CN103245728A - Holographic identification method and system for flaw damage of bridge - Google Patents
Holographic identification method and system for flaw damage of bridge Download PDFInfo
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Abstract
The invention provides a holographic identification method and system for a flaw damage of a bridge. The system comprises a low-frequency vibrating modal identification module, a high-frequency voiceprint identification module, and a flaw damage holographic identification module, wherein the low-frequency vibrating modal identification module is used for identifying whole damage information of the bridge by adopting a vibrating modal identification method; the high-frequency voiceprint identification module is used for identifying partial flaw damage information of the bridge by adopting a voiceprint identification method; and the flaw damage holographic identification module is used for establishing the relevance between the whole damage information and the partial flaw damage information to form a holographic performance evolution state of the bridge. According to the holographic identification method and system, the whole damage information and the partial flaw damage information of the bridge are related, so that the relevance of damage disintegration information of different scales and different levels of the bridge is realized, the holographic monitoring mode of the bridge safety is realized, the previous single-technology and one-sided monitoring is changed, and the holographic identification method and system have complete and profound technical advantages.
Description
Technical field
The present invention relates to bridge health detection technical field, relate in particular to a kind of bridge crackle and damage holographic recognition methods and system.
Background technology
Along with the fast development of science and technology and the strong growth of trip demand, the dual-purpose Longspan Bridge of many rail traffic bridges or highway and track traffic or be about to build up, for example: Yangtse River in Chongqing bridge, Wuhan Yangtze River Bridge.These bridges in use constantly are subjected to the erosion of external environments such as temperature, dust storm, and the influence of disaster such as the prolonged and repeated effect of vehicular load, vehicular impact and earthquake, flood; Therefore, increase along with tenure of use, the structure and material of these bridges constantly aging, fatigue effect significantly increases, thereby the natural accumulated damage that causes bridge member to occur in various degree damages with unexpected, so not only can shorten the serviceable life of bridge, but also serious threat is to people's life and property safety; Therefore, bridge is damaged just seem very importance of identification.At present, Damage detection of bridges is mainly contained multiple technologies such as strain monitoring, deflection monitoring, the identification of power mode, acoustic emission detection, alert and resourceful net monitoring, image recognition and bridge-checking vehicle, though these technology respectively have characteristics, but all be the damage identification at a certain yardstick and aspect, the main shortcomings such as the related deficiency of structural damage information that exist different scale and aspect, practical application effect is difficult as people's will.
Summary of the invention
In view of this, the invention provides a kind of bridge crackle and damage holographic recognition methods and system.The crackle degree of impairment of reflection bridge that can be more comprehensive and deep.
Bridge crackle provided by the invention damages holographic recognition system, comprising:
Low-frequency vibration mode identification module is used for adopting the mode of oscillation method of identification to identify the whole damage information of bridge;
The high frequency voiceprint identification module is used for adopting the Application on Voiceprint Recognition method to identify the localized cracks damage information of bridge;
Crackle damages holographic identification module, is used for setting up the related of described whole damage information and localized cracks damage information, forms the holographic performance evolution state of described bridge.
Further, also comprise:
The signal transducer group comprises: a plurality of signal transducers are used for measuring bridge under the excitation of driving source, the low-frequency vibration signal that produces in the vehicle-bridge coupling power process and local sounding high-frequency signal;
Described low-frequency vibration mode identification module is used for obtaining described low-frequency vibration signal, and according to the natural frequency of vibration of described low-frequency vibration signal identification bridge and the time-varying process of the described natural frequency of vibration, obtains overall performance attenuation trend and the rule of described bridge;
Described high frequency voiceprint identification module is used for obtaining described local sounding high-frequency signal, and according to the local vocal print feature of described local sounding high-frequency signal identification bridge and the variation of described local vocal print feature, obtains the localized cracks damage information of described bridge.
Further, described localized cracks damage information comprises: quantity, degree and the distributing position of localized cracks damage.
Further, described local vocal print feature comprises: the frequency spectrum of local vocal print.
Further, described driving source is the vehicle that moves naturally on the described bridge.
Bridge crackle provided by the invention damages holographic recognition methods, comprising:
The whole damage information of b, employing mode of oscillation method of identification identification bridge;
The localized cracks damage information of c, employing Application on Voiceprint Recognition method identification bridge;
D, set up the related of described whole damage information and localized cracks damage information, form the holographic performance evolution state of described bridge.
Further, before the described b, also comprise:
A, with on the bridge naturally the vehicle of operation be driving source, measure bridge under the excitation of driving source, the low-frequency vibration signal that produces in the vehicle-bridge coupling power process and local sounding high-frequency signal;
Described b comprises: obtain described low-frequency vibration signal, and according to the natural frequency of vibration of described low-frequency vibration signal identification bridge and the time-varying process of the described natural frequency of vibration, obtain overall performance attenuation trend and the rule of described bridge;
Described c comprises: obtain described local sounding high-frequency signal, and according to the local vocal print feature of described local sounding high-frequency signal identification bridge and the variation of described local vocal print feature, obtain the further local of described bridge, described localized cracks damage information comprises: quantity, degree and the distribution of localized cracks damage.
Further, described local vocal print feature comprises: the frequency spectrum of local vocal print.
Beneficial effect of the present invention:
The embodiment of the invention, at first adopt mode of oscillation method of identification and vocal print method of identification to identify whole damage information and the localized cracks damage information of bridge respectively, set up the related of whole damage information and localized cracks damage information then, form the holographic performance evolution state of bridge.Because it is the whole damage information of bridge is related with the localized cracks damage information, therefore realized damage decay information related of bridge different scale and different levels, realized the holographic monitoring pattern of bridge health, change single, the unilateral monitoring of conventional art, had more comprehensive, deep technical advantage.
Description of drawings
Below in conjunction with drawings and Examples the present invention is further described:
Fig. 1 is the structural representation that bridge crackle provided by the invention damages the embodiment of holographic recognition system.
Fig. 2 is the schematic flow sheet that bridge crackle provided by the invention damages the embodiment of holographic recognition methods.
Embodiment
Please refer to Fig. 1, is the structural representation that bridge crackle provided by the invention damages the embodiment of holographic recognition system.This system mainly comprises: signal transducer group 1, low-frequency vibration mode identification module 2, high frequency voiceprint identification module 3 and crackle damage holographic identification module 4.
Wherein, signal transducer group 1 comprises: a plurality of signal transducers, these signal transducers are distributed in the key position of bridge structure, these key positions can be the span centre, fulcrum, L/4, L/8 of bridge main beam and how much physical characteristicss undergo mutation the control cross section, can also be the root, turning point of bridge pier column, king-post and how much physical characteristicss undergo mutation the control cross section, and the quantity of signal transducer can suitably be adjusted as required.These signal transducers are mainly used in measuring bridge under the excitation of driving source, the low-frequency vibration signal that produces in the vehicle-bridge coupling power process and local sounding high-frequency signal, preferably, present embodiment is driving source with the vehicle that moves naturally on the bridge, thereby needn't the extrinsic motivated source, can realize the real-time and continuous holographic identification of bridge crackle damage.Preferably, signal transducer can adopt acceleration transducer to realize, also can adopt strain transducer as required.
Wherein, low-frequency vibration mode identification module 2, the main whole damage information that adopts mode of oscillation method of identification identification bridge, wherein the mode of oscillation method of identification refers to from the whole low-frequency vibration response data of the bridge structure of field measurement gained, determine the modal parameter of structure, comprising mode natural frequency, modal damping ratio, modal mass, modal stiffness and the vibration shape etc., and identify the overall performance damage evolution state of bridge structure according to the variation of modal parameter.。Concrete, low-frequency vibration module identification module 2 obtains low-frequency vibration signal from sensor groups 1, and according to the natural frequency of vibration of low-frequency vibration signal identification bridge and the time-varying process of the natural frequency of vibration, obtains overall performance attenuation trend and the rule of bridge.
Wherein, high frequency voiceprint identification module 3, the main localized cracks damage information that adopts Application on Voiceprint Recognition method identification bridge, wherein the Application on Voiceprint Recognition method refers to from the bridge structure local high-frequency vibratory response data of field measurement gained, determine the vocal print feature of structure partial, and identify the local damage state of bridge structure according to the probability stability variation of vocal print feature.Concrete, high frequency voiceprint identification module 3 is obtained local sounding high-frequency signal from sensor groups 1, and according to the local vocal print feature of local sounding high-frequency signal identification bridge (for example: frequency spectrum) and the variation of local vocal print feature, obtain the localized cracks damage information of bridge, these localized cracks damage informations comprise: quantity, degree and the distributing position of localized cracks damage, etc.Wherein, high frequency voiceprint identification module 3 mainly is based on the crackle damage and causes the sudden change of bridge structure local geometric physics acoustic mechanism and then cause local vocal print to change, in conjunction with geometry topological property that accelerometer distributes, come generation that the recognition structure localized cracks damages and development and located.
Wherein, crackle damages holographic identification module 4 and is mainly used in setting up the related of whole damage information and localized cracks damage information, i.e. influence of bridge member local rigidity being degenerated based on the localized cracks development concerns, the result that damage is identified according to localized cracks is correcting principle dynamical simulation model one by one, the variation of analytical calculation structural entity mode of oscillation feature also compares checking with integral body damage recognition result, form the holographic performance evolution state of bridge, namely set up the yardstick of striding between accumulation gradually and the whole sudden change that damages matter of amount of bridge structure localized cracks damage, stride the holographic corresponding relation of level.Concrete, crackle damages holographic identification module 4 on the identification basis of low-frequency vibration mode identification module 2 and high frequency voiceprint identification module 3, set up the local microcosmic of bridge, carefully see crackle damage quantity, program and the distribution correlation model between making a variation with structural entity macroscopic view kinematic behavior, the holographic performance evolution state of comprehensive distinguishing bridge.Further, crackle damages holographic identification module 4 and can also identify ultimate limit state critical point with the early warning bridge.Further, crackle damages that holographic identification module 4 can also (include but not limited to: holographic performance evolution state) report the bridge inspection and maintenance management decision system, behavior such as safeguarding for the bridge inspection and maintenance management decision system provides data to support with recognition result.
The bridge crackle of present embodiment damages holographic recognition system, because wherein each parts (include but not limited to: sensor groups 1, low-frequency vibration mode identification module 2, high frequency voiceprint identification module 3 and crackle damage holographic identification module 4) all can be changed, and can not influence it and continue the operation that links up, so system reliability is good.
The bridge crackle of present embodiment damages holographic recognition system, with the bridge structure microcosmic, carefully see the crackle damage information and macroscopical kinematic behavior decay information associates, set up the healthy holographic monitoring pattern of bridge structure, change single, the unilateral monitoring effect of conventional art, have more comprehensive, deep technical advantage.
Please refer to Fig. 2, is the schematic flow sheet that bridge crackle provided by the invention damages the embodiment of holographic recognition methods.This method flow is corresponding with above-mentioned system.Wherein, this method comprises:
Step S11, with on the bridge naturally the vehicle of operation be driving source, measure bridge under the excitation of driving source, the low-frequency vibration signal that produces in the vehicle-bridge coupling power process and local sounding high-frequency signal.
Wherein, step S11 is driving source with the vehicle that moves naturally on the bridge, therefore can avoid the extrinsic motivated source, can realize the continuous and real-time holographic identification of bridge crackle damage.In addition, step S11 can gather low-frequency vibration signal and the local sounding high-frequency signal that produces in the vehicle-bridge coupling power process by the key position signalization sensor at bridge by signal transducer.
The whole damage information of step S12, employing mode of oscillation method of identification identification bridge adopts the Application on Voiceprint Recognition method to identify the localized cracks damage information of bridge.
Concrete, step S12 obtains low-frequency vibration signal from step S11, then according to the natural frequency of vibration of low-frequency vibration signal identification bridge and the time-varying process of the natural frequency of vibration, obtain overall performance attenuation trend and the rule of bridge; Simultaneously, step S12 obtains local sounding high-frequency signal from step S11, then according to the local vocal print feature of local sounding high-frequency signal identification bridge and the variation of local vocal print feature, obtains the localized cracks damage information of bridge.
Step S13, set up the related of whole damage information and localized cracks damage information, form the holographic performance evolution state of bridge.
By this step, with the bridge structure microcosmic, carefully see the crackle damage information and macroscopical kinematic behavior decay information associates, set up the healthy holographic monitoring pattern of bridge structure, change single, the unilateral monitoring effect of conventional art, have more comprehensive, deep technical advantage.
Explanation is at last, above embodiment is only unrestricted in order to technical scheme of the present invention to be described, although with reference to preferred embodiment the present invention is had been described in detail, those of ordinary skill in the art is to be understood that, can make amendment or be equal to replacement technical scheme of the present invention, and not breaking away from aim and the scope of technical solution of the present invention, it all should be encompassed in the middle of the claim scope of the present invention.
Claims (9)
1. a bridge crackle damages holographic recognition system, it is characterized in that: comprising:
Low-frequency vibration mode identification module is used for adopting the mode of oscillation method of identification to identify the whole damage information of bridge;
The high frequency voiceprint identification module is used for adopting the Application on Voiceprint Recognition method to identify the localized cracks damage information of bridge;
Crackle damages holographic identification module, is used for setting up the related of described whole damage information and localized cracks damage information, forms the holographic performance evolution state of described bridge.
2. bridge crackle as claimed in claim 1 damages holographic recognition system, it is characterized in that: also comprise:
The signal transducer group comprises: a plurality of signal transducers are used for measuring bridge under the excitation of driving source, the low-frequency vibration signal that produces in the vehicle-bridge coupling power process and local sounding high-frequency signal;
Described low-frequency vibration mode identification module is used for obtaining described low-frequency vibration signal, and according to the natural frequency of vibration of described low-frequency vibration signal identification bridge and the time-varying process of the described natural frequency of vibration, obtains overall performance attenuation trend and the rule of described bridge;
Described high frequency voiceprint identification module is used for obtaining described local sounding high-frequency signal, and according to the local vocal print feature of described local sounding high-frequency signal identification bridge and the variation of described local vocal print feature, obtains the localized cracks damage information of described bridge.
3. bridge crackle as claimed in claim 2 damages holographic recognition system, it is characterized in that: described localized cracks damage information comprises: quantity, degree and the distributing position of localized cracks damage.
4. bridge crackle as claimed in claim 2 damages holographic recognition system, it is characterized in that: described local vocal print feature comprises: the frequency spectrum of local vocal print.
5. bridge crackle as claimed in claim 2 damages holographic recognition system, it is characterized in that: described driving source is the vehicle that moves naturally on the described bridge.
6. a bridge crackle damages holographic recognition methods, it is characterized in that: comprising:
The whole damage information of b, employing mode of oscillation method of identification identification bridge;
The localized cracks damage information of c, employing Application on Voiceprint Recognition method identification bridge;
D, set up the related of described whole damage information and localized cracks damage information, form the holographic performance evolution state of described bridge.
7. bridge crackle damnification recognition method as claimed in claim 6 is characterized in that: before the described b, also comprise:
A, with on the bridge naturally the vehicle of operation be driving source, measure bridge under the excitation of driving source, the low-frequency vibration signal that produces in the vehicle-bridge coupling power process and local sounding high-frequency signal;
Described b comprises: obtain described low-frequency vibration signal, and according to the natural frequency of vibration of described low-frequency vibration signal identification bridge and the time-varying process of the described natural frequency of vibration, obtain overall performance attenuation trend and the rule of described bridge;
Described c comprises: obtain described local sounding high-frequency signal, and according to the local vocal print feature of described local sounding high-frequency signal identification bridge and the variation of described local vocal print feature, obtain the localized cracks damage information of described bridge.
8. bridge crackle damnification recognition method as claimed in claim 7, it is characterized in that: described localized cracks damage information comprises: quantity, degree and the distribution of localized cracks damage.
9. bridge crackle damnification recognition method as claimed in claim 7, it is characterized in that: described local vocal print feature comprises: the frequency spectrum of local vocal print.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105067239A (en) * | 2015-07-31 | 2015-11-18 | 电子科技大学 | Beam crack fault detection apparatus and apparatus based on frequency sweep frequency sweep excitation vibration |
| CN105738480A (en) * | 2016-02-05 | 2016-07-06 | 武汉大学 | Concrete gravity dam strong shock damaged part quick identification method based on frequency errors |
| CN105866250A (en) * | 2016-03-17 | 2016-08-17 | 北京工业大学 | Vibration-based identification method for cracks of ventilating vane |
| CN108376184A (en) * | 2018-01-05 | 2018-08-07 | 深圳市市政设计研究院有限公司 | A kind of method and system of bridge health monitoring |
| WO2021036638A1 (en) * | 2019-04-26 | 2021-03-04 | 深圳市豪视智能科技有限公司 | Bridge vibration detection method and related apparatus |
| 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 |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3867836A (en) * | 1973-03-26 | 1975-02-25 | Us Navy | Crack detection apparatus and method |
| CN101281117A (en) * | 2008-05-29 | 2008-10-08 | 上海交通大学 | Wide span rail traffic bridge damnification recognition method |
| CN101900708A (en) * | 2010-08-18 | 2010-12-01 | 哈尔滨工业大学 | Vibration and audio signal-based high-speed train track defect detecting method |
| CN102156168A (en) * | 2011-03-04 | 2011-08-17 | 赵永贵 | Bridge prestressing force pore path grouting defect detection method |
| US20120204646A1 (en) * | 2011-02-10 | 2012-08-16 | National Taiwan University Of Science And Technology | Method for analyzing structure safety |
-
2013
- 2013-05-09 CN CN201310168993.9A patent/CN103245728B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3867836A (en) * | 1973-03-26 | 1975-02-25 | Us Navy | Crack detection apparatus and method |
| CN101281117A (en) * | 2008-05-29 | 2008-10-08 | 上海交通大学 | Wide span rail traffic bridge damnification recognition method |
| CN101900708A (en) * | 2010-08-18 | 2010-12-01 | 哈尔滨工业大学 | Vibration and audio signal-based high-speed train track defect detecting method |
| US20120204646A1 (en) * | 2011-02-10 | 2012-08-16 | National Taiwan University Of Science And Technology | Method for analyzing structure safety |
| CN102156168A (en) * | 2011-03-04 | 2011-08-17 | 赵永贵 | Bridge prestressing force pore path grouting defect detection method |
Non-Patent Citations (2)
| Title |
|---|
| 严普强等: "工程中的低频振动测量与其传感器", 《振动、测试与诊断》 * |
| 刘殿中: "桥梁结构的损伤识别与定位方法", 《吉林建筑工程学院学报》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105067239A (en) * | 2015-07-31 | 2015-11-18 | 电子科技大学 | Beam crack fault detection apparatus and apparatus based on frequency sweep frequency sweep excitation vibration |
| CN105067239B (en) * | 2015-07-31 | 2017-10-27 | 电子科技大学 | The beam crack fault detection means and method vibrated based on swept frequency excitation |
| CN105738480A (en) * | 2016-02-05 | 2016-07-06 | 武汉大学 | Concrete gravity dam strong shock damaged part quick identification method based on frequency errors |
| CN105866250A (en) * | 2016-03-17 | 2016-08-17 | 北京工业大学 | Vibration-based identification method for cracks of ventilating vane |
| CN105866250B (en) * | 2016-03-17 | 2018-12-18 | 北京工业大学 | Ventilating vane method for crack based on vibration |
| CN108376184A (en) * | 2018-01-05 | 2018-08-07 | 深圳市市政设计研究院有限公司 | A kind of method and system of bridge health monitoring |
| WO2021036638A1 (en) * | 2019-04-26 | 2021-03-04 | 深圳市豪视智能科技有限公司 | Bridge vibration detection method and related apparatus |
| 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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