generates an alarm signal to remind a staff on duty to perform further processing;
step six: the method comprises the steps of carrying out damage sound wave comparison, comparing a sound wave signal detected by an abnormal stress point with a sound wave signal with the highest historical similarity in a resource library, identifying the damage condition of the stress point, extracting an emergency treatment scheme in the resource library, carrying out deep analysis on the difference part of the sound wave signals, and setting a perfect treatment scheme;
step seven: repairing damage, namely monitoring the damaged stress point of the bridge in real time through an unmanned aerial vehicle, constructing and repairing by constructors according to a processing scheme, and writing repairing records in detail in the construction process;
step eight: and (4) archiving and warehousing, after repairing the damaged stress point, analyzing and recording the sound wave information of the damaged stress point, and transmitting the repaired scheme of the damaged stress point to a resource library for recording, so that the comparison of the damaged stress point in the future is facilitated and the pre-recorded plan is extracted in time.
2. The acoustic emission technology-based abnormal state monitoring and damage identification method for key stress parts of swivel bridges according to claim 1, characterized in that: in the first step, the number of the acoustic emission sensors installed at each stress point is two, and the type of the acoustic emission sensors is selected to be RL 1.
3. The acoustic emission technology-based abnormal state monitoring and damage identification method for key stress parts of swivel bridges according to claim 1, characterized in that: in the second step, the signal acquisition frequency is once every ten seconds.
4. The acoustic emission technology-based abnormal state monitoring and damage identification method for key stress parts of swivel bridges according to claim 1, characterized in that: in the step eight, the archiving and warehousing are network communication writing of the cloud server and the like, and can also be local communication port (USB, internet access and the like) writing of the module.
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| CN202011153900.1A CN112362752A (en) | 2020-10-26 | 2020-10-26 | Acoustic emission technology-based abnormal state monitoring and damage identification method for key stress part of swivel bridge |
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| CN202011153900.1A CN112362752A (en) | 2020-10-26 | 2020-10-26 | Acoustic emission technology-based abnormal state monitoring and damage identification method for key stress part of swivel bridge |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113418986A (en) * | 2021-06-11 | 2021-09-21 | 安徽中科昊音智能科技有限公司 | Voiceprint detection system for bridge tunnel |
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| JP2016122361A (en) * | 2014-12-25 | 2016-07-07 | 西日本高速道路エンジニアリング四国株式会社 | Inspection information management system of road structure |
| US20180293255A1 (en) * | 2015-12-25 | 2018-10-11 | Fujifilm Corporation | Similar damage search device and a similar damage search method |
| CN109559025A (en) * | 2018-11-15 | 2019-04-02 | 安徽省交通控股集团有限公司 | A kind of bridge detecting/monitoring integrated health condition evaluation system and its application method |
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2020
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Patent Citations (6)
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| US20090070048A1 (en) * | 2004-07-15 | 2009-03-12 | Stothers Ian Mcgregor | Acoustic structural integrity monitoring system and method |
| CN101763053A (en) * | 2008-12-26 | 2010-06-30 | 上海交技发展股份有限公司 | Movable type bridge security detection and analysis management system |
| CN103776904A (en) * | 2011-12-30 | 2014-05-07 | 上海华魏光纤传感技术有限公司 | Bridge health monitoring system based on acoustic emission technology |
| JP2016122361A (en) * | 2014-12-25 | 2016-07-07 | 西日本高速道路エンジニアリング四国株式会社 | Inspection information management system of road structure |
| US20180293255A1 (en) * | 2015-12-25 | 2018-10-11 | Fujifilm Corporation | Similar damage search device and a similar damage search method |
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