Exposed reinforcement detection method and system for tunnel strong earthquake region lining

Abstract

The method comprises the following steps: according to a tunnel construction drawing, constructing a standard reinforcing steel bar structure of the tunnel strong earthquake area, determining a plurality of reinforcing steel bar sampling positions of the tunnel strong earthquake area, and respectively carrying out image sampling on each reinforcing steel bar sampling position, obtaining a plurality of regional reinforcing steel bar characteristics of the tunnel strong earthquake region, restoring a built reinforcing steel bar structure of the tunnel strong earthquake region based on the regional reinforcing steel bar characteristics, and identifying structural difference information between the built reinforcing steel bar structure and the standard reinforcing steel bar structure, according to the difference attribute corresponding to each piece of structural difference information, determining the rib leakage defect feature of the corresponding steel bar sampling position, generating and displaying a rib leakage defect report of the tunnel strong earthquake area, improving the quality of rib leakage identification work by using the convenience and accuracy of image identification, and effectively improving the working efficiency of workers.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel exposed rebar identification and detection, and in particular to a method and system for detecting exposed rebar in tunnel linings in strong earthquake zones. Background Art

[0002] Tunnel construction in high-seismic zones refers to areas with frequent seismic activity or high seismic intensity. When constructing tunnels in these areas, special consideration must be given to the impact of earthquakes on the tunnel structure. High-seismic zones generally refer to areas that have historically or geologically been prone to strong earthquakes and may experience high seismic intensity or frequent seismic activity. Due to the unique topography of high-seismic zones, the impact of earthquakes on the tunnel structure must be carefully considered when constructing tunnels in these areas. Tunnel safety requires precise seismic design, appropriate excavation methods, and strengthened support structures.

[0003] Rebar is a common load-bearing material used in tunnel construction. Generally speaking, the quality of the rebar affects the quality of the tunnel. Therefore, during tunnel construction, it is necessary to identify and detect whether the rebar has been improperly installed or misplaced due to construction or design issues, resulting in exposed, missing, or non-compliant rebar. Such issues can affect the strength and stability of the tunnel structure and even jeopardize its safety.

[0004] Therefore, the present invention provides a method and system for detecting exposed reinforcement in tunnel linings in strong earthquake zones. Summary of the Invention

[0005] The present invention provides a method and system for detecting exposed rebar in tunnel linings in strong earthquake zones, which performs image recognition and detection on rebar in tunnel strong earthquake zones, and timely locates positions that are correctly installed as required or have position deviations, thereby preventing improper installation of rebar from affecting tunnel quality.

[0006] The present invention provides a method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone, comprising: Step 1: Construct a standard steel bar structure in the tunnel's strong earthquake zone according to the tunnel construction drawings, and determine several steel bar sampling locations in the tunnel's strong earthquake zone; Step 2: performing image sampling on each of the steel bar sampling positions to obtain several regional steel bar features in the tunnel strong earthquake zone; Step 3: restoring the construction steel bar structure of the tunnel strong earthquake zone based on the regional steel bar characteristics, and identifying structural difference information between the construction steel bar structure and the standard steel bar structure; Step 4: Determine the reinforcement defect characteristics of the corresponding steel bar sampling position according to the difference attributes corresponding to each of the structural difference information, generate and display the reinforcement defect report of the tunnel strong earthquake zone.

[0007] In one practicable manner, The step 1 comprises: Step 11: screening a number of tunnel structural features included in the tunnel construction drawings, using the tunnel structural features to restore the overall tunnel structure of the tunnel, performing tunnel topography analysis on the overall tunnel structure, and locating the regional scope of the tunnel strong earthquake zone; Step 12: performing tunnel material analysis on a regional range in the overall tunnel structure, obtaining tunnel reinforcement characteristics in the tunnel strong earthquake zone in the overall tunnel structure, and constructing a standard reinforcement structure in the tunnel strong earthquake zone; Step 13: Determine the steel bar direction corresponding to each steel bar in the tunnel strong earthquake zone according to the standard steel bar structure, and regard the steel bar intersections between different steel bars as the steel bar sampling positions in the tunnel strong earthquake zone.

[0008] In one practicable manner, The step 2 comprises: Step 21: Controlling the camera equipment at the tunnel site to sample each of the steel bar sampling positions, obtaining a sampling image corresponding to each of the steel bar sampling positions, identifying the appearance of the steel bar corresponding to the steel bar sampling position in each of the sampling images, and establishing a steel bar appearance spatial array of the tunnel strong earthquake zone based on the steel bar appearance; Step 22: performing morphological recognition on each of the steel bar appearances in the steel bar appearance spatial array, treating the steel bar sampling positions with consistent steel bar morphology as the same sampling class, identifying a plurality of morphological inflection points corresponding to each of the steel bar morphologies, and performing pixel enhancement on the corresponding morphological inflection points in each of the sampled images to obtain inflection point details corresponding to each of the morphological inflection points; Step 23: Inputting each of the inflection point details into the corresponding steel bar appearance in the steel bar appearance spatial array for detail enhancement, respectively obtaining newly added details corresponding to each of the sampling classes, generating a plurality of steel bar detail information corresponding to the sampling classes, using the steel bar detail information to fine-tune the corresponding steel bar morphology, and drawing a steel bar morphology image corresponding to the steel bar sampling position; Step 24: Project each of the steel bar morphology images to obtain a number of steel bar basic features, adjust the steel bar basic features using each of the steel bar detail information, cluster the generated steel bar detail features, and regard the steel bar feature corresponding to each clustering result as the regional steel bar feature of the tunnel strong earthquake zone.

[0009] In one practicable manner, Also includes: The regional steel bar features corresponding to each array position are marked in the steel bar appearance space array, and the regional presentation features corresponding to each regional range in the tunnel strong earthquake zone are determined and displayed.

[0010] In one practicable manner, The step 3 comprises: Step 31: identifying several reinforcement construction methods included in the tunnel strong earthquake zone based on the regional reinforcement characteristics, and performing structural restoration simulation on the tunnel strong earthquake zone according to several regional reinforcement characteristics included in the reinforcement construction range corresponding to each reinforcement construction method to obtain the constructed reinforcement structure of the tunnel strong earthquake zone; Step 32: performing a pressure test on the constructed steel bar structure to obtain a positional compressive strength value corresponding to each steel bar sampling position in the tunnel strong earthquake zone, determining a standard compressive strength value corresponding to each steel bar sampling position based on the standard steel bar structure, and generating a type of difference information between the constructed steel bar structure and the standard steel bar structure; Step 33: superimposing the constructed steel bar structure onto the standard steel bar structure, screening the non-overlapping portion of the constructed steel bar structure and the standard steel bar structure, and determining two types of difference information between the constructed steel bar structure and the standard steel bar structure; Step 34: combining the first type of difference information and the second type of difference information corresponding to the same steel bar sampling position to generate a plurality of structural difference information between the constructed steel bar structure and the standard steel bar structure.

[0011] In one practicable manner, The step 4 comprises: Step 41: performing attribute recognition on each of the structural difference information to obtain the steel bar attributes corresponding to each of the steel bar sampling positions, and performing specification recognition on each of the structural difference information using AI to obtain the steel bar specifications corresponding to each of the steel bar sampling positions; Step 42: Based on the steel bar attributes and the steel bar specifications corresponding to each steel bar sampling location, identify the missing reinforcement attributes and the missing reinforcement degree corresponding to the steel bar sampling location, generate corresponding missing reinforcement defect features, locate each missing reinforcement defect feature respectively, generate and display the missing reinforcement defect report for the tunnel strong earthquake zone.

[0012] In one practicable manner, Also includes: Derivation of the tunnel safety level in the strong earthquake zone of the tunnel based on the reinforcement defect report; When the safety level is lower than the specified level, a safety warning is issued for the strong earthquake zone of the tunnel.

[0013] The present invention provides a system for detecting exposed reinforcement in tunnel linings in strong earthquake zones, comprising: A positioning sampling module is used to construct a standard steel bar structure in the tunnel's strong earthquake zone according to the tunnel construction drawings and determine several steel bar sampling locations in the tunnel's strong earthquake zone; A sampling execution module is used to perform image sampling on each of the steel bar sampling positions to obtain several regional steel bar features in the strong earthquake zone of the tunnel; A difference analysis module is used to restore the construction steel bar structure of the tunnel strong earthquake zone based on the regional steel bar characteristics and identify structural difference information between the construction steel bar structure and the standard steel bar structure; The missing reinforcement identification module is used to determine the missing reinforcement defect characteristics of the corresponding steel bar sampling position according to the difference attributes corresponding to each of the structural difference information, generate and display the missing reinforcement defect report of the tunnel strong earthquake zone.

[0014] In one practicable manner, The positioning sampling module includes: a range positioning unit, configured to screen a plurality of tunnel structural features included in the tunnel construction drawings, restore the overall tunnel structure of the tunnel using the tunnel structural features, perform tunnel topography analysis on the overall tunnel structure, and locate the regional range of the tunnel strong earthquake zone; a standard analysis unit, configured to perform tunnel material analysis on a regional range within the overall tunnel structure, obtain tunnel reinforcement characteristics of the tunnel strong earthquake zone within the overall tunnel structure, and construct a standard reinforcement structure for the tunnel strong earthquake zone; The positioning execution unit is used to determine the steel bar direction corresponding to each steel bar in the tunnel strong earthquake zone according to the standard steel bar structure, and regard the steel bar intersections between different steel bars as the steel bar sampling positions in the tunnel strong earthquake zone.

[0015] In one practicable manner, The sampling execution module includes: a spatial arrangement unit, configured to control a camera at the tunnel site to sample images at each of the steel bar sampling positions, obtain a sampled image corresponding to each of the steel bar sampling positions, identify the appearance of the steel bar corresponding to the steel bar sampling position in each of the sampled images, and establish a steel bar appearance spatial array of the tunnel strong earthquake zone based on the steel bar appearance; a detail enhancement unit, configured to perform morphological recognition on each of the steel bar appearances in the steel bar appearance spatial array, regard the steel bar sampling positions with consistent steel bar morphology as the same sampling class, identify a plurality of morphological inflection points corresponding to each of the steel bar morphologies, and perform pixel enhancement on the corresponding morphological inflection points in each of the sampled images to obtain inflection point details corresponding to each of the morphological inflection points; a morphology adjustment unit, configured to input each of the inflection point details into the corresponding steel bar appearance in the steel bar appearance spatial array for detail enhancement, obtain newly added details corresponding to each of the sampling classes, generate a plurality of steel bar detail information corresponding to the sampling classes, use the steel bar detail information to fine-tune the corresponding steel bar morphology, and draw a steel bar morphology image corresponding to the steel bar sampling position; The feature generation unit is used to project each of the steel bar morphology images respectively to obtain a number of steel bar basic features, adjust the steel bar basic features respectively using the steel bar detail information, cluster the generated steel bar detail features, and regard the steel bar feature corresponding to each clustering result as the regional steel bar feature of the tunnel strong earthquake zone.

[0016] The achievable beneficial effects of the above technical solution are: under the guidance of the tunnel construction drawings, a standard steel bar structure in the strong earthquake zone of the tunnel is constructed, and the structure is used to determine the steel bar sampling position in the strong earthquake zone, and further image sampling is performed on each steel bar sampling position to obtain the corresponding regional steel bar characteristics, and then the construction steel bar structure in the strong earthquake zone of the tunnel is restored, and then the structural difference information between the steel bar construction structure and the standard steel bar structure is identified to analyze the missing reinforcement defect characteristics at each steel bar sampling position, thereby constructing a missing reinforcement report for the strong earthquake zone of the tunnel. In this way, all steel bars in the strong earthquake zone can be identified and detected in a short time, and the convenience and accuracy of image recognition are used to improve the quality of missing reinforcement identification work, effectively improve the work efficiency of workers, ensure the safety of the workers' working environment, and avoid displacement during subsequent concrete pouring.

[0017] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0018] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 Schematic diagram of the workflow of a method for detecting exposed reinforcement in tunnel linings in a strong earthquake zone according to an embodiment of the present invention; Figure 2 The figure is a schematic diagram of the composition of a system for detecting exposed reinforcement bars in tunnel linings in strong earthquake zones according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0021] Example 1 This embodiment provides a method for detecting exposed reinforcement in tunnel linings in strong earthquake zones. Figure 1 As shown, including: Step 1: Construct a standard steel bar structure in the tunnel's strong earthquake zone according to the tunnel construction drawings, and determine several steel bar sampling locations in the tunnel's strong earthquake zone; Step 2: performing image sampling on each of the steel bar sampling positions to obtain several regional steel bar features in the tunnel strong earthquake zone; Step 3: restoring the construction steel bar structure of the tunnel strong earthquake zone based on the regional steel bar characteristics, and identifying structural difference information between the construction steel bar structure and the standard steel bar structure; Step 4: Determine the reinforcement defect characteristics of the corresponding steel bar sampling position according to the difference attributes corresponding to each of the structural difference information, generate and display the reinforcement defect report of the tunnel strong earthquake zone.

[0022] In this example, the standard steel reinforcement structure refers to the standard structure that is derived from the construction drawings and represents the required reinforcement structure in the tunnel's strong earthquake zone. In this example, the regional reinforcement feature represents the characteristics of the tunnel area located in a strong earthquake zone; In this example, the construction of the steel reinforcement structure represents the characteristics of the steel reinforcement at the site of the tunnel in the strong earthquake zone; In this example, the structural difference information represents the differences between the constructed steel structure and the standard steel structure; In this example, the missing reinforcement defect characteristics refer to the characteristics presented when the steel bars in the strong earthquake zone of the tunnel are leaking, including: exposed steel bars, missing steel bars, poorly welded steel bars, missing steel bars, and incorrectly installed steel bars.

[0023] The working principle and beneficial effects of the above technical solution are as follows: under the guidance of the tunnel construction drawings, a standard steel bar structure in the strong earthquake zone of the tunnel is constructed, and the structure is used to determine the steel bar sampling position in the strong earthquake zone. Further, image sampling is performed on each steel bar sampling position to obtain the corresponding regional steel bar characteristics, and then the construction steel bar structure in the strong earthquake zone of the tunnel is restored. Then, by identifying the structural difference information between the steel bar construction structure and the standard steel bar structure, the missing bar defect characteristics at each steel bar sampling position are analyzed, and a missing bar report for the strong earthquake zone of the tunnel is constructed. In this way, all steel bars in the strong earthquake zone can be identified and detected in a short time. The convenience and accuracy of image recognition are used to improve the quality of missing bar identification work, effectively improve the work efficiency of workers, ensure the safety of the workers' working environment, and avoid displacement during subsequent concrete pouring.

[0024] Example 2 Based on Example 1, the method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone, step 1, comprises: Step 11: screening a number of tunnel structural features included in the tunnel construction drawings, using the tunnel structural features to restore the overall tunnel structure of the tunnel, performing tunnel topography analysis on the overall tunnel structure, and locating the regional scope of the tunnel strong earthquake zone; Step 12: performing tunnel material analysis on a regional range in the overall tunnel structure, obtaining tunnel reinforcement characteristics in the tunnel strong earthquake zone in the overall tunnel structure, and constructing a standard reinforcement structure in the tunnel strong earthquake zone; Step 13: Determine the steel bar direction corresponding to each steel bar in the tunnel strong earthquake zone according to the standard steel bar structure, and regard the steel bar intersections between different steel bars as the steel bar sampling positions in the tunnel strong earthquake zone.

[0025] In this example, the tunnel structural characteristics represent the characteristics that will be present when the tunnel is completed; In this example, the rebar orientation indicates the installation orientation of a complete rebar during the construction of the tunnel.

[0026] The working principle and beneficial effects of the above technical solution are as follows: by utilizing the tunnel structural features contained in the tunnel construction drawings to restore the overall tunnel structure, then determining the strong earthquake zone in the tunnel through terrain analysis, and further combining tunnel material analysis to construct a standard steel bar structure in the strong earthquake zone of the tunnel. Finally, the steel bar intersections between different steel bars are regarded as the steel bar sampling locations in the strong earthquake zone of the tunnel. In this way, the locations where sampling is required can be screened out, effectively reducing the number of unnecessary sampling and improving the sampling quality and efficiency.

[0027] Example 3 Based on Example 1, the method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone, step 2, includes: Step 21: Controlling the camera equipment at the tunnel site to sample each of the steel bar sampling positions, obtaining a sampling image corresponding to each of the steel bar sampling positions, identifying the appearance of the steel bar corresponding to the steel bar sampling position in each of the sampling images, and establishing a steel bar appearance spatial array of the tunnel strong earthquake zone based on the steel bar appearance; Step 22: performing morphological recognition on each of the steel bar appearances in the steel bar appearance spatial array, treating the steel bar sampling positions with consistent steel bar morphology as the same sampling class, identifying a plurality of morphological inflection points corresponding to each of the steel bar morphologies, and performing pixel enhancement on the corresponding morphological inflection points in each of the sampled images to obtain inflection point details corresponding to each of the morphological inflection points; Step 23: Inputting each of the inflection point details into the corresponding steel bar appearance in the steel bar appearance spatial array for detail enhancement, respectively obtaining newly added details corresponding to each of the sampling classes, generating a plurality of steel bar detail information corresponding to the sampling classes, using the steel bar detail information to fine-tune the corresponding steel bar morphology, and drawing a steel bar morphology image corresponding to the steel bar sampling position; Step 24: Project each of the steel bar morphology images to obtain a number of steel bar basic features, adjust the steel bar basic features using each of the steel bar detail information, cluster the generated steel bar detail features, and regard the steel bar feature corresponding to each clustering result as the regional steel bar feature of the tunnel strong earthquake zone.

[0028] In this example, the steel bar appearance spatial array represents the result of spatially arranging the steel bar appearances according to the positional relationship between the steel bar sampling positions; In this example, the morphological inflection point represents the point at which the state of the steel bar changes as presented in the steel bar morphology; In this example, the inflection point details represent the details presented by the inflection points of the morphology; In this example, the reinforcement basic feature represents a feature that can only express the shape of the reinforcement.

[0029] The working principle and beneficial effects of the above technical solution are as follows: by using a shooting device to take image materials of the steel bar sampling position to obtain a sampling image of each steel bar sampling position, and then identifying the steel bar appearance contained in the sampling image to establish a steel bar appearance spatial array in the tunnel strong earthquake zone, and then classifying the steel bar sampling positions through morphological recognition, performing pixel enhancement on several morphological inflection points corresponding to a steel bar morphology, and determining the inflection point details of each morphological inflection point, and further fine-tuning the steel bar morphology by analyzing the newly added details of each sampling class, and then determining the basic characteristics of the steel bar by projection, and then adjusting the details of the basic characteristics of the steel bar, and finally using clustering to construct the regional steel bar characteristics of the tunnel strong earthquake zone. In this way, the steel bars in the tunnel strong earthquake zone can be deeply analyzed, their morphology and details can be determined, and then the regional steel bar characteristics of the tunnel strong earthquake zone can be established, which is convenient for subsequent identification and detection work.

[0030] Example 4 Based on Example 3, the method for detecting exposed reinforcement bars in tunnel linings in a strong earthquake zone further includes: The regional steel bar features corresponding to each array position are marked in the steel bar appearance space array, and the regional presentation features corresponding to each regional range in the tunnel strong earthquake zone are determined and displayed.

[0031] The working principle and beneficial effects of the above technical solution are as follows: by presenting the characteristics of each area in the tunnel's strong earthquake zone in the steel bar appearance spatial array, it is convenient for workers to analyze the safety of the area based on the characteristics of each area.

[0032] Example 5 Based on Example 1, the method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone, step 3, includes: Step 31: identifying several reinforcement construction methods included in the tunnel strong earthquake zone based on the regional reinforcement characteristics, and performing structural restoration simulation on the tunnel strong earthquake zone according to several regional reinforcement characteristics included in the reinforcement construction range corresponding to each reinforcement construction method to obtain the constructed reinforcement structure of the tunnel strong earthquake zone; Step 32: performing a pressure test on the constructed steel bar structure to obtain a positional compressive strength value corresponding to each steel bar sampling position in the tunnel strong earthquake zone, determining a standard compressive strength value corresponding to each steel bar sampling position based on the standard steel bar structure, and generating a type of difference information between the constructed steel bar structure and the standard steel bar structure; Step 33: superimposing the constructed steel bar structure onto the standard steel bar structure, screening the non-overlapping portion of the constructed steel bar structure and the standard steel bar structure, and determining two types of difference information between the constructed steel bar structure and the standard steel bar structure; Step 34: combining the first type of difference information and the second type of difference information corresponding to the same steel bar sampling position to generate a plurality of structural difference information between the constructed steel bar structure and the standard steel bar structure.

[0033] In this example, the process of structural restoration simulation is as follows: model simulation in virtual space; In this example, the position compressive strength value indicates the maximum pressure value that a steel bar sampling position can withstand when pressure is applied to it; In this example, one type of difference information represents the difference between the positional compressive strength value and the standard compressive strength value of a steel bar sampling location; In this example, the second type of difference information represents the difference between the actual structure and the standard structure of a steel bar sampling location.

[0034] The working principle and beneficial effects of the above technical solution are as follows: by utilizing the steel bar construction method in the tunnel's strong earthquake zone to restore the construction steel bar structure in the tunnel's strong earthquake zone, and then analyzing the positional compressive strength value of each steel bar sampling position through a pressure test, and analyzing the differences between the construction steel bar structure and the standard steel bar structure to determine the structural difference information between the construction steel bar structure and the standard steel bar structure. In this way, not only the differences between the construction steel bar structure and the standard steel bar structure can be determined, but also the different values ​​corresponding to each different point can be determined, which effectively improves the accuracy of missing reinforcement detection and achieves the effect of deep excavation and deep identification.

[0035] Example 6 Based on Example 1, the method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone, step 4, includes: Step 41: performing attribute recognition on each of the structural difference information to obtain the steel bar attributes corresponding to each of the steel bar sampling positions, and performing specification recognition on each of the structural difference information using AI to obtain the steel bar specifications corresponding to each of the steel bar sampling positions; Step 42: Based on the steel bar attributes and the steel bar specifications corresponding to each steel bar sampling location, identify the missing reinforcement attributes and the missing reinforcement degree corresponding to the steel bar sampling location, generate corresponding missing reinforcement defect features, locate each missing reinforcement defect feature respectively, generate and display the missing reinforcement defect report for the tunnel strong earthquake zone.

[0036] In this example, the reinforcement properties include: reinforcement appearance, reinforcement to non-reinforcement ratio, and reinforcement model.

[0037] The working principle and beneficial effects of the above technical solution are as follows: by performing attribute recognition and specification recognition on the structural difference information, the steel bar attributes and steel bar specifications of each steel bar sampling position are determined, and then the characteristics of the missing reinforcement defects at the steel bar sampling position are analyzed. Finally, each missing reinforcement position is located, and a corresponding missing reinforcement defect report is generated. In this way, each missing reinforcement attribute can be identified and quickly located, providing workers with an effective technical reference.

[0038] Example 7 Based on Example 1, the method for detecting exposed reinforcement bars in tunnel linings in a strong earthquake zone further includes: Derivation of the tunnel safety level in the strong earthquake zone of the tunnel based on the reinforcement defect report; When the safety level is lower than the specified level, a safety warning is issued for the strong earthquake zone of the tunnel.

[0039] In this example, the specified level is level 2, that is, tunnel strong earthquake zones at level 2 and below do not have the corresponding earthquake resistance.

[0040] The working principle and beneficial effects of the above technical solution are as follows: when the safety level of the tunnel in the strong earthquake zone is low, it indicates that the quality of the tunnel here is unqualified, and a corresponding safety warning is issued to remind workers to carry out quality reinforcement immediately.

[0041] Example 8 This embodiment provides a system for detecting exposed reinforcement in tunnel linings in strong earthquake zones. Figure 2 Shown, including: A positioning sampling module is used to construct a standard steel bar structure in the tunnel's strong earthquake zone according to the tunnel construction drawings and determine several steel bar sampling locations in the tunnel's strong earthquake zone; A sampling execution module is used to perform image sampling on each of the steel bar sampling positions to obtain several regional steel bar features in the strong earthquake zone of the tunnel; A difference analysis module is used to restore the construction steel bar structure of the tunnel strong earthquake zone based on the regional steel bar characteristics and identify structural difference information between the construction steel bar structure and the standard steel bar structure; The missing reinforcement identification module is used to determine the missing reinforcement defect characteristics of the corresponding steel bar sampling position according to the difference attributes corresponding to each of the structural difference information, generate and display the missing reinforcement defect report of the tunnel strong earthquake zone.

[0042] In this example, the standard steel reinforcement structure refers to the standard structure that is derived from the construction drawings and represents the required reinforcement structure in the tunnel's strong earthquake zone. In this example, the regional reinforcement feature represents the characteristics of the tunnel area located in a strong earthquake zone; In this example, the construction of the steel reinforcement structure represents the characteristics of the steel reinforcement at the site of the tunnel in the strong earthquake zone; In this example, the structural difference information represents the differences between the constructed steel structure and the standard steel structure; In this example, the missing reinforcement defect characteristics refer to the characteristics presented when the steel bars in the strong earthquake zone of the tunnel are leaking, including: exposed steel bars, missing steel bars, poorly welded steel bars, missing steel bars, and incorrectly installed steel bars.

[0043] The working principle and beneficial effects of the above technical solution are as follows: under the guidance of the tunnel construction drawings, a standard steel bar structure in the strong earthquake zone of the tunnel is constructed, and the structure is used to determine the steel bar sampling position in the strong earthquake zone. Further, image sampling is performed on each steel bar sampling position to obtain the corresponding regional steel bar characteristics, and then the construction steel bar structure in the strong earthquake zone of the tunnel is restored. Then, by identifying the structural difference information between the steel bar construction structure and the standard steel bar structure, the missing bar defect characteristics at each steel bar sampling position are analyzed, and a missing bar report for the strong earthquake zone of the tunnel is constructed. In this way, all steel bars in the strong earthquake zone can be identified and detected in a short time. The convenience and accuracy of image recognition are used to improve the quality of missing bar identification work, effectively improve the work efficiency of workers, ensure the safety of the workers' working environment, and avoid displacement during subsequent concrete pouring.

[0044] Example 9 Based on Example 8, the exposed rebar detection system for tunnel lining in a strong earthquake zone, the positioning sampling module, includes: a range positioning unit, configured to screen a plurality of tunnel structural features included in the tunnel construction drawings, restore the overall tunnel structure of the tunnel using the tunnel structural features, perform tunnel topography analysis on the overall tunnel structure, and locate the regional range of the tunnel strong earthquake zone; a standard analysis unit, configured to perform tunnel material analysis on a regional range within the overall tunnel structure, obtain tunnel reinforcement characteristics of the tunnel strong earthquake zone within the overall tunnel structure, and construct a standard reinforcement structure for the tunnel strong earthquake zone; The positioning execution unit is used to determine the steel bar direction corresponding to each steel bar in the tunnel strong earthquake zone according to the standard steel bar structure, and regard the steel bar intersections between different steel bars as the steel bar sampling positions in the tunnel strong earthquake zone.

[0045] In this example, the tunnel structural characteristics represent the characteristics that will be present when the tunnel is completed; In this example, the rebar orientation indicates the installation orientation of a complete rebar during the construction of the tunnel.

[0046] The working principle and beneficial effects of the above technical solution are as follows: by utilizing the tunnel structural features contained in the tunnel construction drawings to restore the overall tunnel structure, then determining the strong earthquake zone in the tunnel through terrain analysis, and further combining tunnel material analysis to construct a standard steel bar structure in the strong earthquake zone of the tunnel. Finally, the steel bar intersections between different steel bars are regarded as the steel bar sampling locations in the strong earthquake zone of the tunnel. In this way, the locations where sampling is required can be screened out, effectively reducing the number of unnecessary sampling and improving the sampling quality and efficiency.

[0047] Example 10 Based on Example 8, the exposed rebar detection system for tunnel lining in a strong earthquake zone, the sampling execution module includes: a spatial arrangement unit, configured to control a camera at the tunnel site to sample images at each of the steel bar sampling positions, obtain a sampled image corresponding to each of the steel bar sampling positions, identify the appearance of the steel bar corresponding to the steel bar sampling position in each of the sampled images, and establish a steel bar appearance spatial array of the tunnel strong earthquake zone based on the steel bar appearance; a detail enhancement unit, configured to perform morphological recognition on each of the steel bar appearances in the steel bar appearance spatial array, regard the steel bar sampling positions with consistent steel bar morphology as the same sampling class, identify a plurality of morphological inflection points corresponding to each of the steel bar morphologies, and perform pixel enhancement on the corresponding morphological inflection points in each of the sampled images to obtain inflection point details corresponding to each of the morphological inflection points; a morphology adjustment unit, configured to input each of the inflection point details into the corresponding steel bar appearance in the steel bar appearance spatial array for detail enhancement, obtain newly added details corresponding to each of the sampling classes, generate a plurality of steel bar detail information corresponding to the sampling classes, use the steel bar detail information to fine-tune the corresponding steel bar morphology, and draw a steel bar morphology image corresponding to the steel bar sampling position; The feature generation unit is used to project each of the steel bar morphology images respectively to obtain a number of steel bar basic features, adjust the steel bar basic features respectively using the steel bar detail information, cluster the generated steel bar detail features, and regard the steel bar feature corresponding to each clustering result as the regional steel bar feature of the tunnel strong earthquake zone.

[0048] In this example, the steel bar appearance spatial array represents the result of spatially arranging the steel bar appearances according to the positional relationship between the steel bar sampling positions; In this example, the morphological inflection point represents the point at which the state of the steel bar changes as presented in the steel bar morphology; In this example, the inflection point details represent the details presented by the inflection points of the morphology; In this example, the reinforcement basic feature represents a feature that can only express the shape of the reinforcement.

[0049] The working principle and beneficial effects of the above technical solution are as follows: by using a shooting device to take image materials of the steel bar sampling position to obtain a sampling image of each steel bar sampling position, and then identifying the steel bar appearance contained in the sampling image to establish a steel bar appearance spatial array in the tunnel strong earthquake zone, and then classifying the steel bar sampling positions through morphological recognition, performing pixel enhancement on several morphological inflection points corresponding to a steel bar morphology, and determining the inflection point details of each morphological inflection point, and further fine-tuning the steel bar morphology by analyzing the newly added details of each sampling class, and then determining the basic characteristics of the steel bar by projection, and then adjusting the details of the basic characteristics of the steel bar, and finally using clustering to construct the regional steel bar characteristics of the tunnel strong earthquake zone. In this way, the steel bars in the tunnel strong earthquake zone can be deeply analyzed, their morphology and details can be determined, and then the regional steel bar characteristics of the tunnel strong earthquake zone can be established, which is convenient for subsequent identification and detection work.

[0050] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone, characterized in that: include: Step 1: Construct a standard steel bar structure in the tunnel's strong earthquake zone according to the tunnel construction drawings, and determine several steel bar sampling locations in the tunnel's strong earthquake zone; Step 2: performing image sampling on each of the steel bar sampling positions to obtain several regional steel bar features in the tunnel strong earthquake zone; Step 3: restoring the construction steel bar structure of the tunnel strong earthquake zone based on the regional steel bar characteristics, and identifying structural difference information between the construction steel bar structure and the standard steel bar structure; Step 4: Determine the reinforcement defect characteristics of the corresponding steel bar sampling position according to the difference attributes corresponding to each of the structural difference information, generate and display the reinforcement defect report of the tunnel strong earthquake zone.

2. The method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone according to claim 1, characterized in that: The step 1 comprises: Step 11: screening a number of tunnel structural features included in the tunnel construction drawings, using the tunnel structural features to restore the overall tunnel structure of the tunnel, performing tunnel topography analysis on the overall tunnel structure, and locating the regional scope of the tunnel strong earthquake zone; Step 12: performing tunnel material analysis on a regional range in the overall tunnel structure, obtaining tunnel reinforcement characteristics in the tunnel strong earthquake zone in the overall tunnel structure, and constructing a standard reinforcement structure in the tunnel strong earthquake zone; Step 13: Determine the steel bar direction corresponding to each steel bar in the tunnel strong earthquake zone according to the standard steel bar structure, and regard the steel bar intersections between different steel bars as the steel bar sampling positions in the tunnel strong earthquake zone.

3. The method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone according to claim 1, characterized in that: The step 2 comprises: Step 21: Controlling the camera equipment at the tunnel site to sample each of the steel bar sampling positions, obtaining a sampling image corresponding to each of the steel bar sampling positions, identifying the appearance of the steel bar corresponding to the steel bar sampling position in each of the sampling images, and establishing a steel bar appearance spatial array of the tunnel strong earthquake zone based on the steel bar appearance; Step 22: performing morphological recognition on each of the steel bar appearances in the steel bar appearance spatial array, treating the steel bar sampling positions with consistent steel bar morphology as the same sampling class, identifying a plurality of morphological inflection points corresponding to each of the steel bar morphologies, and performing pixel enhancement on the corresponding morphological inflection points in each of the sampled images to obtain inflection point details corresponding to each of the morphological inflection points; Step 23: Inputting each of the inflection point details into the corresponding steel bar appearance in the steel bar appearance spatial array for detail enhancement, respectively obtaining newly added details corresponding to each of the sampling classes, generating a plurality of steel bar detail information corresponding to the sampling classes, using the steel bar detail information to fine-tune the corresponding steel bar morphology, and drawing a steel bar morphology image corresponding to the steel bar sampling position; Step 24: Project each of the steel bar morphology images to obtain a number of steel bar basic features, adjust the steel bar basic features using each of the steel bar detail information, cluster the generated steel bar detail features, and regard the steel bar feature corresponding to each clustering result as the regional steel bar feature of the tunnel strong earthquake zone.

4. The method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone according to claim 3, wherein: Also includes: The regional steel bar features corresponding to each array position are marked in the steel bar appearance space array, and the regional presentation features corresponding to each regional range in the tunnel strong earthquake zone are determined and displayed.

5. The method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone according to claim 1, characterized in that: The step 3 comprises: Step 31: identifying several reinforcement construction methods included in the tunnel strong earthquake zone based on the regional reinforcement characteristics, and performing structural restoration simulation on the tunnel strong earthquake zone according to several regional reinforcement characteristics included in the reinforcement construction range corresponding to each reinforcement construction method to obtain the constructed reinforcement structure of the tunnel strong earthquake zone; Step 32: performing a pressure test on the constructed steel bar structure to obtain a positional compressive strength value corresponding to each steel bar sampling position in the tunnel strong earthquake zone, determining a standard compressive strength value corresponding to each steel bar sampling position based on the standard steel bar structure, and generating a type of difference information between the constructed steel bar structure and the standard steel bar structure; Step 33: superimposing the constructed steel bar structure onto the standard steel bar structure, screening the non-overlapping portion of the constructed steel bar structure and the standard steel bar structure, and determining two types of difference information between the constructed steel bar structure and the standard steel bar structure; Step 34: combining the first type of difference information and the second type of difference information corresponding to the same steel bar sampling position to generate a plurality of structural difference information between the constructed steel bar structure and the standard steel bar structure.

6. The method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone according to claim 1, wherein: The step 4 comprises: Step 41: performing attribute recognition on each of the structural difference information to obtain the steel bar attributes corresponding to each of the steel bar sampling positions, and performing specification recognition on each of the structural difference information using AI to obtain the steel bar specifications corresponding to each of the steel bar sampling positions; Step 42: Based on the steel bar attributes and the steel bar specifications corresponding to each steel bar sampling location, identify the missing reinforcement attributes and the missing reinforcement degree corresponding to the steel bar sampling location, generate corresponding missing reinforcement defect features, locate each missing reinforcement defect feature respectively, generate and display the missing reinforcement defect report for the tunnel strong earthquake zone.

7. The method for detecting exposed reinforcement in tunnel lining in a strong earthquake zone according to claim 1, wherein: Also includes: Derivation of the tunnel safety level in the strong earthquake zone of the tunnel based on the reinforcement defect report; When the safety level is lower than the specified level, a safety warning is issued for the strong earthquake zone of the tunnel.

8. A system for detecting exposed reinforcement in tunnel linings in strong earthquake zones, characterized in that: include: A positioning sampling module is used to construct a standard steel bar structure in the tunnel's strong earthquake zone according to the tunnel construction drawings and determine several steel bar sampling locations in the tunnel's strong earthquake zone; A sampling execution module is used to perform image sampling on each of the steel bar sampling positions to obtain several regional steel bar features in the strong earthquake zone of the tunnel; A difference analysis module is used to restore the construction steel bar structure of the tunnel strong earthquake zone based on the regional steel bar characteristics and identify structural difference information between the construction steel bar structure and the standard steel bar structure; The missing reinforcement identification module is used to determine the missing reinforcement defect characteristics of the corresponding steel bar sampling position according to the difference attributes corresponding to each of the structural difference information, generate and display the missing reinforcement defect report of the tunnel strong earthquake zone.

9. The exposed reinforcement detection system for tunnel lining in a strong earthquake zone according to claim 8, characterized in that: The positioning sampling module includes: a range positioning unit, configured to screen a plurality of tunnel structural features included in the tunnel construction drawings, restore the overall tunnel structure of the tunnel using the tunnel structural features, perform tunnel topography analysis on the overall tunnel structure, and locate the regional range of the tunnel strong earthquake zone; a standard analysis unit, configured to perform tunnel material analysis on a regional range within the overall tunnel structure, obtain tunnel reinforcement characteristics of the tunnel strong earthquake zone within the overall tunnel structure, and construct a standard reinforcement structure for the tunnel strong earthquake zone; The positioning execution unit is used to determine the steel bar direction corresponding to each steel bar in the tunnel strong earthquake zone according to the standard steel bar structure, and regard the steel bar intersections between different steel bars as the steel bar sampling positions in the tunnel strong earthquake zone.

10. The exposed reinforcement detection system for tunnel lining in a strong earthquake zone according to claim 8, characterized in that: The sampling execution module includes: a spatial arrangement unit, configured to control a camera at the tunnel site to sample images at each of the steel bar sampling positions, obtain a sampled image corresponding to each of the steel bar sampling positions, identify the appearance of the steel bar corresponding to the steel bar sampling position in each of the sampled images, and establish a steel bar appearance spatial array of the tunnel strong earthquake zone based on the steel bar appearance; a detail enhancement unit, configured to perform morphological recognition on each of the steel bar appearances in the steel bar appearance spatial array, regard the steel bar sampling positions with consistent steel bar morphology as the same sampling class, identify a plurality of morphological inflection points corresponding to each of the steel bar morphologies, and perform pixel enhancement on the corresponding morphological inflection points in each of the sampled images to obtain inflection point details corresponding to each of the morphological inflection points; a morphology adjustment unit, configured to input each of the inflection point details into the corresponding steel bar appearance in the steel bar appearance spatial array for detail enhancement, obtain newly added details corresponding to each of the sampling classes, generate a plurality of steel bar detail information corresponding to the sampling classes, use the steel bar detail information to fine-tune the corresponding steel bar morphology, and draw a steel bar morphology image corresponding to the steel bar sampling position; The feature generation unit is used to project each of the steel bar morphology images respectively to obtain a number of steel bar basic features, adjust the steel bar basic features respectively using the steel bar detail information, cluster the generated steel bar detail features, and regard the steel bar feature corresponding to each clustering result as the regional steel bar feature of the tunnel strong earthquake zone.

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