Railway tunnel crack monitoring method and system

Abstract

The application provides a railway tunnel crack monitoring method and system, and relates to data processing technology, wherein the method comprises the following steps: determining the starting point, the ending point and the extension route of the tunnel crack; controlling the high-precision acquisition unit to move along the extension route from the starting point until the starting point is located in the window frame line of the acquisition window; determining the sub-route of the acquisition window corresponding to the extension route, and determining the first transverse point and the second transverse point with distribution characteristics located on both sides of the sub-route; controlling the transverse light unit carried by the high-precision acquisition unit to move to the transverse point, and controlling the high-precision acquisition unit to acquire the acquisition image corresponding to the sub-route; determining the route endpoint far away from the starting point as a new starting point based on the sub-route, and repeating the above steps until the ending point is located in the acquisition image corresponding to any acquisition times, so as to obtain the detection data corresponding to the tunnel crack. The application at least improves the monitoring accuracy.

Description

Technical Field

[0001] This invention relates to data processing technology, and more particularly to a method and system for monitoring cracks in railway tunnels. Background Technology

[0002] As a key infrastructure for rail transit, railway tunnels are subjected to multiple effects such as surrounding rock pressure, train vibration, temperature changes and groundwater erosion over a long period of time. This makes them highly susceptible to cracks on the surface of the lining structure. The development and expansion of cracks not only weaken the load-bearing capacity of the tunnel structure, but may also cause secondary diseases such as water leakage and lining spalling. In severe cases, it may even lead to structural instability and directly threaten the safety of train operation.

[0003] With the continuous increase in the operating mileage of my country's railway network, the aging problem of tunnels in service is becoming increasingly prominent, and crack monitoring has become a core aspect of tunnel operation and maintenance. How to accurately capture key parameters such as crack length, width, and extension direction to provide reliable data support for defect assessment and repair is an important issue for ensuring the long-term safe operation of railway tunnels.

[0004] Currently, railway tunnel crack monitoring mainly adopts a manual inspection mode. Maintenance personnel use tools such as flashlights, tape measures, and crack width gauges to inspect the tunnel lining surface one by one, observe and record crack characteristics and measure dimensions with the naked eye. This mode relies on personnel experience, is easily affected by lighting conditions and visual fatigue, has limited ability to identify fine cracks (e.g., width < 0.2 mm), and the measurement data is highly subjective and has low accuracy.

[0005] Therefore, there is an urgent need to provide a method and system for monitoring cracks in railway tunnels that can improve the accuracy of monitoring. Summary of the Invention

[0006] In view of the above problems, the present invention is proposed to provide a method and system for monitoring cracks in railway tunnels that overcomes or at least partially solves the above problems.

[0007] According to one aspect of the present invention, a method for monitoring cracks in railway tunnels is provided, comprising the following steps:

[0008] Determine the starting and ending points of the corresponding tunnel cracks, as well as the extension route determined by the starting and ending points.

[0009] The high-precision acquisition unit is controlled to move along the extended route from the starting point until the starting point is located at the window frame of the acquisition window of the high-precision acquisition unit.

[0010] Determine the sub-route corresponding to the acquisition window of the extended route, and determine the first lateral point and the second lateral point with distribution characteristics on both sides of the sub-route based on the tunnel crack;

[0011] The control high-precision acquisition unit carries the lateral light unit to coincide with the lateral point, and controls the high-precision acquisition unit to acquire in response to the light of the lateral light unit, so as to obtain the acquisition image corresponding to the sub-route;

[0012] The route endpoint far away from the starting point is determined as a new starting point based on the sub-route, and the above steps are repeated until the terminal point is located in the acquisition image corresponding to any acquisition times, so as to obtain the detection data corresponding to the tunnel crack.

[0013] Optionally, in the method according to the present application, the starting point and the terminal point corresponding to the tunnel crack and the extension route determined by the starting point and the terminal point comprise:

[0014] In response to receiving the crack monitoring signal sent by any employee terminal and carrying the positioning information, the unmanned aerial vehicle is controlled to fly to the positioning information based on the preset flight height for acquisition, and the obtained flight image is sent to the employee terminal;

[0015] In response to receiving the position determination signal sent by the employee terminal based on the flight image, the crack area indicating the tunnel crack located in the flight image is determined based on image recognition, and the two image contour points with the maximum distance constituting the region contour of the crack area are determined as the starting point and the terminal point;

[0016] The extension route of the corresponding tunnel crack is determined based on the start-stop line connecting the starting point and the terminal point.

[0017] Optionally, in the method according to the present application, the extension route of the corresponding tunnel crack is determined based on the start-stop line connecting the starting point and the terminal point, comprising:

[0018] Each first array line respectively passing through each first array point subjected to array processing on the start-stop line is generated along the direction perpendicular to the start-stop line;

[0019] An image coordinate system is established, wherein the start-stop line coincides with the Y-axis of the image coordinate system;

[0020] The image coordinate points located in the crack area determined based on the obtained each first array line are determined as route points based on the mean value calculation of the corresponding transverse coordinate values of all image coordinate points with the same vertical coordinate values of the region contour;

[0021] The route points at adjacent positions are connected along the extension direction of the start-stop line to obtain the extension route.

[0022] Optionally, in the method according to the present application, the high-precision acquisition unit is controlled to move along the extension route with the starting point as the starting point until the starting point is located in the window frame line of the acquisition window of the high-precision acquisition unit, and the method further comprises:

[0023] The window frame line of the acquisition window with the starting point located at the high-precision acquisition unit is determined as the adjustment frame line, and the two window frame lines perpendicular to the adjustment frame line are determined as the verification frame lines;

[0024] The response determines that any check frame line coincides with a tunnel crack based on the acquisition window. The acquisition multiplier of the corresponding acquisition window is then reduced by the same baseline multiplier to obtain the acquisition multiplier corresponding to different reduction times.

[0025] The response determines that each check frame does not coincide with the tunnel crack based on the acquisition multiple corresponding to any decreasing number of acquisitions. It controls the high-precision acquisition unit to move away from the starting point along the extension route until the starting point is located at the adjustment frame.

[0026] Optionally, in the method according to the present invention, determining the sub-route corresponding to the acquisition window of the extended route, and determining the first lateral point and the second lateral point with distribution characteristics located on both sides of the sub-route based on the tunnel crack, includes:

[0027] The sub-path is divided into arrays, and each second array line is generated along a direction perpendicular to the tangent direction of the sub-path for each second array point obtained by the respective path;

[0028] Determine the first intersection point and the second intersection point where each second array line intersects with the crack profile of the tunnel crack, and determine the intersection distance between the first intersection point and the second intersection point;

[0029] The maximum intersection distance is defined as the maximum distance. Then, with the second array line corresponding to the maximum distance as the center, a calculation process is constructed to calculate the difference between the corresponding intersection distance and the maximum distance in turn, and different distance differences are obtained.

[0030] If any distance difference is less than a preset difference, the second array line corresponding to that distance difference is determined as the distribution characteristic line; otherwise, the calculation process is stopped.

[0031] The first and second intersection points of the distribution characteristic lines corresponding to the center positions along the sub-route are determined as the first and second lateral points with distribution characteristics.

[0032] Optionally, in the method according to the invention, controlling the lateral illumination unit carried by the high-precision acquisition unit to move to coincide with the lateral point includes:

[0033] If the center point of the response acquisition window does not coincide with the feature intersection point where the distribution feature line of the corresponding horizontal point intersects with the sub-line segment, the high-precision acquisition unit is controlled to move along the direction from the center point of the window toward the feature intersection point until the center point of the window coincides with the feature intersection point.

[0034] The collection multiple corresponding to the collection window is updated until the starting point is located at the adjustment frame line, and an updated number value corresponding to the updated collection multiple is obtained;

[0035] The unit length between each lateral point and the sub-route is determined based on the distribution characteristic line, and the update multiple is determined based on the decreasing number corresponding to the collection multiple of the collection window and the updated number value;

[0036] The unit length is updated by the corresponding update multiple, and the high-precision collection unit is controlled to carry the lateral light unit towards different lateral points based on the obtained actual length corresponding to each lateral point.

[0037] Optionally, in the method according to the application, in response to the illumination of the lateral light unit, the high-precision collection unit is controlled to collect to obtain the collection image corresponding to the sub-route, and then further comprising:

[0038] The real coordinate system is established, and the starting point and the route endpoint away from the starting point determined based on the sub-route are determined as the first vertical point and the second vertical point, wherein any distribution characteristic line coincides with the X-axis of the real coordinate system;

[0039] In response to the existence of the lateral coordinate difference value corresponding to any vertical point and the window center point, the high-precision collection unit is controlled to move laterally corresponding to the coordinate difference value, and the vertical coordinate difference value corresponding to the vertical coordinate number value of the vertical point and the window center point is obtained;

[0040] The vertical light unit carried by the high-precision collection unit is controlled to move towards the vertical point based on the vertical coordinate difference value, and in response to the illumination of the vertical light unit based on the vertical point, the high-precision collection unit is controlled to collect, and the collection image is updated based on the obtained vertical supplementary image to obtain the updated collection image.

[0041] Optionally, in the method according to the application, the collection image is updated based on the obtained vertical supplementary image to obtain the updated collection image, comprising:

[0042] The same image part of the vertical supplementary image and the collection image is determined as the to-be-supplemented region, and the first contrast and the second contrast of different image pixel points constituting the to-be-supplemented region are determined based on the vertical supplementary image and the collection image respectively;

[0043] The image pixel point with the corresponding first contrast greater than the second contrast in the vertical supplementary image is determined as the supplementary pixel point, and the supplementary pixel points at adjacent positions are connected to obtain each supplementary sub-region;

[0044] The region part of the corresponding to-be-supplemented region in the collection image is replaced based on each supplementary sub-region to obtain the updated collection image.

[0045] Optionally, in the method according to the present invention, obtaining the detection data corresponding to the tunnel crack includes:

[0046] Determine the acquisition factor for images acquired at different acquisition times, and set the smallest acquisition factor as the stitching factor;

[0047] The captured images are reduced by the corresponding stitching factor using the image center point as the center to obtain the updated captured images;

[0048] Create vertically arranged image fill slots on the data display interface, and fill each captured image into different image fill slots from top to bottom according to the capture order. The sub-routes of the captured images corresponding to different image fill slots are presented as line segment connections.

[0049] Create filling slots of various lengths that are horizontally arranged with each image filling slot, and fill the filling slots of different lengths sequentially from top to bottom according to the acquisition order of the same acquired image, so as to obtain the detection data of the corresponding tunnel cracks composed of the data display interface.

[0050] According to another aspect of the present invention, a railway tunnel crack monitoring system is provided, comprising:

[0051] The route determination module is configured to determine the start point, end point, and extended route determined by the start point and end point of the corresponding tunnel crack.

[0052] The acquisition and movement module is configured to control the high-precision acquisition unit to move along the extended route from the starting point until the starting point is located at the window frame of the acquisition window of the high-precision acquisition unit.

[0053] The distribution determination module is configured to determine the sub-route corresponding to the acquisition window of the extended route, and to determine the first lateral point and the second lateral point with distribution characteristics located on both sides of the sub-route based on the tunnel crack;

[0054] The image acquisition module is configured to control the lateral illumination unit carried by the high-precision acquisition unit to move to coincide with the lateral point, and respond to the lateral illumination unit to provide illumination, thereby controlling the high-precision acquisition unit to acquire images of the corresponding sub-route.

[0055] The data integration module is configured to determine the route endpoints far from the starting point as new starting points based on the sub-route, repeat the above steps until the termination point is located in the image acquired for any number of acquisitions, and obtain the detection data of the corresponding tunnel crack.

[0056] According to the scheme of the present application, the present application effectively breaks through the bottleneck of the tunnel crack monitoring accuracy under the artificial inspection mode, significantly improves the precision and reliability of the crack parameter measurement, and provides high-quality data support for the tunnel structure disease evaluation, wherein the following aspects can be embodied:

[0057] 1. In the aspect of accurate capture of crack details, the present application solves the problems of uneven light and difficult identification of fine cracks in artificial inspection through the cooperative design of transverse light adaptation and high-precision acquisition, and specifically, based on the first and second transverse points on both sides of the sub-route, the transverse light unit is controlled to accurately move to the target position and turn on the light, a directional light source perpendicular to the crack direction is formed, the clear light and shade contrast is formed on the crack edge based on the directional light, the fine cracks are clearly distinguished from the interference features such as stains and scratches on the lining surface, and the detail blur problem caused by the dispersed flashlight light in artificial inspection is avoided; at the same time, the high-precision acquisition unit performs image acquisition under the assistance of the directional light, the micro features such as the edge profile and width change of the crack are completely retained, and the detail clarity of the acquired image is improved by tens of times compared with artificial visual observation, thereby laying a foundation for the accurate measurement of crack width and shape.

[0058] 2. In the aspect of continuous monitoring of the whole crack, the present application realizes the complete coverage of the crack extension trajectory through the route tracking and the acquisition mode of iterative segmentation, first determines the starting point, ending point and extension route of the crack, then controls the high-precision acquisition unit to move along the route in segments, divides the sub-route in units of acquisition windows, updates the starting point after completing the acquisition of each segment of the sub-route and repeats the operation, and covers the whole crack, so that the continuous acquisition images of the crack from the starting point to the ending point are obtained, the omission of the middle segment of the crack is avoided, the change of the extension direction of the crack is accurately captured, and the technical problem that it is difficult to form a complete crack data chain in artificial inspection is solved.

[0059] 3. In the aspect of improving the measurement accuracy, the present application greatly reduces the measurement error through the positioning reference determination and data traceability, aligns the acquisition window and the sub-route accurately based on the crack extension route, ensures that the shooting angle of each acquisition image is always focused on the core area of the crack, avoids the angle deviation in the measurement by artificial handheld tools, and the accurate coincidence of the transverse light unit and the transverse point ensures the consistency of the light conditions of the acquisition images of different sub-routes, eliminates the image comparison error caused by the light difference, and the detection data formed by the segment-by-segment acquisition can be spliced through the sub-route association to form a complete crack digital file, which can not only directly extract the macro parameters such as crack length and extension direction, but also calculate the width change of each segment based on the continuous images, thereby improving the monitoring accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0060] Figure 1A flow chart of a railway tunnel crack monitoring method according to an embodiment of the present application is shown;

[0061] Figure 2 A structural schematic diagram of the high-precision acquisition unit and the illumination unit in the present embodiment is shown.

[0062] Figure 3 A system block diagram of a railway tunnel crack monitoring system according to another embodiment of the present application is shown. DETAILED DESCRIPTION

[0063] Exemplary embodiments of the present disclosure will be described in detail with reference to the drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood, and the scope of the present disclosure can be accurately conveyed to those skilled in the art.

[0064] To solve the problems existing in the prior art, the inventors propose the present application. An embodiment of the present application provides a railway tunnel crack monitoring method, which can be executed in a computing device, wherein the computing device can be understood as a terminal with data processing function, such as a mobile phone or a computer.

[0065] Figure 1 A flow chart of a railway tunnel crack monitoring method according to an embodiment of the present application is shown,

[0066] As Figure 1 shown, the method proposed in the present embodiment starts from step S1, in which the following contents are included:

[0067] The starting point, the ending point of the corresponding tunnel crack and the extension route determined by the starting point and the ending point are determined.

[0068] For example, in the present embodiment, the present embodiment can provide a clear position reference and path guidance for the subsequent movement of the high-precision acquisition unit and data acquisition by determining the starting point, end point and extension route of the tunnel crack, ensuring the pertinence and integrity of tunnel crack monitoring. It can be explained that the starting point is the initial end point of the extension of the tunnel crack in space, and the end point is the terminal end point of the extension of the tunnel crack. Both of them are key position nodes for defining the overall range of the crack. For example, in long-distance tunnel crack monitoring, the determination of the starting point and the end point can form a clear "from A to B" task closed loop for the monitoring process, ensuring that each crack can be included in the monitoring range. In addition, the extension route is a trajectory line connecting the starting point and the end point and fitting the actual direction of the tunnel crack. It is not a simple straight line connection, but a path formed based on the real extension form of the crack (for example, a curve or a broken line that adapts to the bending and turning of the crack). By determining the extension route, a precise "navigation path" can be provided for the subsequent movement of the high-precision acquisition unit, so that the high-precision acquisition unit can gradually advance along the extension route to ensure that it is always aligned with the crack area and avoid the collected images deviating from the crack target due to path deviation.

[0069] Further, in the present embodiment, the "determination of the starting point, end point and extension route determined by the starting point and end point of the corresponding tunnel crack" can further include the following steps:

[0070] In response to receiving the crack monitoring signal carrying the positioning information sent by any employee terminal, the unmanned aerial vehicle is controlled to fly to the positioning information based on the preset flight height for collection, and the obtained flight image is sent to the employee terminal;

[0071] In response to receiving the position determination signal sent by the employee terminal based on the flight image, the crack area indicating the tunnel crack located in the flight image is determined based on image recognition, and the two image contour points with the largest corresponding distance of the area contour constituting the crack area are determined as the starting point and the end point;

[0072] The extension route of the corresponding tunnel crack is determined based on the start-stop line connecting the starting point and the end point.

[0073] For example, in the present embodiment, the determination of the starting point, end point and extension route can be specifically implemented based on the following method steps:

[0074] Firstly, in response to receiving a crack monitoring signal sent by any employee terminal carrying positioning information, the server involved in the embodiment can control the unmanned aerial vehicle to fly to the positioning information based on a preset flight height to collect flight images, and send the obtained flight images to the employee terminal. It can be explained that the employee terminal can be understood as a terminal device operated by a field worker, and the positioning information is the approximate spatial position reported by the field worker after finding a suspected crack (for example, the left waist of tunnel K1+200). The preset flight height is a height that is safe and can cover the monitoring area based on the tunnel clearance height (for example, 5 meters away from the tunnel wall, ensuring that the shooting range is clear and there is no risk of collision), here, by flying to the positioning information with the unmanned aerial vehicle carrying the image collection device to collect flight images, it can quickly reach the area that is difficult for human to reach, avoid the limitations of manual reconnaissance, and at the same time, the images are real-time returned to the employee terminal, providing visual basis for subsequent position confirmation, greatly improving the efficiency of crack preliminary positioning.

[0075] Secondly, in response to receiving a position determination signal sent by the employee terminal based on the flight images, the server can determine the crack area indicating the tunnel crack in the flight images based on image recognition, and determine the two image contour points with the largest distance of the region contour constituting the crack area as the start point and the end point. Here, the position determination signal is a trigger instruction after the employee confirms the position of the tunnel crack in the flight images through the employee terminal, and then the position of the tunnel crack can be further confirmed, and the crack area indicating the tunnel crack can be accurately extracted from the flight images based on image recognition technology (for example, edge detection algorithm), excluding background (for example, tunnel wall stains, pipeline shadows) interference. It can be explained that since the region contour is the edge contour line of the crack area, the distance between all image contour points on the contour can be calculated, and the two points with the largest distance can be determined as the start point and the end point.

[0076] Finally, the server can determine the extension route of the corresponding tunnel crack based on the start-stop line connecting the start point and the end point established. Here, the start-stop line is a line segment formed by connecting the start point and the end point with a straight line, which can preliminarily outline the extension direction of the crack. Based on the start-stop line, combined with the actual trend of the crack in the flight images, the extension route that fits the real extension form of the crack can be determined. It can be explained that the establishment of the start-stop line provides a clear reference framework for the extension route, avoids the randomness of route determination, ensures that the extension route always surrounds the core area of the crack, provides accurate path guidance for the subsequent high-precision collection unit moving along the route, solves the problem of path deviation without reference, and ensures that the intelligent monitoring can orderly cover the whole crack.

[0077] Furthermore, in the embodiment, the above-mentioned "determining the extension route of the corresponding tunnel crack based on the start-stop line connecting the start point and the end point established" can further include the following steps:

[0078] generating each first array line along a direction perpendicular to the start-end line, the first array line passing through each first array point obtained by arraying the start-end line;

[0079] establishing an image coordinate system, wherein the start-end line coincides with a Y-axis of the image coordinate system;

[0080] performing mean value calculation on corresponding horizontal coordinate values of all image coordinate points with the same vertical coordinate value of the region contour for each first array line obtained, and determining the image coordinate points located in the crack region as route points based on the horizontal coordinate mean value obtained;

[0081] connecting the route points at adjacent positions along the extension direction of the start-end line to obtain an extension route.

[0082] For example, in the embodiment, the determination of the extension route based on the established start-end line can be specifically implemented based on the following method steps:

[0083] Firstly, the server can generate each first array line along a direction perpendicular to the start-end line, the first array line passing through each first array point obtained by arraying the start-end line, wherein the start-end line is a straight line connecting the starting point and the ending point, and the arraying is to uniformly divide the start-end line into a plurality of first array points with consistent intervals (for example, one point is set every 10 pixels), and a straight line passing through each first array point along a direction perpendicular to the start-end line (i.e. corresponding horizontal direction) is a first array line. It can be explained that each first array line generated can divide the long and narrow crack region into a plurality of horizontal analysis units in longitudinal direction, realize the segmented and refined investigation of the crack contour, avoid the strike misjudgment caused by overall extensive analysis, and provide uniform distribution analysis reference for subsequent extraction of route points;

[0084] Secondly, the server can establish an image coordinate system based on the manner that the start-end line coincides with the Y-axis of the image coordinate system, wherein the image coordinate system is a plane rectangular coordinate system established based on the flight image, and by coinciding the start-end line with the Y-axis (vertical axis), the first array line can be naturally parallel to the X-axis (horizontal axis), realizing the coordinate alignment of the crack extension direction (vertical direction) and the analysis direction (horizontal direction), and further providing a unified standard for subsequent quantitative analysis of the horizontal position of the crack contour, ensuring the consistency of the position description of the contour points on different first array lines, avoiding the calculation deviation caused by the coordinate confusion, and laying a coordinate system foundation for accurate extraction of route points;

[0085] Then, the server can superimpose each first array line on all image coordinate points of the corresponding same vertical coordinate value of the region contour to calculate the mean value of the corresponding horizontal coordinate value, and determine the image coordinate points determined to be located in the crack region as route points based on the obtained horizontal coordinate mean value, where the same first array line corresponds to the same vertical coordinate value (Y value) which intersects with the region contour of the crack region to form a plurality of image coordinate points; calculating the mean value of the horizontal coordinate value (X value) of these points can filter out noise points or irregular protrusions on the contour edge to obtain the core horizontal center position of the crack at this vertical position; determining the image coordinate points corresponding to the mean value and located in the crack region as route points can ensure that each route point accurately corresponds to the center direction of the crack at this vertical position, thereby effectively avoiding point position deviation caused by irregular crack contours, so that the route points can truly reflect the core extension trajectory of the crack;

[0086] Finally, the server can connect the route points at adjacent positions along the extension direction of the start-end line to obtain an extension route, where the extension direction of the start-end line is the Y-axis direction of the image coordinate system, and the adjacent route points arranged in a longitudinal sequence are connected in turn to form a curve or a polyline that can completely fit the true direction of the crack from the starting point to the ending point, for example, when the tunnel crack bends to the left at a certain segment and deviates to the right at a certain segment, the connected extension route will also present the corresponding bending shape, rather than a simple straight line. The extension route spliced by the refined route points can provide a "close-fitting" movement path guide for the subsequent high-precision acquisition unit, ensure that the acquisition unit is always aligned with the core area of the crack, avoid monitoring omissions caused by path deviation, and significantly improve the accuracy and integrity of intelligent monitoring of railway tunnel cracks.

[0087] In step S2, the following steps are included:

[0088] The high-precision acquisition unit is controlled to start moving along the extension route from the starting point until the starting point is located in the window frame line of the acquisition window of the high-precision acquisition unit.

[0089] For example, in the present embodiment, by controlling the high-precision acquisition unit to move along the extension route and setting the window frame line termination condition based on the starting point, the present embodiment can establish a standardized monitoring starting position, provide a unified reference for subsequent segmented acquisition and image connection, and ensure the orderliness and integrity of crack monitoring. It can be explained that the high-precision acquisition unit is a device for obtaining high-definition images of the tunnel cracks (for example, a high-definition industrial camera, a three-dimensional scanner, etc.), and the acquisition accuracy directly affects the capture effect of crack details. The starting point is the initial endpoint of the tunnel crack extension determined in the previous step, and the extension route is the trajectory line that fits the real trend of the crack. By taking the starting point as the moving starting point, it can ensure that the monitoring action of the high-precision acquisition unit starts from the initial end of the crack, avoids missing the initial segment caused by cutting into the middle area of the crack, and moves along the extension route to ensure that the acquisition unit always adjusts its position around the core area of the crack, avoiding the loss of focus caused by deviating from the route, and laying a positional foundation for subsequent accurate acquisition of crack images. In addition, the acquisition window is the field of view range of the high-precision acquisition unit, and the window frame line is the edge boundary of the field of view range (for example, the left, right, top, and bottom edge lines of the acquisition window). When the high-precision acquisition unit moves to the starting point and falls on the window frame line, it means that the acquisition unit has reached the initial monitoring position. At this time, the field of view of the acquisition window not only contains the initial segment of the crack corresponding to the starting point, but also reserves subsequent field of view space for continuous movement and acquisition along the extension route, so that different crack monitoring tasks or multiple monitoring of the same crack can all start with a unified initial field of view state, avoiding the confusion of monitoring reference caused by the randomness of the initial position.

[0090] Here, the high-precision acquisition unit can be carried by a UAV for corresponding movement. The UAV appearing in the present embodiment can refer to the same device or different devices.

[0091] It can be further explained that based on the above process, the high-precision acquisition unit obtains a standardized monitoring starting position: taking the initial end of the crack as the starting point, adjusting to the position where the edge of the acquisition window aligns with the starting point along the crack trend. Based on the setting of this starting position, it not only ensures that the monitoring starts from the front end of the crack without missing the initial segment, but also provides a clear boundary reference for defining the acquisition range of each subsequent movement and acquisition, for example, the starting point on the current window frame line can be taken as the reference, and the other side of the window away from the starting point can be taken as the new connection boundary, to ensure that the images of different acquisition times can be sequentially connected along the extension route, avoiding repeated acquisition or missing of crack paragraphs, and providing an orderly starting basis for the entire tunnel crack intelligent monitoring process, significantly improving the standardization and integrity of the monitoring.

[0092] Since the high-precision acquisition unit moves to the starting point located at the window frame line of the acquisition window, if direct acquisition is performed based on the current acquisition multiple, the acquisition window view may be too narrow due to the high acquisition multiple, for example, when the width of the tunnel crack is large or the acquisition multiple is too large, the edges of the tunnel crack may exceed the lateral boundary of the acquisition window, resulting in that the lateral full view of the crack in the acquisition window cannot be captured by a single acquisition, and finally the integrity and accuracy of the crack monitoring are reduced. Therefore, in order to solve this problem, in the embodiment, after the above-mentioned "controlling the high-precision acquisition unit to move along the extension route with the starting point as the starting point until the starting point is located at the window frame line of the acquisition window of the high-precision acquisition unit", the following steps can be further included:

[0093] determining the window frame line where the starting point is located at the window frame line of the acquisition window of the high-precision acquisition unit as an adjustment frame line, and determining two window frame lines perpendicular to the adjustment frame line as check frame lines;

[0094] in response to determining that any check frame line coincides with the tunnel crack based on the acquisition window, decreasing the acquisition multiple corresponding to the acquisition window to the same reference multiple to obtain the acquisition multiple corresponding to different decreasing times;

[0095] in response to determining that each check frame line does not coincide with the tunnel crack based on the acquisition multiple corresponding to any decreasing time, controlling the high-precision acquisition unit to move away from the starting point along the extension route until the starting point is located at the adjustment frame line.

[0096] For example, in the embodiment, the position adjustment of the high-precision acquisition unit can be specifically implemented based on the following method steps:

[0097] Firstly, the server can determine the window frame line where the starting point is located at the window frame line of the acquisition window of the high-precision acquisition unit as an adjustment frame line, and determine two window frame lines perpendicular to the adjustment frame line as check frame lines. Here, the adjustment frame line is the edge of the acquisition window where the starting point is located (for example, the starting point is located at the upper frame line of the window, and the lower frame line is the adjustment frame line), which serves as the reference boundary for subsequent position calibration; the check frame line is the window edge perpendicular to the adjustment frame line (for example, the adjustment frame line is the left frame line, and the check frame line is the upper and lower frame lines), which is used to judge whether the lateral view of the acquisition window can completely cover the tunnel crack. By clearly dividing the functions of the frame lines, a clear judgment object is provided for subsequent multiple adjustment and position calibration, avoiding operation confusion caused by frame line function confusion, and ensuring that the adjustment and calibration actions have a clear target orientation;

[0098] Secondly, in response to determining that any of the comparison frame lines coincides with the tunnel crack based on the collection window, the server can decrease the collection multiple corresponding to the collection window to a same reference multiple, to obtain collection multiples corresponding to different decreasing times, which can be explained as follows: when any of the comparison frame lines coincides with the tunnel crack, it indicates that the current collection multiple is too high and the field of view is too narrow, and the transverse edge of the tunnel crack exceeds the range of the collection window, while the same reference multiple is a preset fixed decreasing amplitude (such as 0.2 times per decreasing), and the collection multiple is gradually reduced according to the amplitude, so as to gradually expand the field of view range of the collection window, and the stepwise decreasing manner can accurately control the degree of expansion of the field of view, avoid excessive field of view redundancy or image clarity reduction caused by one-time multiple adjustment, and ensure that the field of view is expanded while maintaining sufficient collection accuracy, to provide adaptive field of view conditions for complete capture of transverse details of the crack;

[0099] Finally, in response to determining that none of the comparison frame lines coincides with the tunnel crack based on the collection multiple corresponding to any of the decreasing times, the server can correspondingly control the high-precision collection unit to move away from the starting point along the extension route until the starting point is located at the adjustment frame line, that is, when all the comparison frame lines do not coincide with the tunnel crack, it indicates that the field of view under the current collection multiple can completely cover the transverse range of the tunnel crack; at this time, by moving the high-precision collection unit away from the starting point along the extension route, the collection window can be adjusted to a more optimal monitoring starting position while maintaining the integrity of the field of view; and the terminal condition that "until the starting point is located at the adjustment frame line" can ensure that the high-precision collection unit still maintains the same calibration standard as the initial position setting after moving, which not only solves the problem of incomplete coverage of the crack caused by the narrow field of view, but also ensures that the high-precision collection unit always takes the adjustment frame line as the reference, to provide a stable position reference for the ordered connection of images during subsequent collection along the extension route, avoid missing or repeated collection of tunnel crack sections caused by position deviation, and significantly improve the integrity and accuracy of intelligent monitoring of railway tunnel cracks.

[0100] In step S3, the following steps are included:

[0101] Determine a sub-route of the extension route corresponding to the collection window, and determine first and second transverse points located on both sides of the sub-route and having distribution identification based on the tunnel crack.

[0102] For example, in the present embodiment, the present embodiment can provide clear path segments and position references for subsequent accurate lighting and image acquisition by dividing the sub-route within the acquisition window, locating the identifying lateral points on both sides of the crack, ensuring the pertinence of the monitoring of the tunnel crack and the image quality; It can be explained that the extended route is the complete trajectory line through the whole tunnel crack, and the acquisition window is the current shooting field of view range of the high-precision acquisition unit; The sub-route is the part of the extended route within the acquisition window, which is the core monitoring object of the current acquisition action, and the complete extended route is divided into several segments that adapt to the acquisition window, so that each acquisition focuses on a specific crack segment, avoiding excessive acquisition of non-crack areas due to ambiguous acquisition range, improving the pertinence of acquisition, and ensuring that the acquisition action accurately corresponds to the local area of the crack; In addition, since the tunnel crack is distributed laterally on both sides of the sub-route, the lateral points with distribution identification are the key position points that can reflect the lateral boundary characteristics of the crack (for example, the characteristic endpoints of the left and right edges of the tunnel crack, or the endpoints on both sides of the widest part of the tunnel crack), and the lateral range of the crack in the corresponding segment of the sub-route can be accurately defined to provide clear position identification for subsequent operations; That is, it can be understood that the sub-route determines "which segment of the crack is acquired", the first and second lateral points determine "where the lateral range of the tunnel crack is", which not only ensures the accurate focus of the acquisition range and avoids resource waste, but also provides a reliable positioning basis for the lateral lighting unit, ensuring the effectiveness of the light compensation, and thus improving the clarity of the acquired image and the detail integrity of the tunnel crack, providing high-quality image data support for intelligent monitoring of railway tunnel cracks, and significantly enhancing the accuracy and reliability of the monitoring.

[0103] Further, in the present embodiment, the above-mentioned "determining the sub-route of the extended route corresponding to the acquisition window, and determining the first lateral point and the second lateral point with distribution characteristics located on both sides of the sub-route based on the tunnel crack" can further include the following steps:

[0104] array dividing the sub-route, and generating each second array line respectively passing through each second array point obtained along the direction perpendicular to the tangent direction of the sub-route;

[0105] determining a first intersection point and a second intersection point of each second array line and the crack profile of the tunnel crack, and determining the intersection distance of the first intersection point corresponding to the second intersection point;

[0106] determining the maximum intersection distance as the maximum distance, and constructing a calculation process for calculating the difference between the corresponding intersection distance and the maximum distance towards both sides with the second array line corresponding to the maximum distance as the center, to obtain different distance differences;

[0107] In response to any distance difference being less than a preset difference, a second array line corresponding to the distance difference is determined as a distribution feature line, otherwise the calculation process is stopped;

[0108] The first intersection point and the second intersection point of the distribution feature line corresponding to the center position along the sub-route are determined as the first lateral point and the second lateral point with distribution identification.

[0109] For example, in the present embodiment, the determination of the sub-route, the first lateral point and the second lateral point can be specifically implemented based on the following method steps:

[0110] Firstly, the server can perform array division on the sub-route, and generate a second array line respectively passing each second array point obtained along a direction perpendicular to the tangent direction of the sub-route. Based on the foregoing, the sub-route is a segment of the extension route located in the collection window, the array division is to uniformly divide the sub-route into a plurality of second array points with consistent intervals (for example, one point is set every 5 pixels), ensuring that there is no omission in the lateral distribution analysis of the entire sub-route; the tangent direction of the sub-route is the extension direction thereof, and a straight line passing each second array point is generated along a direction perpendicular to the tangent (i.e., the lateral direction), that is, the second array line. It can be explained that the second array line can densely cover the crack segment corresponding to the sub-route like a “lateral detection line”, realizing point-by-point survey of the lateral width of the tunnel crack, avoiding the omission of distribution features due to sparse analysis points, and laying a foundation for subsequent accurate capture of the lateral boundary of the tunnel crack;

[0111] Secondly, the server can determine the first intersection point and the second intersection point of each second array line intersecting with the crack contour of the tunnel crack, and determine the intersection distance of the first intersection point corresponding to the second intersection point. Here, the crack contour is the edge contour line of the tunnel crack in the collection window, each second array line formed intersects with the contour to form two intersection points (i.e., the first intersection point and the second intersection point), and respectively corresponds to the two side boundaries of the tunnel crack. The intersection distance is the straight line distance between the two intersection points, which directly reflects the actual width of the tunnel crack at the lateral position. That is, by calculating the intersection distance on all second array lines, the distribution change rule of the width of the tunnel crack along the sub-route can be quantified, providing objective data support for screening key lateral points and avoiding point deviation caused by visual judgment;

[0112] Then, the server can determine the maximum intersection distance as the maximum distance, and construct a calculation process for calculating the difference between the corresponding intersection distance and the maximum distance from the second array line corresponding to the maximum distance to both sides in sequence to obtain different distance differences. Here, the maximum distance is the maximum value among all intersection distances, and the second array line corresponding to the widest part of the crack can most clearly reflect the lateral distribution range of the tunnel crack, so it is taken as the center reference. The difference between the intersection distance and the maximum distance (i.e., the distance difference) calculated from the center to the second array line on both sides can intuitively present the shrinkage trend of the width of the tunnel crack from the widest part to both sides, providing a gradient basis for defining the effective lateral distribution range of the tunnel crack.

[0113] Then, in response to any distance difference being less than a preset difference value, the server can determine the second array line corresponding to the distance difference as the distribution feature line, otherwise stop the calculation process. It can be explained that the preset difference value is a threshold value (for example, 2 pixels) preset based on the monitoring accuracy of the tunnel crack. When the distance difference is less than the threshold value, it means that the width of the tunnel crack at this position is very small different from the widest part, and still in the core distribution area of the tunnel crack. Determining such array lines as distribution feature lines can accurately define the effective range of the lateral distribution of the tunnel crack, avoiding the misinclusion of the edge area with too narrow width into the core monitoring range. At the same time, stopping the calculation when the distance difference is greater than or equal to the preset difference value can timely define the boundary of the distribution feature line, ensuring the accuracy and efficiency of the screening result.

[0114] Finally, the first intersection point and the second intersection point of the distribution feature line corresponding to the center position along the sub-route are determined as the first lateral point and the second lateral point with distribution identification. Here, based on the foregoing, it can be known that the second array line determined as the distribution feature line is still in the core distribution area of the tunnel crack, therefore, the distribution feature line at the center position can represent the lateral distribution of the tunnel crack, so the two intersection points of the distribution feature line corresponding to the center position can be determined as the first lateral point and the second lateral point, which can truly reflect the lateral distribution characteristics of the tunnel crack, and provide a reliable position reference for subsequent image acquisition and parameter analysis of the tunnel crack, significantly improving the accuracy and reliability of intelligent monitoring of railway tunnel cracks.

[0115] It can be explained that when the number of line segments corresponding to all distribution feature lines corresponding to the same sub-route is even, the first intersection point and the second intersection point of one of the two distribution feature lines corresponding to the center position with the largest distance difference can be determined as the first lateral point and the second lateral point with distribution identification.

[0116] In step S4, the following content is included:

[0117] The control high-precision acquisition unit carries the lateral light unit to move to coincide with the lateral point, and controls the lateral light unit to light in response, and controls the high-precision acquisition unit to acquire, to obtain the acquisition image corresponding to the sub-route.

[0118] For example, in the embodiment, the embodiment can ensure that the sub-route image acquired is clear in presenting crack details by precisely controlling the lateral light unit to align with the lateral point and triggering acquisition in combination with the lighting action, provide high-quality data support for subsequent monitoring and analysis, and improve the effectiveness of intelligent monitoring of tunnel cracks; it can be explained that the lateral light unit is a device provided by the high-precision acquisition unit for providing lateral directional lighting, and the lighting range directly affects the brightness and contrast of the crack area; the lateral point is the first lateral point and the second lateral point previously determined and located on both sides of the sub-route, which define the lateral core distribution range of the crack; controlling the lateral light unit to move to coincide with the lateral point can make the light precisely focus on the lateral boundary and core area of the crack, avoid excessive illumination of non-crack areas or insufficient illumination of crack areas caused by deviation of the light, and the like; for example, when the first lateral point and the second lateral point correspond to the left and right edges of the crack respectively, the light emitted by the lateral light unit can uniformly cover the lateral range of the crack after moving to coincide with the two points, enhance the light and dark contrast between the crack and the tunnel wall, lay a lighting foundation for clearly capturing the crack profile, ensure that the crack area is in a sufficient and suitable lighting environment when the high-precision acquisition unit acquires the image, avoid blind acquisition when the light is not stable or does not cover the target area, ensure that each sub-route image acquired has high definition and high contrast, provide reliable image data for subsequent intelligent monitoring links such as crack parameter measurement and state analysis, and significantly improve the accuracy and effectiveness of intelligent monitoring of railway tunnel cracks.

[0119] It can be explained that the lateral light unit can be specifically LED lamp beads or other light-emitting elements, which can be slidingly connected with the lateral moving slide rails previously arranged on both sides of the high-precision acquisition unit, wherein the lateral light unit can include two and be correspondingly arranged on the lateral moving slide rails on both sides, so that the lateral light unit can slide based on the lateral moving slide rails.

[0120] Further, in the embodiment, the above-mentioned "controlling the high-precision acquisition unit to carry the lateral light unit to move to coincide with the lateral point" can further include the following steps:

[0121] In response to the window center point of the acquisition window not coinciding with the characteristic intersection point at which the distribution characteristic line corresponding to the lateral point intersects with the sub-segment, the high-precision acquisition unit is controlled to move in the direction from the window center point to the characteristic intersection point until the window center point coincides with the characteristic intersection point.

[0122] The collection multiple corresponding to the collection window is updated until the starting point is located on the adjustment frame line, and an updated value corresponding to the update is obtained;

[0123] The unit length between each lateral point and the sub-route is determined based on the distribution characteristic line, and the update multiple is determined based on the decrement corresponding to the collection multiple of the collection window and the updated value;

[0124] The unit length is updated by the corresponding update multiple, and the lateral illumination unit carried by the high-precision collection unit is controlled to move towards different lateral points based on the actual length of each lateral point obtained.

[0125] For example, in the present embodiment, the control movement of the lateral illumination unit can be specifically based on the following method steps:

[0126] Firstly, in response to the window center point of the collection window not coinciding with the characteristic intersection point at which the distribution characteristic line corresponding to the lateral point intersects with the sub-segment, the server can control the high-precision collection unit to move in the direction from the window center point to the characteristic intersection point until the window center point coincides with the characteristic intersection point. It can be explained that the distribution characteristic line is a straight line determined in advance, which can reflect the lateral distribution characteristic of the tunnel crack, and the sub-segment is the sub-route within the collection window; the characteristic intersection point is the intersection point of the distribution characteristic line and the sub-segment, which is the core reference point of the lateral distribution of the tunnel crack. When the window center point deviates from the point, the visual field reference of the surface collection window is deviated, and the coordinate positioning of the lateral point lacks reliable reference. At this time, the server can control the high-precision collection unit to move to the characteristic intersection point and make them coincide, so as to calibrate the visual field center of the collection window to the core position of the lateral distribution of the tunnel crack, ensure the accurate and unified coordinate description of the lateral point in the collection window, provide a reliable reference for subsequent position calculation, and avoid positioning errors caused by deviation of the visual field reference;

[0127] Secondly, the server can update the collection multiple corresponding to the collection window until the starting point is located on the adjustment frame line, and obtain an updated value corresponding to the update. Based on the above content, the adjustment frame line is the frame line of the collection window where the starting point is located, which is the fixed reference for position calibration. After updating the collection multiple (such as increasing or decreasing the multiple according to the monitoring accuracy requirement), the high-precision collection unit needs to be moved to make the starting point return to the adjustment frame line again, so as to ensure that the position reference of the collection window is always aligned with the adjustment frame line. The updated value obtained is the change parameter (for example, the collection multiple is updated from 1.0 to 1.5, and the updated value is 0.5) before and after the update of the collection multiple. The value can quantify the influence of the multiple change on the image scale, provide data basis for subsequent correction of the distance parameter of the lateral point, and avoid distance calculation distortion caused by multiple change;

[0128] Then, the server can determine the unit length between each lateral point and the sub-route based on the distribution characteristic line, and determine the update multiple based on the decreasing number of the collection multiple of the collection window and the update value. It can be explained that the unit length is the distance of the lateral point along the distribution characteristic line to the sub-route (based on the image scale of the current collection multiple); the decreasing number of the collection multiple is the operation number when the collection multiple is adjusted before, and the update multiple reflecting the actual image scale can be calculated by combining the update value, wherein the multiple is the actual distance conversion coefficient after calibration, which can correct the distance deviation caused by the change of the collection multiple, that is, through this calculation, the unit length based on the image scale can be converted into the distance parameter conforming to the actual physical space, solving the problem of inaccurate distance positioning caused by image scale distortion, and providing accurate numerical reference for the moving distance of the light unit;

[0129] Finally, the server can update the unit length by the corresponding update multiple, and control the lateral light unit carried by the high-precision collection unit to move towards different lateral points based on the actual length corresponding to each lateral point obtained. Here, the unit length is multiplied by the update multiple to obtain the actual length between the lateral point and the sub-route (i.e. the real distance that the light unit needs to move), and then the light unit can be controlled to move in the direction towards the lateral point by the actual length, which can ensure that the light unit accurately coincides with the lateral point. For example, the unit length is 10 pixels, the update multiple is 0.8 (corresponding to actual 1 pixel = 0.8 mm), and the actual length is 8 mm, so the light unit moves 8 mm to accurately align with the lateral point. The movement control of the baseline calibration and parameter correction completely solves the positioning deviation problem of the light unit, ensures that the light can accurately cover the lateral core area of the crack, and provides clear imaging conditions for the high-precision collection unit, significantly improving the accuracy and reliability of intelligent monitoring of railway tunnel cracks.

[0130] In addition, in the present embodiment, if only the lateral light unit is used to supplement light and collect images, there may be coordinate deviation between the window center point of the collection window and the vertical key point (e.g. the starting point, the end point of the sub-route) of the sub-route, resulting in insufficient light or imaging deviation of the crack area near the vertical point. At the same time, the lack of directional light and supplementary collection mechanism for the vertical point will make the crack details (e.g. the extension form and width change of the tunnel crack in the vertical direction) around the vertical point in the collected image blurred or missing, which cannot fully reflect the overall appearance of the crack corresponding to the sub-route, and finally reduces the integrity of the image data and the reliability of subsequent analysis. Therefore, based on the similar idea of setting the lateral light unit, the above-mentioned "responding to the light of the lateral light unit, controlling the high-precision collection unit to collect images, and obtaining the collection images corresponding to the sub-route" can further include the following steps:

[0131] A real coordinate system is established, and the starting point and the route endpoint determined based on the sub-route and away from the starting point are determined as the first vertical point and the second vertical point, wherein any distribution characteristic line coincides with the X axis of the real coordinate system;

[0132] In response to the horizontal coordinate difference value of any vertical point and the window center point, the high-precision acquisition unit is controlled to move horizontally according to the corresponding coordinate difference value, and the vertical coordinate difference value of the vertical coordinate value of the vertical point and the window center point is obtained.

[0133] The vertical lighting unit carried by the high-precision acquisition unit is controlled to move towards the vertical point based on the vertical coordinate difference value, and in response to the vertical lighting unit illuminating based on the vertical point, the high-precision acquisition unit is controlled to acquire and update the acquisition image based on the obtained vertical supplementary image, to obtain the updated acquisition image.

[0134] For example, in this embodiment, the vertical key point position of the sub-route is illuminated based on the set vertical lighting unit, and in order to ensure the integrity of the image data, the following method steps can be used:

[0135] First, the server can establish a real coordinate system, and determine the starting point and the route endpoint determined based on the sub-route and away from the starting point as the first vertical point and the second vertical point, wherein any distribution characteristic line coincides with the X axis of the real coordinate system. It can be explained that the real coordinate system can be a two-dimensional coordinate system established based on the actual space of the tunnel, which can convert the abstract coordinates in the image into real space positions. Since the first vertical point corresponds to the starting point and the second vertical point corresponds to the end point of the sub-route away from the starting point, they are key boundary points of the sub-route in the vertical direction, therefore, by coinciding the distribution characteristic line (a straight line reflecting the horizontal distribution of the crack) with the X axis (the horizontal axis), the coordinate alignment of the horizontal and vertical positions of the crack can be realized, providing a unified standard for subsequent coordinate difference calculation. The establishment of this coordinate system can provide a spatial reference for accurate description and deviation correction of point positions, avoid positioning errors caused by coordinate system confusion, and ensure that the position analysis of the vertical point has practical significance.

[0136] Secondly, in response to the horizontal coordinate difference value of the corresponding horizontal coordinate value between any vertical point and the window center point, the server can control the high-precision acquisition unit to move horizontally by the corresponding horizontal coordinate difference value, and obtain the vertical coordinate difference value of the vertical coordinate value corresponding to the vertical point and the window center point. Based on the above content, it can be known that the window center point is the geometric center of the acquisition window. If the first or second vertical point has a horizontal coordinate difference value (distance in the X-axis direction) with the point, it indicates that the horizontal position of the acquisition window deviates from the vertical point position, which will cause the imaging of the surrounding area of the vertical point position to be incomplete. Therefore, the high-precision acquisition unit can be controlled to move horizontally by the corresponding difference value, so that the horizontal positions of the window center point and the vertical point are aligned, the horizontal offset is corrected, and the vertical coordinate difference value (distance in the Y-axis direction) is obtained, which can clearly indicate the positional relationship between the vertical point position and the window center point in the vertical direction, thereby providing a precise distance basis for the movement of the vertical lighting unit, and avoiding lighting deviation caused by unknown vertical position.

[0137] Then, the vertical lighting unit carried by the high-precision acquisition unit is controlled to move towards the vertical point based on the vertical coordinate difference value, and in response to the vertical lighting unit lighting based on the vertical point, the high-precision acquisition unit is controlled to acquire, thereby obtaining a vertical supplementary image. It can be indicated that, similar to the horizontal lighting unit, the vertical lighting unit is also a device for providing vertical directional lighting, and moves by a distance corresponding to the vertical coordinate difference value in the direction towards the vertical point, so that the lighting is accurately focused on the vertical point position and the crack area around it, thereby enhancing the brightness and contrast of the area, solving the problem of insufficient vertical area lighting that may exist in the previous horizontal lighting, and ensuring that the vertical supplementary image is acquired in the most suitable state of lighting. The image can clearly capture the crack details around the vertical point position (for example, the morphological change of the tunnel crack at the end), thereby making up for the information loss in the vertical dimension of the original acquisition image.

[0138] Finally, the acquisition image is updated based on the obtained vertical supplementary image, thereby obtaining an updated acquisition image. It can be indicated that the vertical supplementary image focuses on the clear details around the vertical point position, and the fusion and update of the vertical supplementary image and the original acquisition image can supplement and improve the vertical crack information that is blurred or missing in the original image. For example, the crack edge near the second vertical point in the original image is blurred, and the clear details of the supplementary image can replace the corresponding area, so that the complete form of the crack corresponding to the sub-route from the first vertical point to the second vertical point is clearly presented, the acquisition information in the horizontal and vertical directions is integrated, the limitations of single lighting acquisition are eliminated, and the final acquisition image contains not only the horizontal crack details but also the complete vertical boundary area, thereby providing comprehensive and clear image data support for intelligent monitoring of railway tunnel cracks, and significantly improving the integrity and reliability of the monitoring results.

[0139] It can be explained that similar to the transverse light unit, the vertical light unit can also be embodied as an LED lamp bead or other light-emitting elements, which can be slidingly connected with the vertical moving slide rails pre-provided on both sides of the high-precision acquisition unit, wherein the vertical moving slide rails correspond to the transverse moving slide rails perpendicularly, and the corresponding vertical light unit can also include two and be correspondingly provided on the vertical moving slide rails on both sides, so that the vertical light unit can slide based on the vertical moving slide rails.

[0140] Figure 2 The structure diagram of the high-precision acquisition unit and the light unit in the embodiment is shown, as shown in Figure 2 The high-precision acquisition unit corresponds to the center position, specifically Figure 2 C in the figure, and the vertical light unit and the transverse light unit are located around the high-precision acquisition unit, which correspond to L1, L2, L3 and L4 respectively, wherein each light unit can change the position based on a separate moving slide rail, and the length of each moving slide rail can be pre-set, and the specific value of the embodiment is not limited.

[0141] Further, in the embodiment, the above-mentioned "updating the acquisition image based on the obtained vertical supplementary image to obtain an updated acquisition image" can further include the following steps:

[0142] The image part of the vertical supplementary image which is the same as the acquisition image is determined as the to-be-supplemented region, and the first contrast and the second contrast of different image pixels constituting the to-be-supplemented region are determined based on the vertical supplementary image and the acquisition image respectively;

[0143] The image pixel points in the vertical supplementary image whose corresponding first contrast is greater than the second contrast are determined as the supplementary pixel points, and the supplementary pixel points at adjacent positions are connected to obtain each supplementary sub-region;

[0144] The region part of the corresponding to-be-supplemented region in the acquisition image is replaced based on each supplementary sub-region to obtain an updated acquisition image.

[0145] For example, in the embodiment, updating the acquisition image based on the vertical supplementary image can specifically include the following method steps:

[0146] Firstly, the server can determine the vertical supplementary image and the same image part of the collected image as the to-be-supplemented region, and determine the first contrast and the second contrast of different image pixels constituting the to-be-supplemented region based on the vertical supplementary image and the collected image respectively. It can be explained that the to-be-supplemented region is the picture part corresponding to the overlap of the vertical supplementary image and the collected image, and accurately positioning the region can avoid interference to the clear region which is not overlapped, and ensure that the update only acts on the overlapping range which needs to be optimized, and the contrast is a quantitative index of the brightness difference of the pixel points in the image, which directly reflects the distinction degree of the crack profile and the background, wherein the first contrast is the contrast of each pixel point in the to-be-supplemented region of the vertical supplementary image, and the second contrast is the contrast of the corresponding pixel point in the collected image. By calculating the contrast of the two respectively, the clear degree of the same pixel position in the two images can be objectively judged, which provides data basis for subsequent selection of high-quality pixels, and avoids selection deviation caused by visual judgment;

[0147] Secondly, the server can determine the image pixel point in the vertical supplementary image whose corresponding first contrast is greater than the second contrast as a supplementary pixel point, and connect the supplementary pixel points at adjacent positions to obtain each supplementary sub-region. That is, when the first contrast of a certain pixel point in the vertical supplementary image is higher than the second contrast of the collected image, it means that the pixel point is clearer in the supplementary image, which may be caused by the illumination based on the vertical illumination unit. Therefore, it can be determined as a supplementary pixel point to select the high-quality details in the supplementary image. By connecting the adjacent supplementary pixel points to form a supplementary sub-region, the dispersed high-quality pixels can be integrated into a continuous region block, avoiding image splicing marks caused by scattered replacement, ensuring that the updated image is naturally transitioned, and at the same time, the specific range that needs to be replaced is clear, improving the accuracy of the update operation.

[0148] Finally, the server can replace the region part located in the corresponding to-be-supplemented region of the collected image based on each supplementary sub-region to obtain an updated collected image. It can be explained that replacing the region part (low-contrast blurred details) at the corresponding position in the collected image with the supplementary sub-region (high-contrast clear details) in the vertical supplementary image can achieve the image fusion effect of "taking the best and removing the worst", which can make the updated image not only retain the original clear information of other regions of the collected image, but also supplement the crack details around the vertical point, avoid the decline of image quality caused by overall superposition, and maximize the use of the advantage information of the supplementary image, ensuring that the updated collected image realizes detail optimization in the to-be-supplemented region, and presents the full picture of the crack corresponding to the sub-route completely and clearly, providing high-quality image support for subsequent intelligent monitoring links such as crack width measurement and morphology analysis, and significantly improving the accuracy and reliability of railway tunnel crack monitoring.

[0149] In step S5, the following content can also be included:

[0150] determining the route endpoint far away from the starting point as a new starting point based on the sub-route, repeating the above steps until the terminal point is located in the collection image corresponding to any collection times, and obtaining the detection data corresponding to the tunnel crack.

[0151] For example, in the present embodiment, the present embodiment realizes the full-range coverage monitoring of the tunnel crack from the starting point to the terminal point by dynamically updating the starting point, cyclically executing the collection process, and setting the termination condition, ensures the complete and coherent detection data obtained, and provides a comprehensive basis for crack evaluation, ensures that each collected sub-route can be sequentially connected along the extension route of the crack, avoids the repetition or fragmentation of the collection range, for example, the initial starting point is the crack starting point A, the first collected sub-route is A-B, after setting B as the new starting point, the next collected sub-route can extend from B to C, realizing the seamless connection of the crack paragraphs, laying the position foundation for the full-range monitoring, and finally obtaining the detection data corresponding to the tunnel crack.

[0152] Further, in the present embodiment, the above-mentioned "obtaining the detection data corresponding to the tunnel crack" can further include the following steps:

[0153] determining the collection multiples corresponding to the collection images of different collection times, and determining the smallest collection multiple as the splicing multiple;

[0154] reducing each collection image by the corresponding splicing multiple with the image center point as the center to obtain the updated collection image;

[0155] creating each image filling slot in the presentation vertical arrangement located in the data display interface, and filling each collection image into different image filling slots in turn from top to bottom based on the collection order, wherein the sub-routes included in the collection images corresponding to different image filling slots present a line segment connection relationship;

[0156] creating each length filling slot in the presentation horizontal arrangement with each image filling slot, and filling the actual length corresponding to the same collection image into different length filling slots in turn from top to bottom based on the collection order, obtaining the detection data corresponding to the tunnel crack composed of the data display interface.

[0157] For example, in the present embodiment, the acquisition of the detection data can be specifically realized based on the following method steps:

[0158] Firstly, the server can determine the acquisition multiples of the acquisition images corresponding to different acquisition times, and determine the minimum acquisition multiple as the stitching multiple. It can be explained that the acquisition images of different acquisition times may adjust the acquisition multiple due to the aforementioned monitoring accuracy requirement (for example, some images are 1.5 times, and some are 1.0 times), resulting in inconsistent image scaling ratios; the minimum acquisition multiple can ensure that all images can retain the original content after scaling, avoid cutting part of the crack details due to too large multiple, and by determining it as the stitching multiple, it provides a standard benchmark for subsequent uniform image size, ensures that the scaled different acquisition images have consistent proportions, lays a foundation for subsequent orderly stitching, and solves the problem of image size chaos that cannot be displayed coherently;

[0159] Secondly, the server can reduce each acquisition image by the corresponding stitching multiple with the image center point as the center to obtain the updated acquisition image. Taking the image center point as the scaling center can ensure that the core area of the image (i.e., the crack segment corresponding to the sub-route) is always at the image center position, avoiding the crack from deviating from the field of view after scaling; reducing the image by the stitching multiple makes all updated acquisition images have uniform size specifications, for example, images with an acquisition multiple of 1.5 times and images with an acquisition multiple of 1.0 times are reduced by 1.0 times (stitching multiple) after scaling, and the size is consistent and the core crack area position is stable, providing adaptive image materials for subsequent orderly filling and arrangement;

[0160] Then, the server can create each image filling slot in the presentation vertical arrangement in the data display interface, and fill each acquisition image into different image filling slots in sequence from top to bottom based on the acquisition order, wherein the sub-routes included in the acquisition images corresponding to different image filling slots present a line segment connection relationship. It can be explained that the vertically arranged image filling slots provide an orderly display space for the acquisition images, and filling based on the acquisition order (i.e., the order of the high-precision acquisition unit moving along the extension route) can restore the extension process of the crack from the starting point to the ending point; the line segment connection relationship of the sub-routes means that the end of the sub-route of the previous image and the start of the sub-route of the next image are connected and linked in the display interface, and the continuous form of the crack is intuitively presented, so that the dispersed images can be converted into a "visual crack chain", solving the problem that a single image cannot display a complete crack, and enabling the monitoring personnel to quickly grasp the overall trend and segmented details of the crack;

[0161] Finally, the server can further create length filling slots in transverse arrangement with each image filling slot, and fill the actual length corresponding to the same collected image into different length filling slots from top to bottom based on the collection sequence, to obtain detection data of the corresponding tunnel crack composed of the data display interface, wherein the length filling slots in transverse arrangement correspond to the image filling slots one by one, ensuring that each crack image can be directly associated with its actual length data (for example, the actual length of a certain crack corresponding to a sub-route is 0.8 meters); the length data is filled according to the collection sequence, which is consistent with the arrangement logic of the image, realizing clear association of "one image corresponds to one length", so that the detection data contains not only the visual form of the tunnel crack, but also the accurate size information, and the monitoring personnel can quickly obtain the complete information of each crack without repeated comparison, significantly improving the readability and utilization efficiency of the data, and providing intuitive and reliable comprehensive detection data support for the evaluation, analysis and decision of the railway tunnel crack.

[0162] In summary, the embodiment effectively breaks through the bottleneck of insufficient accuracy of tunnel crack monitoring in the manual inspection mode, significantly improves the accuracy and reliability of crack parameter measurement, and provides high-quality data support for tunnel structure disease evaluation. Specifically, the following aspects can be embodied:

[0163] 1. In the aspect of accurate capture of crack details, the embodiment solves the problems of uneven lighting and difficulty in identifying fine cracks in manual inspection through the coordinated design of transverse lighting adaptation and high-precision collection. Specifically, based on the first and second transverse points on both sides of the sub-route, the transverse lighting unit can be controlled to move to the target position and turn on the light, forming a directional light source perpendicular to the crack direction. Thus, based on the directional lighting, a clear light and dark contrast can be formed on the edge of the crack, distinguishing fine cracks from interference features such as stains and scratches on the lining surface, and avoiding the problem of detail blurring caused by scattered flashlight lighting in manual inspection. At the same time, the high-precision collection unit collects images under the guidance of directional lighting, which can completely retain the micro features of crack edge profile and width variation, and the detail clarity of the collected images is tens of times higher than that of manual visual observation, laying a foundation for accurate measurement of crack width and shape.

[0164] 2. In the aspect of continuous monitoring of the whole crack, the embodiment realizes complete coverage of the crack extension trajectory through route tracking and segment-by-segment iterative collection mode. First, the starting point, ending point and extension route of the crack are determined, and then the high-precision collection unit is controlled to move along the route in segments. The sub-route is divided into units based on the collection window. After completing the collection of each sub-route, the starting point is updated and the operation is repeated until the entire crack is covered. Continuous collection images of the crack from the starting point to the ending point can be obtained, avoiding omission of the middle section of the crack and accurately capturing changes in the extension direction of the crack, solving the technical problem that it is difficult to form a complete crack data chain in manual inspection.

[0165] 3. Regarding the improvement of measurement accuracy, this embodiment significantly reduces measurement errors through clear positioning benchmarks and data traceability. Using the crack extension route as a benchmark, the acquisition window is precisely aligned with the sub-route, ensuring that the shooting angle of each acquired image is always focused on the core area of ​​the crack, avoiding the perspective deviation that occurs when measuring with handheld tools. At the same time, the precise overlap of the lateral illumination unit and the lateral point ensures the consistency of illumination conditions for images acquired from different sub-routes, eliminating image comparison errors caused by illumination differences. Furthermore, the detection data acquired segment by segment can be spliced ​​together through sub-route association to form a complete digital archive of the crack. This not only allows for the direct extraction of macroscopic parameters such as crack length and extension direction, but also enables the calculation of width changes in each segment based on continuous images, thus improving monitoring accuracy.

[0166] Another embodiment of the present invention provides a railway tunnel crack monitoring system. Figure 3 Its corresponding system block diagram, such as Figure 3 As shown, the system includes:

[0167] The route determination module is configured to determine the start point, end point, and extended route determined by the start point and end point of the corresponding tunnel crack.

[0168] The acquisition and movement module is configured to control the high-precision acquisition unit to move along the extended route from the starting point until the starting point is located at the window frame of the acquisition window of the high-precision acquisition unit.

[0169] The distribution determination module is configured to determine the sub-route corresponding to the acquisition window of the extended route, and to determine the first lateral point and the second lateral point with distribution characteristics located on both sides of the sub-route based on the tunnel crack;

[0170] The image acquisition module is configured to control the lateral illumination unit carried by the high-precision acquisition unit to move to coincide with the lateral point, and respond to the lateral illumination unit to provide illumination, thereby controlling the high-precision acquisition unit to acquire images of the corresponding sub-route.

[0171] The data integration module is configured to determine the route endpoints far from the starting point as new starting points based on the sub-route, repeat the above steps until the termination point is located in the image acquired for any number of acquisitions, and obtain the detection data of the corresponding tunnel crack.

[0172] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been described in detail in order to not obscure the understanding of this description.

[0173] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been described in detail in order to not obscure the understanding of this description.

[0174] Similarly, it is to be understood that the mechanical details of the inventive features sometimes are grouped into a single embodiment, figure or description of related embodiments in this disclosure. This disclosure is not to be interpreted to be limited to the embodiment(s) illustrated.

[0175] Those skilled in the art will understand that the modules, or units, or components of the devices in the examples disclosed herein can be arranged in a device as described in the examples, or alternatively can be located in one or more devices different from the devices in the examples. The modules in the foregoing examples can be combined into a module or further divided into multiple sub-modules.

[0176] Those skilled in the art will understand that the modules in the devices in the examples can be adaptively changed and arranged in one or more devices different from the examples. The modules or units or components in the examples can be combined into a module or unit or component, and further divided into multiple sub-modules or sub-units or sub-components.

[0177] Further, those skilled in the art will understand that the combination of features of different embodiments means within the scope of the application and forms different embodiments, although some of the examples described herein include certain features included in other examples but not others.

[0178] Further, some of the examples described herein are combinations of method or method elements, which are implemented by a processor of a computer system or by other means of carrying out the function of the method elements. Thus, a processor with the necessary instructions for carrying out such a method or element of a method forms a means for carrying out the method or element of a method. Furthermore, an element described herein of a means for carrying out a particular function is a means for carrying out the function if the element fulfills the purpose of the function when carried out. Thus, a claim of a method or method elements reciting means for carrying out a function is intended to cover both a processor with the necessary instructions for carrying out the function and a processor which in combination with the necessary structure for carrying out the function forms a means for carrying out the function.

[0179] As used herein, unless otherwise indicated, the use of the ordinal adjectives "first", "second", "third", etc., merely to distinguish different instances of a similar object do not imply a meaning that the objects must be in a given order, or that one comes before or after another.

[0180] While the application has been described in terms of several embodiments, those skilled in the art will recognize that the application can be practiced with modifications within the spirit and scope of the application, which are encompassed by the description. Furthermore, it is to be appreciated that the description set forth herein focuses on the functioning and utility of the application, and thus describes in some instances internal activities of a computer, data store, and hardware components in terms of operations performed by computer components. Such workflow descriptions are used by those skilled in the art to describe what pieces of hardware or software are involved in performing the described operations, and thus a particular piece of hardware or software should not be construed as being limited to performing only the operations described in the workflow in which it is involved.

Claims

1. A method for monitoring cracks in railway tunnels, characterized in that, include: Determine the starting and ending points of the corresponding tunnel cracks, as well as the extension route determined by the starting and ending points. The high-precision acquisition unit is controlled to move along the extended route from the starting point until the starting point is located at the window frame of the acquisition window of the high-precision acquisition unit. Determine the sub-route corresponding to the acquisition window of the extended route, and determine the first lateral point and the second lateral point with distribution characteristics on both sides of the sub-route based on the tunnel crack; The high-precision acquisition unit is controlled to move the lateral illumination unit to coincide with the lateral point, and the lateral illumination unit responds to the illumination, thereby controlling the high-precision acquisition unit to acquire images of the corresponding sub-route. Based on the sub-route, the route endpoint far from the starting point is determined as the new starting point. The above steps are repeated until the termination point is located in the image of any acquisition number, and the detection data of the corresponding tunnel crack is obtained. The high-precision acquisition unit is controlled to move along the extended route from the starting point until the starting point is located within the window frame of the acquisition window of the high-precision acquisition unit. This process then includes: The window frame line of the acquisition window with the starting point located at the high-precision acquisition unit is determined as the adjustment frame line, and the two window frame lines perpendicular to the adjustment frame line are determined as the verification frame lines; The response determines that any check frame line coincides with a tunnel crack based on the acquisition window. The acquisition multiplier of the corresponding acquisition window is then reduced by the same baseline multiplier to obtain the acquisition multiplier corresponding to different reduction times. The response determines that each verification frame does not coincide with the tunnel crack based on the acquisition multiple corresponding to any decreasing number of acquisitions. It controls the high-precision acquisition unit to move away from the starting point along the extension route until the starting point is located at the adjustment frame. The sub-route corresponding to the acquisition window of the extended route is determined, and based on the tunnel cracks, the first and second lateral points with distributional characteristics located on both sides of the sub-route are determined, including: The sub-path is divided into arrays, and each second array line is generated along a direction perpendicular to the tangent direction of the sub-path for each second array point obtained by the respective path; Determine the first intersection point and the second intersection point where each second array line intersects with the crack profile of the tunnel crack, and determine the intersection distance between the first intersection point and the second intersection point; The maximum intersection distance is defined as the maximum distance. Then, with the second array line corresponding to the maximum distance as the center, a calculation process is constructed to calculate the difference between the corresponding intersection distance and the maximum distance in turn, and different distance differences are obtained. If any distance difference is less than a preset difference, the second array line corresponding to that distance difference is determined as the distribution characteristic line; otherwise, the calculation process is stopped. The first and second intersection points of the distribution characteristic lines corresponding to the center positions along the sub-route are determined as the first and second lateral points with distribution characteristics.

2. The method according to claim 1, characterized in that, include: Determine the starting and ending points of the corresponding tunnel cracks, as well as the extension route determined by the starting and ending points, including: In response to receiving a crack monitoring signal carrying location information sent by any employee terminal, the system controls the drone to fly to the location information at a preset flight altitude to collect the information and sends the obtained flight image to the employee terminal. The system responds to the location determination signal sent by the receiving employee based on the flight image, determines the crack region located in the flight image that indicates the tunnel crack based on image recognition, and determines the two image contour points with the largest corresponding distance that make up the crack region as the start point and end point. The extension route of the corresponding tunnel crack is determined based on the established start and end lines connecting the starting and ending points.

3. The railway tunnel crack monitoring method according to claim 2, characterized in that, Based on the established start and end lines connecting the starting and ending points, the extension route of the corresponding tunnel crack is determined, including: Generate each first array line for each first array point obtained by arraying the start and end lines along a direction perpendicular to the start and end lines; Establish an image coordinate system, where the start and end lines coincide with the Y-axis of the image coordinate system; The average value of the corresponding horizontal coordinate values ​​of all image coordinate points that coincide with the region contour for each first array line is calculated, and the image coordinate points located in the crack region are determined as route points based on the obtained average horizontal coordinate values. Connect the route points that are adjacent to each other along the extension direction of the start and end lines to obtain the extended route.

4. The method according to claim 1, characterized in that, Controlling the lateral illumination unit carried by the high-precision acquisition unit to move until it coincides with the lateral point includes: If the center point of the response acquisition window does not coincide with the feature intersection point where the distribution feature line of the corresponding horizontal point intersects with the sub-line segment, the high-precision acquisition unit is controlled to move along the direction from the center point of the window toward the feature intersection point until the center point of the window coincides with the feature intersection point. Update the acquisition multiplier of the corresponding acquisition window until the starting point is located at the adjustment frame line, and obtain the corresponding updated value. The unit length between each horizontal point and the sub-route is determined based on the distribution feature line, and the update factor is determined based on the number of decreases corresponding to the acquisition factor of the acquisition window and the update value. The unit length is updated by a corresponding update factor, and the lateral illumination unit carried by the high-precision acquisition unit is controlled to move towards different lateral points based on the actual length of each lateral point.

5. The method according to claim 4, characterized in that, The system responds to illumination from the lateral illumination unit, controls the high-precision acquisition unit to acquire images of the corresponding sub-route, and then includes: Establish a real coordinate system, and define the starting point and the route endpoints far from the starting point, determined based on the sub-route, as the first vertical point and the second vertical point, respectively, wherein any distribution feature line coincides with the X-axis of the real coordinate system; In response to the existence of a horizontal coordinate difference between any vertical point and the center point of the window, the high-precision acquisition unit is controlled to move horizontally according to the corresponding coordinate difference, and the vertical coordinate difference between the vertical point and the center point of the window is obtained. The high-precision acquisition unit controls the vertical illumination unit carried by the high-precision acquisition unit to move towards the vertical point based on the vertical coordinate difference, and responds to the vertical illumination unit to illuminate based on the vertical point, controls the high-precision acquisition unit to acquire data, and updates the acquired image based on the obtained vertical supplementary image to obtain the updated acquired image.

6. The method according to claim 5, characterized in that, The acquired image is updated based on the obtained vertical supplementary image to obtain the updated acquired image, including: The image portion that is the same as the vertically supplemented image and the acquired image is determined as the region to be supplemented, and the first contrast and second contrast of different image pixels that make up the region to be supplemented are determined based on the vertically supplemented image and the acquired image, respectively. Image pixels in the vertical supplementary image whose first contrast is greater than the second contrast are identified as supplementary pixels, and supplementary pixels in adjacent positions are connected to obtain each supplementary sub-region. The corresponding area to be supplemented in the acquired image is replaced based on each supplementary sub-region to obtain the updated acquired image.

7. The method according to claim 4, characterized in that, The detection data for the corresponding tunnel cracks were obtained, including: Determine the acquisition factor for images acquired at different acquisition times, and set the minimum acquisition factor as the stitching factor; The captured images are reduced by the corresponding stitching factor using the image center point as the center to obtain the updated captured images; Create vertically arranged image fill slots on the data display interface, and fill each captured image into different image fill slots from top to bottom according to the capture order. The sub-routes of the captured images corresponding to different image fill slots are presented as line segment connections. Create filling slots of various lengths that are horizontally arranged with each image filling slot, and fill the filling slots of different lengths sequentially from top to bottom according to the acquisition order of the same acquired image, so as to obtain the detection data of the corresponding tunnel cracks composed of the data display interface.

8. A railway tunnel crack monitoring system, characterized in that, include: The route determination module is configured to determine the start point, end point, and extended route determined by the start point and end point of the corresponding tunnel crack. The acquisition and movement module is configured to control the high-precision acquisition unit to move along the extended route from the starting point until the starting point is located at the window frame of the acquisition window of the high-precision acquisition unit. The distribution determination module is configured to determine the sub-route corresponding to the acquisition window of the extended route, and to determine the first lateral point and the second lateral point with distribution characteristics located on both sides of the sub-route based on the tunnel crack; The image acquisition module is configured to control the lateral illumination unit carried by the high-precision acquisition unit to move to coincide with the lateral point, and respond to the lateral illumination unit to provide illumination, thereby controlling the high-precision acquisition unit to acquire images of the corresponding sub-route. The data integration module is configured to determine the route endpoints far from the starting point as new starting points based on the sub-route, repeat the above steps until the termination point is located in the image acquired for any number of acquisitions, and obtain the detection data of the corresponding tunnel crack. The high-precision acquisition unit is controlled to move along the extended route from the starting point until the starting point is located within the window frame of the acquisition window of the high-precision acquisition unit. This process then includes: The window frame line of the acquisition window with the starting point located at the high-precision acquisition unit is determined as the adjustment frame line, and the two window frame lines perpendicular to the adjustment frame line are determined as the verification frame lines; The response determines that any check frame line coincides with a tunnel crack based on the acquisition window. The acquisition multiplier of the corresponding acquisition window is then reduced by the same baseline multiplier to obtain the acquisition multiplier corresponding to different reduction times. The response determines that each verification frame does not coincide with the tunnel crack based on the acquisition multiple corresponding to any decreasing number of acquisitions. It controls the high-precision acquisition unit to move away from the starting point along the extension route until the starting point is located at the adjustment frame. The sub-route corresponding to the acquisition window of the extended route is determined, and based on the tunnel cracks, the first and second lateral points with distributional characteristics located on both sides of the sub-route are determined, including: The sub-path is divided into arrays, and each second array line is generated along a direction perpendicular to the tangent direction of the sub-path for each second array point obtained by the respective path; Determine the first intersection point and the second intersection point where each second array line intersects with the crack profile of the tunnel crack, and determine the intersection distance between the first intersection point and the second intersection point; The maximum intersection distance is defined as the maximum distance. Then, with the second array line corresponding to the maximum distance as the center, a calculation process is constructed to calculate the difference between the corresponding intersection distance and the maximum distance in turn, and different distance differences are obtained. If any distance difference is less than a preset difference, the second array line corresponding to that distance difference is determined as the distribution characteristic line; otherwise, the calculation process is stopped. The first and second intersection points of the distribution characteristic lines corresponding to the center positions along the sub-route are determined as the first and second lateral points with distribution characteristics.

Images