Prestressed concrete continuous beam bridge construction monitoring system

Abstract

The invention discloses a prestressed concrete continuous beam bridge construction monitoring system which comprises a data acquisition module, a preprocessing module, a database module, a data processing module and a data output module. The preprocessing module is used for denoising and enhancing the real-time image data; the data processing module is used for monitoring abnormal data in the construction process of the beam bridge and generating a warning report when the abnormal data exist; according to the method, the layout during binding of the steel bars is analyzed firstly, the minimum monitoring area is set according to the sizes of the steel bars, and the minimum area can guarantee that the number of the steel bars changes in an existing error so as to guarantee monitoring effectiveness and representativeness during data acquisition; and then each monitoring area is individually monitored in a targeted manner, the reason of data abnormity during steel bar binding is deduced according to the monitoring result, and feedback is performed in a targeted manner, so that monitoring personnel are assisted to quickly lock hidden dangers existing in the steel bar binding process, and the detection efficiency is improved.

Description

Technical Field

[0001] The invention relates to the field of intelligence, and in particular to a prestressed concrete continuous beam bridge construction monitoring system. Background Art

[0002] Steel bars play a key bearing role in beam bridge structures. When the steel bars are unevenly laid, the beam bridge will produce uneven deformation during the stress process, which will affect its overall bearing capacity. Specifically, areas with sparse steel bars may be prematurely damaged due to insufficient bearing capacity, while areas with dense steel bars may produce stress concentration due to excessive bearing, which is also not conducive to the stability of the structure. In the process of making prestressed concrete beam bridge structural parts, a large number of steel bars are required as the skeleton. After the steel bars are laid, it is difficult to visually observe whether the layout of the steel bars is reasonable. During acceptance, evaluation and acceptance are often carried out through fixed-point measurements at arbitrary positions. However, the measurement data has great limitations, resulting in large errors between the evaluation results and the actual acceptance standards. In order to improve the construction quality of beam bridges, a prestressed concrete continuous beam bridge construction monitoring system is proposed. Summary of the invention

[0003] The technical problem to be solved by the present invention is: how to solve the problem that the existing safety protection system has a single protection type, resulting in poor protection effect and bringing certain impacts on the use of the safety protection system, and provides a prestressed concrete continuous beam bridge construction monitoring system.

[0004] The present invention solves the above technical problems through the following technical solutions. The present invention includes a data acquisition module, a preprocessing module, a database module, a data processing module, and a data output module; The data acquisition module is used to collect real-time data information of the beam bridge construction process, and the real-time data information includes real-time image data; The preprocessing module is used to receive real-time image data, and perform denoising and enhancement on the real-time image data; The database module is used to store historical data information during the construction of the beam bridge; The data processing module is used to receive real-time data information and historical data information, analyze the real-time data information in combination with the historical data information, monitor the abnormal data during the construction of the beam bridge, and generate a warning report when abnormal data exists; The data output module is used to receive and output warning reports.

[0005] Preferably, the specific processing process of the preprocessing module is: Import real-time image data; Divide the image evenly into multiple block units; Use the multithreaded programming library to create threads; Allocate the divided block units evenly to each thread; In each thread, the mean filtering algorithm and the histogram equalization algorithm are applied to the assigned block units for processing; After all threads have completed processing, the processed block units are merged into a complete image and output.

[0006] Preferably, the real-time data information also includes real-time size data, and the generation process of the warning report is specifically as follows: Collect real-time image data of steel bar bundling before pouring of beam bridge; Randomly establish a plurality of first virtual straight lines in the target direction; Collect the dimensions of a preset number M1 of steel bars on each first virtual straight line and obtain the average dimension Le; Use the formula Lr=Le / M1 to calculate the average gap between two adjacent steel bars; Collect the steel bar size Lv that is arranged vertically opposite to the target; Use the formula Lu=Lr / Lv to calculate the minimum monitoring size in the target direction; When the target direction is the length direction of the beam bridge, the first minimum monitoring size Lu1 is obtained; When the target direction is the width direction of the beam bridge, the second minimum monitoring size Lu2 is obtained; Establish multiple monitoring areas with Lu1 as the length dimension and Lu2 as the width dimension, wherein the length direction of the monitoring area is parallel to the length direction of the beam bridge, and the width direction of the monitoring area is parallel to the width direction of the beam bridge; Count the number of steel bars M2 in the length direction and the number of steel bars M3 in the width direction in each monitoring area respectively; Calculate the steel density P in each monitoring area. The specific calculation process is: P = M2·M3; Get the average density of the steel bars in the multiple monitoring areas ; When the average density <Preset threshold Q1 or average density >When the preset threshold value Q2 is reached, it indicates that there is an abnormality in the arrangement of the steel bars, and a first type of warning report is generated.

[0007] Preferably, when the average density preset threshold Q1 ≤ average density ≤preset threshold Q2, the generation process of the warning report further includes: Read monitoring area data; Import historical data to obtain the steel bar dimension data of multiple beam bridges in the length and width directions during the production process; Calculate the average length spacing dimension La in the length direction when multiple steel bars are bundled and the average width spacing dimension Lb in the width direction when multiple steel bars are bundled; Randomly acquire multiple steel bars in the target direction within the monitoring area; Randomly collect X steel bar spacings in the target direction, which are Lc1, Lc2, Lc3, ..., LcX; Calculate the difference E1 of the distance in the target direction. The specific calculation process is: ; When the difference E1>preset threshold Q3, it is abnormal data and marked; When the target direction is the length direction, Lx is La, and the first marking data is obtained; When the target direction is the width direction, Lx is Lb, and the second marking data is obtained; Counting the total number D1 of the first labeled data and the second labeled data; Use the formula E2=D1 / X to calculate the first anomaly ratio; When the first abnormal proportion E2>the preset threshold value Q4, it indicates that the local spacing of the steel bar bundling is abnormal, and a second type of warning report is generated.

[0008] Preferably, when the first abnormality proportion E2 ≤ the preset threshold value Q4, the generation process of the warning report further includes: Read abnormal data and obtain the abnormal data location; A first standard circle is made with the geometric center of the abnormal data position as the center and a preset size as the radius; Get any steel bar node in the first standard circle and establish a coordinate system with the length direction and width direction as coordinate directions; In the coordinate system, a virtual rectangular grid is made with La as the length unit and Lb as the width unit; Get any Y steel bar detection nodes; Collect the real-time size data Lz of the steel bar detection nodes and the nodes of the virtual rectangular network; When the real-time size data Lz> the preset threshold Q5, the node data is marked; Count the number of marked nodes M4; Use the formula E3=M4 / Y to calculate the second anomaly ratio of node data; When E3>preset threshold Q6, it indicates that the local spacing of the steel bar bundling is abnormal, and a second type of warning report is generated.

[0009] Preferably, the real-time data information also includes real-time vibration frequency data, and the generation process of the warning report also includes: Read monitoring area data; Collect the real-time vibration frequency data of the steel bars in the preset state in the monitoring area; they are Fe1, Fe2, Fe3, ..., Fen; Calculate the dispersion E4 of multiple vibration data. The specific calculation process is: ; Among them, Fei is the i-th real-time vibration frequency data, is the average vibration frequency data; When the dispersion E4>preset threshold Q7, it indicates that there is a problem with the tightness of the steel bar bundling, and a third type of warning report is generated.

[0010] Preferably, the data processing module is also used to analyze the real-time data information to infer whether there is any abnormality in the installation state of the template, and generate a feedback report when there is an abnormality; the real-time data information includes real-time image data and real-time size information, and the generation process of the feedback report is: Collect real-time image data after formwork installation during beam bridge production; Randomly obtain three first reference points on the template, and make virtual lines perpendicular to the template through the three first reference points respectively; A second reference point is obtained on each of the three virtual lines, and the distances between the three second reference points and the template are equal, which are all Lm; Make a virtual plane J through three second reference points; Randomly obtain a first detection point on the template; Collect the dimension data Lj of the first detection point from the virtual plane J; Calculate the deviation degree E5 of the first detection point data. The specific calculation process is: ; When the deviation degree E5>preset threshold Q8, it indicates data abnormality, and a second standard circle is made with the first detection point as the center and the preset size as the radius; Acquire N second verification points continuously and equidistantly on the second standard circle, and collect the sizes of the second verification points from the virtual plane J, which are Lg1, Lg2, Lg3, ..., LgN respectively; Sort the distances of the plurality of second verification points from the virtual plane J from large to small; Get the maximum size LgA and the minimum size LgB; Calculate the deformation degree E6 of the template. The specific calculation process is: ; When the deformation degree E6>preset threshold value Q9, it indicates that the template is locally deformed due to excessive force, and a first type of feedback report is generated.

[0011] Preferably, the process of generating the feedback report further includes: Obtaining the first detection point and the geometric center point of the template; Acquire a third detection point on the template, wherein the geometric center point of the template is located at the center point of the connecting line between the first detection point and the second detection point; A third standard circle is made with the third detection point as the center and the preset size as the radius, and the third standard circle is symmetrical with the second standard circle about the geometric center point of the template; Calculate the deformation degree E6` of the template at the third standard circle; Calculate the difference in deformation of the symmetrical position of the template E7. The specific calculation process is: ; When the difference degree E7 is less than the preset threshold value Q10, it indicates that the template is deformed due to compression, and a second type of feedback report is generated.

[0012] Preferably, the system further comprises a control module and an alarm module, wherein the alarm module is used to receive an alarm report and make an alarm action, and the control module is used to control the opening or closing of the alarm module.

[0013] Compared with the prior art, the present invention has the following advantages: the system first analyzes the layout of the steel bar bundling, and sets a minimum monitoring area in combination with the size of the steel bar. The minimum area can ensure that there is a change in the number of steel bars within the existing error, so as to ensure the effectiveness of monitoring and the representativeness of data collection; then each monitoring area is monitored separately in a targeted manner, and the cause of the abnormal data during steel bar bundling is inferred based on the monitoring results, and targeted feedback is given to assist monitoring personnel to quickly identify hidden dangers in the steel bar bundling process and improve detection efficiency; and further improve the construction quality of beam bridges to implement scientific and effective monitoring guidance strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is the overall module diagram of the present invention. DETAILED DESCRIPTION

[0015] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0016] like Figure 1As shown, this embodiment provides a technical solution: a prestressed concrete continuous beam bridge construction monitoring system, including a data acquisition module, a preprocessing module, a database module, a data processing module, and a data output module; The data acquisition module is used to collect real-time data information of the beam bridge construction process, and the real-time data information includes real-time image data; The preprocessing module is used to receive real-time image data, and perform denoising and enhancement on the real-time image data; The database module is used to store historical data information during the construction of the beam bridge; The data processing module is used to receive real-time data information and historical data information, analyze the real-time data information in combination with the historical data information, monitor the abnormal data during the construction of the beam bridge, and generate a warning report when abnormal data exists; The data output module is used to receive and output warning reports.

[0017] The system first analyzes the layout of the steel bar bundling, and sets the minimum monitoring area based on the size of the steel bars. This minimum area can ensure that there are changes in the number of steel bars within the existing error, so as to ensure the effectiveness of monitoring and representativeness of data collection; then each monitoring area is monitored separately, and the cause of abnormal data during steel bar bundling is inferred based on the monitoring results, and targeted feedback is provided to assist monitoring personnel to quickly identify hidden dangers in the steel bar bundling process and improve detection efficiency; and further improve the construction quality of beam bridges to implement scientific and effective monitoring guidance strategies.

[0018] Among them, the specific processing process of the preprocessing module is: Import real-time image data; Divide the image evenly into multiple block units; Use the multithreaded programming library to create threads; It should be noted that the multi-threaded programming library can be C++'s std::thread module, Python's threading module, etc., which are existing technologies and will not be described in detail.

[0019] Allocate the divided block units evenly to each thread; In each thread, the mean filtering algorithm and the histogram equalization algorithm are applied to the assigned block units for processing; After all threads have completed processing, the processed block units are merged into a complete image and output.

[0020] Among them, the real-time data information also includes real-time dimension data. The generation process of the warning report is as follows: Collect real-time image data of steel bar bundling before pouring of beam bridge; Randomly establish a plurality of first virtual straight lines in the target direction; Collect the dimensions of a preset number M1 of steel bars on each first virtual straight line and obtain the average dimension Le; Use the formula Lr=Le / M1 to calculate the average gap between two adjacent steel bars; Collect the steel bar size Lv that is arranged vertically opposite to the target; Use the formula Lu=Lr / Lv to calculate the minimum monitoring size in the target direction; When the target direction is the length direction of the beam bridge, the first minimum monitoring size Lu1 is obtained; When the target direction is the width direction of the beam bridge, the second minimum monitoring size Lu2 is obtained; Establish multiple monitoring areas with Lu1 as the length dimension and Lu2 as the width dimension. The length direction of the monitoring area is parallel to the length direction of the beam bridge, and the width direction of the monitoring area is parallel to the width direction of the beam bridge. Count the number of steel bars M2 in the length direction and the number of steel bars M3 in the width direction in each monitoring area respectively; Calculate the steel density P in each monitoring area. The specific calculation process is: P = M2·M3; Get the average density of steel bars in multiple monitoring areas ; When the average density <Preset threshold Q1 or average density >When the preset threshold value Q2 is reached, it indicates that there is an abnormality in the arrangement of the steel bars, and a first type of warning report is generated.

[0021] When implementing this embodiment, the layout of the steel bars during bundling is first analyzed, and a minimum monitoring area is set in combination with the size of the steel bars. The minimum area can ensure that there are changes in the number of steel bars within the existing error, so as to ensure the effectiveness of monitoring and representativeness of data collection; the steel bar density in the monitoring area is calculated; when the steel bar density is too large or too small, it indicates that there is an abnormality in the arrangement of the steel bars, which is specifically manifested as uniform arrangement of the steel bars but abnormal spacing. Targeted warnings are issued to assist monitors in carefully finding abnormal problems, thereby improving monitoring efficiency and further improving the quality of prestressed beam bridges.

[0022] There may be local anomalies in the arrangement of steel bars, which is manifested as the overall steel bar density is normal, but the steel bars are bundled too tightly or sparsely in some areas, which has a great impact on the bearing capacity of prestressed beam bridges. In order to improve the system monitoring capability, the following further technical solutions are proposed: Furthermore, when the average density preset threshold Q1 ≤ average density When the value is less than or equal to the preset threshold value Q2, the generation process of the warning report also includes: Read monitoring area data; Import historical data to obtain the steel bar dimension data of multiple beam bridges in the length and width directions during the production process; Calculate the average length spacing dimension La in the length direction when multiple steel bars are bundled and the average width spacing dimension Lb in the width direction when multiple steel bars are bundled; Randomly acquire multiple steel bars in the target direction within the monitoring area; Randomly collect X steel bar spacings in the target direction, which are Lc1, Lc2, Lc3, ..., LcX; Calculate the difference E1 of the distance in the target direction. The specific calculation process is: ; When the difference E1>preset threshold Q3, it is abnormal data and marked; When the target direction is the length direction, Lx is La, and the first marking data is obtained; When the target direction is the width direction, Lx is Lb, and the second marking data is obtained; Counting the total number D1 of the first labeled data and the second labeled data; Use the formula E2=D1 / X to calculate the first anomaly ratio; When the first abnormal proportion E2>the preset threshold value Q4, it indicates that the local spacing of the steel bar bundling is abnormal, and a second type of warning report is generated.

[0023] When this embodiment is implemented, detection positions are randomly selected at different locations in the monitoring area. At different detection positions, the spacing in the length direction and the spacing in the width direction of the steel bars are measured respectively, and then the number of measurement data that do not meet the construction requirements, that is, the number of abnormal data, is counted; when the number of abnormalities is large, it indicates that the steel bars are partially arranged unevenly, and targeted warnings are issued to improve the accuracy of system judgment.

[0024] When the above real-time example is executed, the detection position is randomly selected for detection. When the beam bridge components are built, the amount of steel bars arranged is large; when the abnormal positions of the local arrangement of steel bars are relatively concentrated, the random selection of data may cause the first abnormality to account for too large or too small proportion, affecting the judgment accuracy; To solve this problem, the following further solutions are proposed: Furthermore, when the first abnormality proportion E2 ≤ the preset threshold Q4, the generation process of the warning report further includes: Read abnormal data and obtain the abnormal data location; A first standard circle is made with the geometric center of the abnormal data position as the center and a preset size as the radius; Get any steel bar node in the first standard circle and establish a coordinate system with the length direction and width direction as coordinate directions; In the coordinate system, a virtual rectangular grid is made with La as the length unit and Lb as the width unit; Get any Y steel bar detection nodes; Collect the real-time size data Lz of the steel bar detection nodes and the nodes of the virtual rectangular network; When the real-time size data Lz> the preset threshold Q5, the node data is marked; Count the number of marked nodes M4; Use the formula E3=M4 / Y to calculate the second anomaly ratio of node data; When E3>preset threshold Q6, it indicates that the local spacing of the steel bar bundling is abnormal, and a second type of warning report is generated.

[0025] This embodiment establishes a virtual grid according to the standard arrangement size of the steel bars, and detects the steel bar nodes in the detection area; when the nodes of the virtual grid deviate greatly from the steel bar nodes, it means that there must be some steel bars in the detection area that have abnormal arrangement; by further judging the abnormal local spacing of the steel bars in this way, the judgment accuracy of the system can be improved, and the detection quality of the steel bar bundling process can be improved.

[0026] Furthermore, the real-time data information also includes real-time vibration frequency data, and the generation process of the warning report also includes: Read monitoring area data; Collect the real-time vibration frequency data of the steel bars in the preset state in the monitoring area; they are Fe1, Fe2, Fe3, ..., Fen; It should be noted that the preset state is to strike the steel bars at a preset position within the monitoring area with a preset striking force and a preset frequency.

[0027] Calculate the dispersion E4 of multiple vibration data. The specific calculation process is: ; Among them, Fei is the i-th real-time vibration frequency data, is the average vibration frequency data; When the dispersion E4>preset threshold Q7, it indicates that there is a problem with the tightness of the steel bar bundling, and a third type of warning report is generated.

[0028] This embodiment further analyzes the cause of abnormal local arrangement of steel bars by detecting the vibration frequency of the steel mesh under knocking; after the steel bars are bundled, the vibration frequencies of different positions of the steel mesh are detected; when the difference between the vibration frequencies at different positions is large, it indicates that the steel bars are vibrating abnormally; the cause of the abnormal vibration of the steel bars is that the steel bars are not tightly bundled and the force is uneven; during the vibration of the steel bars, the bundling nodes become loose, causing relative movement of the two steel bars at the two bundling locations; and then causing abnormal vibration of the steel bars; in this way, the abnormal state of the steel bars can be further judged and targeted reports can be issued, which can further improve the detection efficiency of monitoring personnel.

[0029] The data processing module is also used to analyze the real-time data information to infer whether there is any abnormality in the installation status of the template. If there is any abnormality, a feedback report is generated. The real-time data information includes real-time image data and real-time size information. The generation process of the feedback report is as follows: Collect real-time image data after formwork installation during beam bridge production; Randomly obtain three first reference points on the template, and make virtual lines perpendicular to the template through the three first reference points respectively; A second reference point is obtained on each of the three virtual lines, and the distances between the three second reference points and the template are equal, which are all Lm; Make a virtual plane J through three second reference points; Randomly obtain a first detection point on the template; Collect the dimension data Lj of the first detection point from the virtual plane J; Calculate the deviation degree E5 of the first detection point data. The specific calculation process is: ; When the deviation degree E5>preset threshold Q8, it indicates data abnormality, and a second standard circle is made with the first detection point as the center and the preset size as the radius; Acquire N second verification points continuously and equidistantly on the second standard circle, and collect the sizes of the second verification points from the virtual plane J, which are Lg1, Lg2, Lg3, ..., LgN respectively; Sort the distances of the plurality of second verification points from the virtual plane J from large to small; Get the maximum size LgA and the minimum size LgB; Calculate the deformation degree E6 of the template. The specific calculation process is: ; When the deformation degree E6>preset threshold value Q9, it indicates that the template is locally deformed due to excessive force, and a first type of feedback report is generated.

[0030] When this embodiment is implemented, a virtual plane is set at a position parallel to the template, and dimensional data between different positions of the template and the virtual plane are collected. When there is an abnormality in the dimensional data, it indicates that the template is deformed, and the abnormal position is locked; the abnormal position is further detected to determine whether the cause of the abnormality is a defect in the template itself or a bending deformation; a circular area for detection is established at the abnormal position, and points are taken on the circular area to obtain dimensional data from different points to the virtual plane; when the maximum value of the dimension in the circular area deviates greatly from the minimum value of the dimension, it indicates that the cause of the abnormality is the deformation of the template, and the deformation of the template will cause abnormal grooves or protrusions in the concrete on the surface of the beam bridge, affecting the surface quality of the beam bridge; a feedback report is made to remind the staff to make timely adjustments to avoid affecting the beam bridge and improve the quality of the beam bridge.

[0031] Furthermore, the feedback report generation process also includes: Obtaining the first detection point and the geometric center point of the template; A third detection point is obtained on the template, wherein the geometric center point of the template is located at the center point of the connecting line between the first detection point and the second detection point; A third standard circle is made with the third detection point as the center and the preset size as the radius, and the third standard circle is symmetrical with the second standard circle about the geometric center point of the template; Calculate the deformation degree E6` of the template at the third standard circle; Calculate the difference in deformation of the symmetrical position of the template E7. The specific calculation process is: ; When the difference degree E7 is less than the preset threshold value Q10, it indicates that the template is deformed due to compression, and a second type of feedback report is generated.

[0032] This solution detects the symmetrical positions of the abnormal positions of the template; when the data at the symmetrical positions of the template are close to the data at the abnormal positions, it means that the template itself is bent due to squeezing on both sides during installation, and the size of the template needs to be adjusted; targeted feedback is provided to improve the monitoring efficiency and execution efficiency of the monitoring personnel, thereby improving the practicality of the system.

[0033] The system also includes a control module and an alarm module. The alarm module is used to receive an alarm report and make an alarm action, and the control module is used to control the opening or closing of the alarm module.

[0034] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0035] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0036] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A prestressed concrete continuous beam bridge construction monitoring system, characterized in that: It includes data acquisition module, preprocessing module, database module, data processing module and data output module; The data acquisition module is used to collect real-time data information of the beam bridge construction process, and the real-time data information includes real-time image data; The preprocessing module is used to receive real-time image data, and perform denoising and enhancement on the real-time image data; The database module is used to store historical data information during the construction of the beam bridge; The data processing module is used to receive real-time data information and historical data information, analyze the real-time data information in combination with the historical data information, monitor the abnormal data during the construction of the beam bridge, and generate a warning report when abnormal data exists; The data output module is used to receive and output warning reports.

2. A prestressed concrete continuous beam bridge construction monitoring system according to claim 1, characterized in that: The specific processing process of the preprocessing module is: Import real-time image data; Divide the image evenly into multiple block units; Use the multithreaded programming library to create threads; Allocate the divided block units evenly to each thread; In each thread, the mean filtering algorithm and the histogram equalization algorithm are applied to the assigned block units for processing; After all threads have completed processing, the processed block units are merged into a complete image and output.

3. A prestressed concrete continuous beam bridge construction monitoring system according to claim 1, characterized in that: The real-time data information also includes real-time size data. The generation process of the warning report is specifically as follows: Collect real-time image data of steel bar bundling before pouring of beam bridge; Randomly establish a plurality of first virtual straight lines in the target direction; Collect the dimensions of a preset number M1 of steel bars on each first virtual straight line and obtain the average dimension Le; Use the formula Lr=Le / M1 to calculate the average gap between two adjacent steel bars; Collect the steel bar size Lv that is arranged vertically opposite to the target; Use the formula Lu=Lr / Lv to calculate the minimum monitoring size in the target direction; When the target direction is the length direction of the beam bridge, the first minimum monitoring size Lu1 is obtained; When the target direction is the width direction of the beam bridge, the second minimum monitoring size Lu2 is obtained; Establish multiple monitoring areas with Lu1 as the length dimension and Lu2 as the width dimension, wherein the length direction of the monitoring area is parallel to the length direction of the beam bridge, and the width direction of the monitoring area is parallel to the width direction of the beam bridge; Count the number of steel bars M2 in the length direction and the number of steel bars M3 in the width direction in each monitoring area respectively; Calculate the steel density P in each monitoring area. The specific calculation process is: P = M2·M3; Get the average density of the steel bars in the multiple monitoring areas ; When the average density <Preset threshold Q1 or average density >When the preset threshold value Q2 is reached, it indicates that there is an abnormality in the arrangement of the steel bars, and a first type of warning report is generated.

4. A prestressed concrete continuous beam bridge construction monitoring system according to claim 3, characterized in that: When the average density preset threshold Q1 ≤ average density ≤preset threshold Q2, the generation process of the warning report further includes: Read monitoring area data; Import historical data to obtain the steel bar dimension data of multiple beam bridges in the length and width directions during the production process; Calculate the average length spacing dimension La in the length direction when multiple steel bars are bundled and the average width spacing dimension Lb in the width direction when multiple steel bars are bundled; Randomly acquire multiple steel bars in the target direction within the monitoring area; Randomly collect X steel bar spacings in the target direction, which are Lc1, Lc2, Lc3, ..., LcX; Calculate the difference E1 of the distance in the target direction. The specific calculation process is: ； When the difference E1>preset threshold Q3, it is abnormal data and marked; When the target direction is the length direction, Lx is La, and the first marking data is obtained; When the target direction is the width direction, Lx is Lb, and the second marking data is obtained; Counting the total number D1 of the first labeled data and the second labeled data; Use the formula E2=D1 / X to calculate the first anomaly ratio; When the first abnormal proportion E2>the preset threshold value Q4, it indicates that the local spacing of the steel bar bundling is abnormal, and a second type of warning report is generated.

5. A prestressed concrete continuous beam bridge construction monitoring system according to claim 4, characterized in that: When the first abnormality proportion E2≤preset threshold Q4, the generation process of the warning report further includes: Read abnormal data and obtain the abnormal data location; A first standard circle is made with the geometric center of the abnormal data position as the center and a preset size as the radius; Get any steel bar node in the first standard circle and establish a coordinate system with the length direction and width direction as coordinate directions; In the coordinate system, a virtual rectangular grid is made with La as the length unit and Lb as the width unit; Get any Y steel bar detection nodes; Collect the real-time size data Lz of the steel bar detection nodes and the nodes of the virtual rectangular network; When the real-time size data Lz> the preset threshold Q5, the node data is marked; Count the number of marked nodes M4; Use the formula E3=M4 / Y to calculate the second anomaly ratio of node data; When E3>preset threshold Q6, it indicates that the local spacing of the steel bar bundling is abnormal, and a second type of warning report is generated.

6. A prestressed concrete continuous beam bridge construction monitoring system according to claim 4 or 5, characterized in that: The real-time data information also includes real-time vibration frequency data, and the generation process of the warning report also includes: Read monitoring area data; Collect the real-time vibration frequency data of the steel bars in the preset state in the monitoring area; they are Fe1, Fe2, Fe3, ..., Fen; Calculate the dispersion E4 of multiple vibration data. The specific calculation process is: ； Among them, Fei is the i-th real-time vibration frequency data, is the average vibration frequency data; When the dispersion E4>preset threshold Q7, it indicates that there is a problem with the tightness of the steel bar bundling, and a third type of warning report is generated.

7. A prestressed concrete continuous beam bridge construction monitoring system according to claim 1, characterized in that: The data processing module is also used to analyze the real-time data information to infer whether there is any abnormality in the installation status of the template, and generate a feedback report when there is an abnormality; the real-time data information includes real-time image data and real-time size information, and the generation process of the feedback report is: Collect real-time image data after formwork installation during beam bridge production; Randomly obtain three first reference points on the template, and make virtual lines perpendicular to the template through the three first reference points respectively; A second reference point is obtained on each of the three virtual lines, and the distances between the three second reference points and the template are equal, which are all Lm; Make a virtual plane J through three second reference points; Randomly obtain a first detection point on the template; Collect the dimension data Lj of the first detection point from the virtual plane J; Calculate the deviation degree E5 of the first detection point data. The specific calculation process is: ； When the deviation degree E5>preset threshold Q8, it indicates data abnormality, and a second standard circle is made with the first detection point as the center and the preset size as the radius; Acquire N second verification points continuously and equidistantly on the second standard circle, and collect the sizes of the second verification points from the virtual plane J, which are Lg1, Lg2, Lg3, ..., LgN respectively; Sort the distances of the plurality of second verification points from the virtual plane J from large to small; Get the maximum size LgA and the minimum size LgB; Calculate the deformation degree E6 of the template. The specific calculation process is: ； When the deformation degree E6>preset threshold value Q9, it indicates that the template is locally deformed due to excessive force, and a first type of feedback report is generated.

8. A prestressed concrete continuous beam bridge construction monitoring system according to claim 7, characterized in that: The process of generating the feedback report further includes: Obtaining the first detection point and the geometric center point of the template; Acquire a third detection point on the template, wherein the geometric center point of the template is located at the center point of the connecting line between the first detection point and the second detection point; A third standard circle is made with the third detection point as the center and the preset size as the radius, and the third standard circle is symmetrical with the second standard circle about the geometric center point of the template; Calculate the deformation degree E6` of the template at the third standard circle; Calculate the difference in deformation of the symmetrical position of the template E7. The specific calculation process is: ； When the difference degree E7 is less than the preset threshold value Q10, it indicates that the template is deformed due to compression, and a second type of feedback report is generated.

9. A prestressed concrete continuous beam bridge construction monitoring system according to claim 1, characterized in that: It also includes a control module and an alarm module. The alarm module is used to receive an alarm report and make an alarm action, and the control module is used to control the opening or closing of the alarm module.

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