CN113567247A - Bridge detection information management system - Google Patents
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Abstract
The invention discloses a bridge detection information management system which comprises a data acquisition module, a storage module, a use analysis module, a crack detection module, a crack analysis module, a crack prediction module and a central control module, wherein the data acquisition module transmits acquired bridge data information to the storage module, the central control module is used for managing a control center of the system, and the analysis module is used for analyzing bridge construction information and bridge use information to obtain a coherence coefficient
And a load influence stage C, and sending the analysis result to other modules, the crack analysis module calculates and analyzes the crack information and the coherence coefficient to obtain the crack degree G and the crack growth rate r of the crack, the crack prediction module predicts according to the received result to obtain the predicted crack degree, the crack detection module detects according to the predicted crack degree,the prediction can help the detection personnel to perform timely detection, so that the detection result is more accurate, and the crack is repaired in time.
Description
Technical Field
The invention relates to the technical field of information management, in particular to a bridge detection information management system.
Background
The bridge is used as an important carrier for connecting two position points with larger span, and the structure of each part is damaged and deteriorated to different degrees due to the effects of the environment, the erosion of harmful substances, vehicles, fatigue, human factors and the like and the continuous degradation of the performance of the material, particularly the surface of the bridge structure generates cracks, the forming process of the surface cracks in different directions and the degree of damage to the bridge structure are also different; in the prior art, a plurality of traditional detection technologies exist, for example, whether main components of a bridge have cracks or are damaged or not is detected by naked eyes or auxiliary tools (such as bridge inspection vehicles, telescopes, unmanned aerial vehicles and the like), but a plurality of defects exist in a method of artificial detection, such as high operational difficulty, low efficiency, poor integrity, high risk factor and high technical communication difficulty; the method has the advantages that the method cannot detect the cracks in time when the cracks are about to be generated and small cracks are generated, so that the cracks can be detected only when the cracks become larger along with the passage of time, and cannot repair the bridge in time, so that the safety problem is caused; the detection blind area can be left in the detection process due to the limitations of the detection means and the detection method, in order to improve the accuracy of detection of cracks on the bridge, the positions of the cracks on the bridge are mainly detected, scientific basis is provided for maintenance of the bridge, reasonable maintenance and reinforcement methods are adopted in due time, the service life of the bridge is prolonged, the bearing capacity of the bridge is improved, and dangers caused by untimely detection are avoided.
Disclosure of Invention
In view of the above situation, and in order to overcome the defects of the prior art, an object of the present invention is to provide a bridge detection information management system, which can analyze bridge usage information of different location acquisition points by using an analysis module to obtain load influence progression, analyze detected cracks by using a crack analysis module to obtain crack degrees of the cracks, and finally predict cracks of the same location acquisition points by using a crack prediction module.
The technical scheme of its solution is, a bridge detection information management system, including data acquisition module, storage module, use analysis module, crack detection module, crack analysis module, crack prediction module, central control module can use analysis module, crack analysis module and crack prediction module to come to predict the crack in the bridge structures through control, and the structure of bridge is detected by crack detection module again, and the concrete management process of system is as follows:
1) the data acquisition module sends the acquired bridge data information to the storage module, and the bridge data information comprises bridge use information, bridge construction information and bridge detection information;
2) the central control module calls the bridge construction information and the bridge use information from the storage module and sends the bridge construction information and the bridge use information to the use analysis module, the use analysis module analyzes the bridge construction information and the bridge use information to obtain a load influence series, and the specific calculation process is as follows:
firstly, using an analysis module to perform correlation analysis on a bridge structure according to bridge construction information to obtain coherence of position acquisition pointsThe coefficient phi is obtained, the position acquisition points are divided into N types, the position acquisition points are formed by different structures on the bridge, the bridge detection module detects the position acquisition points by taking the position acquisition points as a unit, the number of the position acquisition points containing the bridge piers is recorded as z, the number of the position acquisition points not containing the bridge piers is recorded as w, the middle point of each column in the z position acquisition points containing the bridge is taken as a central stress point, and the distance from each stress point scattered around the central stress point to the central stress point is taken as a vector
ki(i-1, 2, 3.. z) represents the number of stress points from the central stress point in one position acquisition point, and the inclination angle of the bridge is thetai(i ═ 1, 2, 3,. z), classifying z central stress points into n types of location acquisition points, with a specific analytical formula:
wherein the z position acquisition points and the stress points in each position acquisition point are numbered, ΦiRepresenting the coherence coefficient, G, of the i-th one of the z position acquisition pointsjDenotes the contact area, beta, of the stress point with the bridge structure in contactjThe included angle between the jth stress point and the central stress point in the ith position acquisition point is represented, phi values of z different position acquisition points are calculated, and the position acquisition points with the same phi value are classified into one type of position acquisition points;
dividing w position acquisition points not containing piers into m types of position acquisition points, wherein the total number of the acquired position acquisition points is divided into N types, namely m + N is equal to N;
thirdly, analyzing each type of position acquisition points of the N types of position acquisition points in the bridge structure by using an analysis module according to the using information of the bridge to obtain a load influence series C, wherein the load influence series represents the maximum influence in the type of position acquisition points, and the concrete process is as follows:
wherein t represents the detected interval duration, H represents all vehicle loads in a class of position acquisition points, P represents all crowd loads in a class of position acquisition points, phi represents all coherence coefficients in one position acquisition point, v represents the average speed of the vehicle at each position acquisition point, and the analysis module is used for sending the load influence series C obtained by analysis to the crack prediction module and sending the coherence coefficients phi to the crack analysis module;
3) the bridge detection module sends detected bridge detection information to the crack analysis module, the crack analysis module analyzes the bridge detection information, the bridge detection information comprises crack information and other detection information, the crack information comprises position information of a crack on a bridge structure, depth information, length, width and crack cross section image information, the crack analysis module analyzes the crack cross section image information by using an image analysis technology, the length of the crack is recorded as l, the width of the crack is recorded as w, the cracking degree G of the crack is calculated, the cracking degree is further analyzed to obtain the crack growth rate r, and the cracking degree G and the crack growth rate are sent to the crack prediction module;
4) the crack prediction module predicts the cracks on the same type of position acquisition points by utilizing the cracking degree G, the crack growth rate, the load influence series and the coherence coefficient of the crack on the same type of position acquisition points on which the crack is positioned on the bridge, and determines the predicted cracking degree of the crack
And further detecting the bridge structure by the crack detection module.
The crack analysis module in 3) analyzes the detected cracks, classifies the cracks according to the different collecting points of the positions where the cracks are located, the cracking degrees of the cracks on the collecting points at different positions are different due to different load influences, the crack analysis module analyzes according to the crack information and the coherence coefficient phi on the collecting points at the same position, and the crack growth rate is set as r;
and t represents the detection interval duration, the crack growth rate r is solved according to the existing crack information with different cracking degrees as original data, the crack grows along with the growth of the r in the time t, the cracking degree of the crack is increased, the cracking degree is divided into five grades, the different grades correspond to different repairing methods, and the crack analysis module sends the analysis result of the crack to the crack prediction module.
The crack prediction module receives the analysis result sent by the crack analysis module, uses the load influence series sent by the analysis module, and establishes a mathematical model according to the received analysis result to perform analysis prediction, wherein the specific analysis process is as follows:
the method comprises the following steps of 1, firstly, retrieving crack information, wherein the crack information comprises crack position acquisition point information, crack growth rate r and crack degree G, and retrieving bridge use information of position acquisition points corresponding to cracks in a time period with a detection interval t according to the crack information;
step 2, predicting the position acquisition points without the detected cracks according to the analysis results of the cracks acquired from the same type position acquisition points, and establishing a prediction model by using the cracking degrees of all the cracks and the corresponding bridge use information to obtain the predicted cracking degree of the cracks
The dynamic prediction formula is as follows:
obtaining a prediction result by solving a formula, namely predicting the cracking degree
Step 3, predicting cracking degree
The method is used for predicting cracks in acquisition points at the same type of positions, the crack prediction module sends prediction results to the crack detection module, and the crack detection module detects the bridge structure in time according to the prediction results and prevents and repairs the cracks in time.
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages;
1. the system has the advantages that the use analysis module analyzes the use information and the construction information of the bridge, the position acquisition points on the bridge are analyzed by utilizing an analysis technology to obtain different coherence coefficients phi, the position acquisition points on the bridge are classified into N types according to the phi, the load influence series C of the different types of position acquisition points is obtained through analysis, the analysis result is sent to the crack analysis module and the crack prediction module, the accuracy of bridge detection is improved through division of the position acquisition points of the bridge structure, and the detection personnel can perform timely crack detection conveniently.
2. The crack analysis module analyzes the cracks detected on the collection points at each type of positions by utilizing the analysis results and the crack information sent by the analysis module, the growth rate of the cracks is researched, the crack analysis module sends the analysis results of the cracks to the crack prediction module, different growth stages of the cracks are considered, and data are provided for the prediction process of the crack prediction module.
3. And finally, the crack prediction module performs crack prediction analysis on the acquisition points at the same positions according to the analysis result of the analysis module and the analysis result of the existing cracks by the crack analysis module, so that the analysis can help detection personnel to perform timely detection, and when the crack detection module performs targeted detection according to the prediction result, the detection result can be more accurate, the growth of the cracks can be prevented timely, and the cracks can be repaired timely.
Drawings
FIG. 1 is an overall block diagram of the system;
FIG. 2 is a flow chart of information in the present system;
FIG. 3 is an analysis diagram using an analysis module;
FIG. 4 is an analysis diagram of a fracture prediction module.
Detailed Description
The foregoing and other aspects, features and advantages of the invention will be apparent from the following more particular description of embodiments of the invention, as illustrated in the accompanying drawings in which reference is made to figures 1 to 4. The structural contents mentioned in the following embodiments are all referred to the attached drawings of the specification.
A bridge detection information management system comprises a data acquisition module, a storage module, a use analysis module, a crack detection module, a crack analysis module, a crack prediction module and a central control module, wherein the central control module can predict cracks in a bridge structure by controlling the use analysis module, the crack analysis module and the crack prediction module, and then the crack detection module detects the structure of the bridge, the detection of bridge quality problems can directly affect the service life of the bridge and the life safety of people, and the prior art adopts a manual inspection mode, although the detection technician can use the detection device to complete the detection, the detection result is excessively dependent on the technical level of the detection technician, a detection blind area exists, in order to improve the detection accuracy, the selection of the detection method is crucial, and the specific management process of the system is as follows:
1) the data acquisition module sends the acquired bridge data information to the storage module, and the bridge data information comprises bridge use information, bridge construction information and bridge detection information;
2) the central control module transfers bridge construction information and bridge use information from the storage module, and send to the use analysis module, the crack on the bridge is an important reason for influencing the bridge quality, in the process of detecting the crack, because the observation range of human naked eyes is limited and will lead to the existence of detection blind area, in order to be that the detection personnel carry out comprehensive detection to the bridge, use the analysis module through carrying out analysis to the bridge construction information, divide the position acquisition point that the structure on the bridge corresponds, when gathering the detection information, just can avoid the existence of blind area, also can make things convenient for the prediction of crack prediction module, use the analysis module to carry out analysis to bridge construction information and bridge use information and obtain the load influence progression, concrete calculating process is as follows:
firstly, carrying out correlation analysis on a bridge structure by using an analysis module according to bridge construction information to obtain a coherence coefficient phi of position acquisition points, dividing the position acquisition points into N types, wherein the position acquisition points are formed by different structures on the bridge, classifying the positions detected on the bridge for comprehensively detecting cracks on the bridge and avoiding the existence of blind areas, detecting by using the position acquisition points as a unit by using a bridge detection module, recording the number of the position acquisition points containing piers as z, recording the number of the position acquisition points not containing piers as w, using the middle point of each column in the z position acquisition points containing bridges as a central stress point, and taking the distance from each stress point scattered around the central stress point to the central stress point as a vector
ki(i ═ 1, 2, 3.. z) represents the number of stress points from the central stress point in one position acquisition point, and the inclination angle of the bridge is thetai(i ═ 1, 2, 3, when having the domes in the bridge, there are different stress zones in the domes, and the characteristics of atress change along with the bending degree, the bridge inclination angle refers to the inside contained angle relative horizontal direction of stress point that has the holding power of bridge, and bridge inclination angle refers to the tangent line that uses the stress point as the contact point to make the bridge and the contained angle between the level earlier, classifies z central stress point as n class position acquisition point, and specific analytic formula is:
wherein, for z position acquisition pointsAnd stress points in each location acquisition point are numbered phiiRepresenting the coherence coefficient, G, of the i-th one of the z position acquisition pointsjDenotes the contact area, beta, of the stress point with the bridge structure in contactjThe included angle between the jth stress point and the central stress point in the ith position acquisition point is represented, phi values of z different position acquisition points are calculated, and the position acquisition points with the same phi value are classified into one type of position acquisition points;
step two, dividing w position acquisition points not comprising piers into m types of position acquisition points, classifying the position acquisition points comprising piers by utilizing a correlation relation phi, wherein in the w position acquisition points not comprising piers, if the positions of two position acquisition points are respectively adjacent to two position acquisition points comprising piers, when the phi of the two position acquisition points comprising piers of one position acquisition point is equal to the phi of the two position acquisition points comprising piers of the other position acquisition point, the two position acquisition points are classified into one type of position acquisition points, and the acquired position acquisition points are totally divided into N types, namely m + N is equal to N;
thirdly, analyzing each type of position acquisition points of the N types of position acquisition points in the bridge structure by using an analysis module according to the using information of the bridge to obtain a load influence series C, wherein the load influence series represents the maximum influence in the type of position acquisition points, and the load which can be borne by the bridge is reduced along with the increase of the service life, so that the load of different position acquisition points corresponding to each detection acquisition time period is reduced to different degrees, and the specific process is as follows:
wherein t represents the detected interval duration, H represents all vehicle loads in a class of position acquisition points, P represents all crowd loads in a class of position acquisition points, phi represents all coherence coefficients in one position acquisition point, v represents the average speed of the vehicle at each position acquisition point, and the analysis module is used for sending the load influence series C obtained by analysis to the crack prediction module and sending the coherence coefficients phi to the crack analysis module;
3) the bridge detection module sends detected bridge detection information to the crack analysis module, the crack analysis module analyzes the bridge detection information, the bridge detection information comprises crack information and other detection information, the crack information comprises position information of a crack on a bridge structure, depth information, length, width and crack cross section image information, the crack analysis module analyzes the crack cross section image information by using an image analysis technology, the length of the crack is recorded as l, the width of the crack is recorded as w, the cracking degree G of the crack is calculated, the cracking degree is further analyzed to obtain the crack growth rate r, and the cracking degree G and the crack growth rate r are sent to the crack prediction module;
4) the crack prediction module predicts the cracks on the same type of position acquisition points by using the cracking degree G, the crack growth rate, the load influence series and the coherence coefficient of the crack on the same type of position acquisition points on which the crack is positioned, and determines the predicted cracking degree of the crack
And further detecting the bridge structure by the crack detection module.
The crack analysis module in 3) analyzes the detected cracks, classifies the cracks according to the different collecting points of the positions where the cracks are located, the cracking degrees of the cracks on the collecting points at different positions are different due to different load influences, the crack analysis module analyzes according to the crack information and the coherence coefficient phi on the collecting points at the same position, and the crack growth rate is set as r;
t represents the time interval of detection, the crack growth rate r is solved according to the existing crack information with different cracking degrees as original data, the crack can grow along with r along with the time lapse in the time t, the cracking degree of the crack is increased, when the crack is too large, the bridge crack cannot be repaired, safety accidents are caused, the cracking degree is divided into five grades, different grades correspond to different repairing methods, and the crack analysis module sends the analysis result of the crack to the crack prediction module.
The crack prediction module receives the analysis result sent by the crack analysis module, uses the load influence series sent by the analysis module, and establishes a mathematical model according to the received analysis result to perform analysis prediction, wherein the specific analysis process is as follows:
the method comprises the following steps of 1, firstly, retrieving crack information, wherein the crack information comprises crack position acquisition point information, crack growth rate r and crack degree G, and retrieving bridge use information of position acquisition points corresponding to cracks in a time period with a detection interval t according to the crack information;
step 2, predicting the position acquisition points without the detected cracks according to the analysis results of the cracks acquired from the same type position acquisition points, and establishing a prediction model by using the cracking degrees of all the cracks and the corresponding bridge use information to obtain the predicted cracking degree of the cracks
The dynamic prediction formula is as follows:
obtaining a prediction result by solving a formula, namely predicting the cracking degree
Step 3, predicting cracking degree
Is the prediction of cracks in acquisition points at the same type of positionsAnd the crack prediction module sends the prediction result to the crack detection module, and the crack detection module detects the bridge structure in time according to the prediction result and prevents and repairs the crack in time.
The central control module is a center for information management, the central control module can call data from a database, send the data to the analysis module, the crack analysis module and the crack prediction module for analysis, send results to the storage module for storage, the bridge detection module detects all processes in the whole service life cycle of the bridge, the bridge detection module can detect according to the detection period of detection technicians, after the crack prediction module predicts, the bridge detection module can verify the predicted results through detection, and the accuracy of detection is improved through re-verification.
The data acquisition module is including artifical patrolling and examining, pressure acquisition, load collection, artifical patrolling and examining means that the testing personnel utilizes unmanned aerial vehicle, image acquisition device and naked eye inspect each structure of bridge, the image information of bridge can be gathered to the last image acquisition device that loads of unmanned aerial vehicle, crack and other quality safety problems on detecting the bridge through the analysis to image information again, what the data acquisition module gathered is the whole life cycle's of bridge information, and with information storage and storage module, storage module can be cloud repository, when the data information volume of gathering is difficult to the storage, the cloud repository can carry out data blocking storage.
When the system is used, the system mainly comprises a data acquisition module, a storage module, a use analysis module, a crack detection module, a crack analysis module, a crack prediction module and a central control module, wherein the data acquisition module transmits acquired bridge use information, bridge construction information and bridge detection information to the storage module, the central control module is a management control center of the system, the central control module retrieves the bridge construction information and the bridge use information from the storage module and transmits the bridge construction information and the bridge use information to the use analysis module, the use analysis module analyzes the bridge construction information and the bridge use information to obtain a coherence coefficient phi and a load influence series C, the use analysis module transmits the load influence series C to the crack prediction module and transmits the coherence coefficient phi to the crack analysis module, and the crack analysis module calculates and analyzes the crack information and the coherence coefficient to obtain the cracking degree G of a crack, and then further analyzing the cracking degree to obtain a crack growth rate r, and sending the cracking degree G and the crack growth rate r to a crack prediction module, wherein the crack prediction module predicts the cracking degree according to the received load influence series C, the crack growth rate r, the cracking degree G and the bridge use information to obtain the predicted cracking degree, the crack detection module detects similar position acquisition points according to the predicted cracking degree, and can help detection personnel to perform timely detection through the prediction result of the crack, so that the crack detection module performs targeted detection according to the prediction result, the detection result can be more accurate, the crack growth can be prevented timely, and the crack can be repaired timely.
While the invention has been described in further detail with reference to specific embodiments thereof, it is not intended that the invention be limited to the specific embodiments thereof; for those skilled in the art to which the present invention pertains and related technologies, the extension, operation method and data replacement should fall within the protection scope of the present invention based on the technical solution of the present invention.
Claims (5)
1. The utility model provides a bridge detection information management system, its characterized in that includes data acquisition module, storage module, uses analysis module, crack detection module, crack analysis module, crack prediction module, central control module, and central control module can use analysis module, crack analysis module and crack prediction module to predict the crack in the bridge structures through control, detects the structure of bridge by crack detection module again, and the concrete management process of system is as follows:
1) the data acquisition module sends the acquired bridge data information to the storage module, and the bridge data information comprises bridge use information, bridge construction information and bridge detection information;
2) the central control module calls the bridge construction information and the bridge use information from the storage module and sends the bridge construction information and the bridge use information to the use analysis module, the use analysis module analyzes the bridge construction information and the bridge use information to obtain a load influence series, and the specific calculation process is as follows:
firstly, carrying out correlation analysis on a bridge structure by using an analysis module according to bridge construction information to obtain a coherence coefficient phi of position acquisition points, dividing the position acquisition points into N types, wherein the position acquisition points are formed by different structures on the bridge, a bridge detection module detects by taking the position acquisition points as a unit, the number of the position acquisition points containing piers is recorded as z, the number of the position acquisition points not containing piers is recorded as w, the middle point of each pillar in the z position acquisition points containing the bridge is taken as a central stress point, and the distance from each stress point scattered around the central stress point to the central stress point is taken as a vector
ki(i ═ 1, 2, 3.. z) represents the number of stress points from the central stress point in one position acquisition point, and the inclination angle of the bridge is thetai(i ═ 1, 2, 3,. z), classifying z central stress points into n types of location acquisition points, with a specific analytical formula:
wherein the z position acquisition points and the stress points in each position acquisition point are numbered, ΦiRepresenting the coherence coefficient, G, of the i-th one of the z position acquisition pointsjDenotes the contact area, beta, of the stress point with the bridge structure in contactjThe included angle between the jth stress point and the central stress point in the ith position acquisition point is represented, phi values of z different position acquisition points are calculated, and the position acquisition points with the same phi value are classified into one type of position acquisition points;
dividing w position acquisition points not containing piers into m types of position acquisition points, wherein the total number of the acquired position acquisition points is divided into N types, namely m + N is equal to N;
thirdly, analyzing each type of position acquisition points of the N types of position acquisition points in the bridge structure by using an analysis module according to the using information of the bridge to obtain a load influence series C, wherein the load influence series represents the maximum influence in the type of position acquisition points, and the concrete process is as follows:
wherein t represents the detected interval duration, H represents all vehicle loads in a class of position acquisition points, P represents all crowd loads in a class of position acquisition points, phi represents all coherence coefficients in one position acquisition point, v represents the average speed of the vehicle at each position acquisition point, and the analysis module is used for sending the load influence series C obtained by analysis to the crack prediction module and sending the coherence coefficients phi to the crack analysis module;
3) the bridge detection module sends detected bridge detection information to the crack analysis module, the crack analysis module analyzes the bridge detection information, the bridge detection information comprises crack information and other detection information, the crack information comprises position information of a crack on a bridge structure, depth information, length, width and crack cross section image information, the crack analysis module analyzes the crack cross section image information by using an image analysis technology, the length of the crack is marked as 1, the width of the crack is marked as w, the cracking degree G of the crack is calculated, the cracking degree is further analyzed to obtain the crack growth rate r, and the cracking degree G and the crack growth rate r are sent to the crack prediction module;
4) the crack prediction module predicts the cracks on the same type of position acquisition points by utilizing the cracking degree G, the crack growth rate, the load influence series and the coherence coefficient of the crack on the same type of position acquisition points on which the crack is positioned on the bridge, and determines the predicted cracking degree of the crack
And further detecting the bridge structure by the crack detection module.
2. The bridge detection information management system according to claim 1, wherein the crack analysis module in 3) analyzes the detected cracks, classifies the cracks according to different collecting points at the positions of the cracks, the cracking degrees of the cracks at the collecting points at different positions are different due to different load influences, the crack analysis module analyzes according to the crack information and the coherence coefficient phi at the collecting points at the same position, and the crack growth rate is set as r;
and t represents the detection interval duration, the crack growth rate r is solved according to the existing crack information with different cracking degrees as original data, the crack grows along with the growth of the r in the time t, the cracking degree of the crack is increased, the cracking degree is divided into five grades, the different grades correspond to different repairing methods, and the crack analysis module sends the analysis result of the crack to the crack prediction module.
3. The bridge detection information management system according to claim 2, wherein the crack prediction module receives the analysis result sent by the crack analysis module, uses the load influence series sent by the analysis module, and establishes a mathematical model according to the received analysis result to perform analysis prediction, and the specific analysis process is as follows:
the method comprises the following steps of 1, firstly, retrieving crack information, wherein the crack information comprises crack position acquisition point information, crack growth rate r and crack degree G, and retrieving bridge use information of position acquisition points corresponding to cracks in a time period with a detection interval t according to the crack information;
step 2, byPredicting the position acquisition points without detected cracks by using the analysis results of the cracks acquired from the similar position acquisition points, and establishing a prediction model by using the cracking degrees of all the cracks and the corresponding bridge use information to obtain the predicted cracking degree of the cracks
The dynamic prediction formula is as follows:
obtaining a prediction result by solving a formula, namely predicting the cracking degree
Step 3, predicting cracking degree
The method is used for predicting cracks in acquisition points at the same type of positions, the crack prediction module sends prediction results to the crack detection module, and the crack detection module detects the bridge structure in time according to the prediction results and prevents and repairs the cracks in time.
4. The bridge inspection information management system of claim 1, wherein the central control module is a center of information management, the central control module can send the data from the database to the analysis module, the crack analysis module and the crack prediction module for analysis, and send the result to the storage module for storage, and the bridge inspection module inspects all the processes in the whole life cycle of the bridge.
5. The bridge detection information management system according to claim 1, wherein the data acquisition module comprises manual inspection, pressure acquisition and load acquisition, the manual inspection refers to that a detector utilizes an unmanned aerial vehicle, an image acquisition device and naked eyes to inspect each structure of the bridge, the image acquisition device mounted on the unmanned aerial vehicle can acquire image information of the bridge, and then cracks and other quality safety problems on the bridge are detected through analysis of the image information.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115389523A (en) * | 2022-08-26 | 2022-11-25 | 成都木格子装饰工程有限公司 | Building engineering supervision analysis system based on man-machine cooperation and visual inspection |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115389523A (en) * | 2022-08-26 | 2022-11-25 | 成都木格子装饰工程有限公司 | Building engineering supervision analysis system based on man-machine cooperation and visual inspection |
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Application publication date: 20211029 |