A Visual Recognition-Based System and Method for Monitoring Deformation of Surrounding Rock in Tunnels

Abstract

This invention provides a tunnel surrounding rock deformation monitoring system and method based on visual recognition, belonging to the field of computer vision technology. The invention acquires initial and current images of the tunnel surrounding rock by installing monitoring equipment and utilizing visual recognition technology. Based on a visual image processing algorithm, the current image is compared with the initial image to calculate the horizontal and vertical displacement at the tunnel entrance / exit, the change in the tilt angle of the surrounding rock support structure, the displacement of cracks at the surrounding rock junction, and the deformation rate of cracks at the surrounding rock junction. Based on these data, a surrounding rock deformation risk index is generated. Finally, a safety threshold is established, and the generated risk index is compared with the safety threshold to determine whether it exceeds the set standard. This invention, through the installation of monitoring equipment and the application of visual recognition technology, achieves real-time monitoring and early warning of tunnel surrounding rock deformation risks, ensuring construction safety.

Description

Technical Field

[0001] This invention relates to the field of computer vision technology, specifically to a tunnel surrounding rock deformation monitoring system and method based on visual recognition. Background Technology

[0002] Tunnel surrounding rock deformation monitoring is a crucial aspect of underground engineering safety. Traditional monitoring methods rely on geological surveys and sensors, which suffer from problems such as excessive manual intervention and low efficiency. With the development of computer technology and image processing technology, visual recognition has gradually become an effective monitoring tool. By acquiring images of the surrounding rock through high-resolution cameras and utilizing deep learning algorithms, rapid and accurate deformation detection and analysis can be achieved, improving the real-time performance and accuracy of monitoring.

[0003] Currently, visual recognition-based monitoring technology is developing rapidly. Lower equipment costs and the trend towards intelligent systems are making its application increasingly widespread, with many construction companies beginning to adopt this method to replace traditional monitoring methods. Meanwhile, the gradual improvement of relevant regulations and standards provides a guarantee for the healthy development of the industry, and the increasing number of successful cases further proves the effectiveness of this technology in areas such as urban tunnels and mines, improving overall safety.

[0004] In existing technologies, traditional methods for monitoring deformation of tunnel surrounding rock typically rely on manual inspection and traditional sensors, which suffer from problems such as low efficiency, poor real-time performance, and high cost. These methods not only require frequent manual intervention but are also prone to errors due to human factors, making it difficult to conduct large-scale and long-term monitoring. Furthermore, traditional methods often fail to adequately cover key areas of the surrounding rock, leading to the omission of potential hazards.

[0005] Secondly, existing technologies are generally simplistic in their analysis of monitoring data and risk assessment, lacking a systematic risk index generation mechanism and failing to provide comprehensive risk assessment and early warning by integrating multiple monitoring data. This means that when surrounding rock deformation occurs, relevant personnel may not be able to obtain sufficient information in a timely manner to react quickly, thereby increasing safety hazards. Furthermore, existing technologies in tunnel surrounding rock monitoring are slow to respond to environmental changes, lack monitoring accuracy, and have unclear critical risk assessments. In addition, traditional monitoring methods are insufficient in accurately identifying high-risk areas and locating surrounding rock deformation.

[0006] Therefore, it is necessary to provide a tunnel surrounding rock deformation monitoring system and method based on visual recognition to solve the aforementioned problem.

[0007] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] The purpose of this invention is to provide a tunnel surrounding rock deformation monitoring system and method based on visual recognition, so as to solve the problems mentioned in the background art.

[0009] To achieve the above objectives, the present invention provides the following technical solution:

[0010] A tunnel surrounding rock deformation monitoring system based on visual recognition, comprising the following steps:

[0011] The image acquisition module is used to acquire the initial surrounding rock image before tunnel construction using visual recognition technology, and to acquire the current surrounding rock image in real time during construction. The image acquisition module is a high-resolution camera and an image processing unit.

[0012] The surrounding rock deformation parameter calculation module is used to analyze and compare the initial surrounding rock image with the current surrounding rock image, calculate the horizontal and vertical displacement of the surrounding rock at the tunnel entrance and exit, as well as the change in the tilt angle of the surrounding rock support structure, and calculate the deformation rate of the cracks at the surrounding rock junction by monitoring the displacement of the cracks at the surrounding rock junction.

[0013] The deformation risk index generation module is used to generate a surrounding rock deformation risk index based on the calculated horizontal and vertical displacement inside the surrounding rock, the change in the inclination angle of the surrounding rock support structure, and the deformation rate of the cracks at the junction of the surrounding rock.

[0014] The safety monitoring and early warning module is used to set a safety threshold, compare the generated surrounding rock deformation risk index with the safety threshold, and determine whether the surrounding rock deformation risk index exceeds the set safety threshold. If it exceeds the safety threshold, an early warning mechanism is triggered and an alarm message is sent.

[0015] Furthermore, the initial and current surrounding rock images before tunnel construction are obtained, and the initial and current surrounding rock images are analyzed and compared. The method used is as follows:

[0016] Before tunnel construction, a high-resolution camera is used to scan the surrounding rock of the tunnel to obtain clear initial images of the surrounding rock. The images are preprocessed by the image processing unit, including noise reduction, contrast enhancement and brightness adjustment, to improve the accuracy of subsequent identification. Image segmentation technology is used to separate key areas from the background image.

[0017] The key areas include tunnel entrances and exits, support structure nodes, and junctions with surrounding rock. Feature point detection algorithms are used in these key areas to mark multiple feature points in the key areas of the initial and current surrounding rock images, ensuring that these areas are fully covered. The coordinates of each feature point are recorded, and the feature points in the key areas of the current and initial surrounding rock images are aligned.

[0018] Furthermore, the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit, as well as the changes in the inclination angles of the surrounding rock support structure nodes, are calculated. The deformation rate of the cracks at the surrounding rock junctions is calculated by monitoring the displacement of the cracks. The method used is as follows:

[0019] Select using feature point matching algorithm The feature points are evenly distributed on the surface and inside of the surrounding rock at the tunnel entrance and exit. For each matched feature point, let the coordinates of the feature point in the initial surrounding rock image be... The coordinates of the feature points in the current surrounding rock image are: The formulas used to calculate the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit are as follows:

[0020]

[0021]

[0022] in, , These represent the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit, respectively. , These represent the current surrounding rock image, specifically the first... The x and y coordinates of each feature point , These represent the first and second images of the initial surrounding rock. The x and y coordinates of each feature point This is the index of feature points in the initial surrounding rock image. This represents the current acquisition time of the surrounding rock image. The current surrounding rock image is the first one compared to the initial surrounding rock image. Feature point indices aligned with feature points, and , This represents the total number of feature points in the surrounding rock image.

[0023] The starting and ending nodes of the surrounding rock support structure are selected as matching feature points to calculate the change in tilt angle. Let the two feature points of the support structure in the initial surrounding rock image be... , Let the feature points corresponding to the support structure matching in the current surrounding rock image be... , and utilize , As the starting node of the support structure in the initial surrounding rock image and the current surrounding rock image, using , As the terminal node of the support structure in the initial and current surrounding rock images, the formula used to calculate the slope of the support structure in the initial and current surrounding rock images is as follows:

[0024]

[0025]

[0026] in, , These represent the slopes of the surrounding rock support structure in the initial and current surrounding rock images, respectively. , and These represent the x and y coordinates of two feature points in the support structure of the initial surrounding rock image. , and These are the x and y coordinates of two feature points in the current surrounding rock image support structure;

[0027] The formula used to calculate the change in inclination angle of the surrounding rock support structure based on the slope is:

[0028]

[0029]

[0030]

[0031] in, This indicates the change in the inclination angle of the surrounding rock support structure. , These are the tilt angles under the initial surrounding rock image and the current surrounding rock image, respectively;

[0032] Feature points are set at both ends of the crack at the junction of the surrounding rock and the surrounding rock. , As the location of feature points in the initial surrounding rock image, and , The formula used to calculate the displacement of the crack at the junction of the surrounding rock, based on the location of the feature point in the current surrounding rock image, is as follows:

[0033]

[0034]

[0035] in, This indicates the displacement of the crack at the junction of the surrounding rock and the surrounding rock. , and , These represent the x and y coordinates of two feature points on the crack at the junction in the initial surrounding rock image. , and , These are the x and y coordinates of two feature points on the crack at the junction in the current surrounding rock image. This represents the deformation rate of the crack at the junction of the surrounding rock and the surrounding rock. This represents the time interval between the acquisition of the current surrounding rock image and the initial surrounding rock image.

[0036] Furthermore, the formula used to generate the surrounding rock deformation risk index is as follows:

[0037]

[0038] in, This indicates the risk index of surrounding rock deformation.

[0039] Furthermore, the generated surrounding rock deformation risk index is compared with the safety threshold to determine whether the surrounding rock deformation risk index exceeds the established safety threshold. The logical formula used is as follows:

[0040]

[0041] in, This represents the logical judgment value for determining whether to trigger the early warning mechanism. hour, This indicates a risk of deformation in the surrounding rock of the tunnel, triggering an alarm message; when hour, This indicates that no risk of deformation of the surrounding rock in the tunnel has been detected, and there is no need to trigger an alarm at this time. The established safety threshold.

[0042] This invention also provides a method for monitoring tunnel surrounding rock deformation based on visual recognition. The monitoring method employs the aforementioned visual recognition-based tunnel surrounding rock deformation monitoring system, comprising:

[0043] Step 1: Use visual recognition technology to acquire the initial surrounding rock image before tunnel construction, and acquire the current surrounding rock image in real time during construction. The image acquisition module is a high-resolution camera and an image processing unit.

[0044] Step 2: Analyze and compare the initial surrounding rock image with the current surrounding rock image, calculate the horizontal and vertical displacement of the surrounding rock at the tunnel entrance and exit, as well as the change in the tilt angle of the surrounding rock support structure, and calculate the deformation rate of the cracks at the surrounding rock junction by monitoring the displacement of the cracks at the surrounding rock junction.

[0045] Step 3: Generate the surrounding rock deformation risk index by comprehensively considering the calculated horizontal and vertical displacements inside the surrounding rock, the change in the inclination angle of the surrounding rock support structure, and the deformation rate of cracks at the junction of the surrounding rock.

[0046] Step 4: Set a safety threshold. Compare the generated surrounding rock deformation risk index with the safety threshold to determine whether the surrounding rock deformation risk index exceeds the set safety threshold. If it exceeds the safety threshold, trigger the early warning mechanism and send an alarm message.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] First, this invention introduces a vision-based tunnel surrounding rock deformation monitoring system, achieving efficient and real-time data acquisition and analysis. Compared to traditional monitoring methods relying on manual labor and fixed sensors, this system can automatically acquire images of the surrounding rock's condition, significantly reducing the need for manual intervention and the possibility of human error. Furthermore, it utilizes a high-resolution camera to comprehensively scan the surrounding rock, ensuring full coverage of key areas and improving the accuracy and comprehensiveness of monitoring. This automated and efficient monitoring method can support large-scale and long-term monitoring needs, promptly identifying potential risks and thus enhancing the safety of tunnel construction.

[0049] Secondly, this invention possesses a systematic advantage in the analysis and risk assessment of monitoring data. By comprehensively calculating the horizontal displacement, vertical displacement, tilt angle changes, and crack displacement of the surrounding rock, it generates a surrounding rock deformation risk index, providing a more scientific and comprehensive risk assessment method. Compared with existing technologies, this system can achieve automated early warning, promptly issuing alarm information to ensure that relevant personnel can quickly take emergency measures. Furthermore, its flexible data transmission and processing capabilities enable the system to maintain efficient monitoring performance in different construction environments, further enhancing the overall safety level. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the system module flow of the present invention.

[0051] Figure 2 This is a schematic diagram of the overall method flow of the present invention. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0053] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly. Example

[0054] Please see Figure 1 A tunnel surrounding rock deformation monitoring system based on visual recognition, the specific steps of which include:

[0055] The image acquisition module is used to acquire the initial surrounding rock image before tunnel construction using visual recognition technology, and to acquire the current surrounding rock image in real time during construction. The image acquisition module is a high-resolution camera and an image processing unit.

[0056] The surrounding rock deformation parameter calculation module is used to analyze and compare the initial surrounding rock image with the current surrounding rock image, calculate the horizontal and vertical displacement of the surrounding rock at the tunnel entrance and exit, as well as the change in the tilt angle of the surrounding rock support structure, and calculate the deformation rate of the cracks at the surrounding rock junction by monitoring the displacement of the cracks at the surrounding rock junction.

[0057] The deformation risk index generation module is used to generate a surrounding rock deformation risk index based on the calculated horizontal and vertical displacement inside the surrounding rock, the change in the inclination angle of the surrounding rock support structure, and the deformation rate of the cracks at the junction of the surrounding rock.

[0058] The safety monitoring and early warning module is used to set a safety threshold, compare the generated surrounding rock deformation risk index with the safety threshold, and determine whether the surrounding rock deformation risk index exceeds the set safety threshold. If it exceeds the safety threshold, an early warning mechanism is triggered and an alarm message is sent.

[0059] It is important to note that acquiring initial images of the tunnel's surrounding rock using visual recognition technology is crucial, as it provides a baseline reference for subsequent monitoring. This ensures that key areas, such as tunnel entrances and exits, support structure nodes, and rock-surrounding junctions, are adequately covered, enabling accurate identification and analysis of rock deformation. Comprehensive scanning and image processing enhance image identifiability, ensuring key features are highlighted, laying the foundation for real-time monitoring and analysis. Furthermore, real-time data transmission to a central control system or cloud platform enables rapid risk assessment and early warning, improving the response to potential safety hazards. Therefore, this setup not only enhances the accuracy and efficiency of monitoring but also provides strong support for the safety management of tunnel construction and operation.

[0060] Therefore, it is necessary to obtain the initial and current images of the surrounding rock before tunnel construction, and to analyze and compare the initial and current images. The method used is as follows:

[0061] Before tunnel construction, a high-resolution camera is used to scan the surrounding rock of the tunnel to obtain clear initial images of the surrounding rock. The images are preprocessed by the image processing unit, including noise reduction, contrast enhancement and brightness adjustment, to improve the accuracy of subsequent identification. Image segmentation technology is used to separate key areas from the background image.

[0062] The key areas include tunnel entrances and exits, support structure nodes, and junctions with surrounding rock. Feature point detection algorithms are used in these key areas to mark multiple feature points in the key areas of the initial and current surrounding rock images, ensuring that these areas are fully covered. The coordinates of each feature point are recorded, and the feature points in the key areas of the current and initial surrounding rock images are aligned.

[0063] It is important to note that calculating the horizontal and vertical displacements of the surrounding rock at tunnel entrances and exits, the changes in the tilt angle of the support structure, and the displacement of cracks at the junctions of the surrounding rock are crucial for monitoring and assessing the deformation state of the tunnel's surrounding rock. This data helps to identify potential structural risks in a timely manner, ensuring the safety of construction and operation. Through feature point detection and matching algorithms, the deformation of key areas can be accurately tracked, providing quantitative deformation rate and trend analysis, thus providing a scientific basis for engineering decisions. Furthermore, a real-time feedback mechanism based on this monitoring data can quickly trigger early warnings, ensuring that relevant personnel can take timely emergency measures when deformation reaches a set threshold.

[0064] Therefore, it is necessary to calculate the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit, as well as the change in inclination angle of the nodes of the surrounding rock support structure. Furthermore, the deformation rate of the cracks at the surrounding rock junctions is calculated by monitoring the displacement of the cracks. The method used is as follows:

[0065] Select using feature point matching algorithm The feature points are evenly distributed on the surface and inside of the surrounding rock at the tunnel entrance and exit. For each matched feature point, let the coordinates of the feature point in the initial surrounding rock image be... The coordinates of the feature points in the current surrounding rock image are: The formulas used to calculate the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit are as follows:

[0066]

[0067]

[0068] in, , These represent the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit, respectively. , These represent the current surrounding rock image, specifically the first... The x and y coordinates of each feature point , These represent the first and second images of the initial surrounding rock. The x and y coordinates of each feature point This is the index of feature points in the initial surrounding rock image. This represents the current acquisition time of the surrounding rock image. The current surrounding rock image is the first one compared to the initial surrounding rock image. Feature point indices aligned with feature points, and , This represents the total number of feature points in the surrounding rock image.

[0069] The starting and ending nodes of the surrounding rock support structure are selected as matching feature points to calculate the change in tilt angle. Let the two feature points of the support structure in the initial surrounding rock image be... , Let the feature points corresponding to the support structure matching in the current surrounding rock image be... , and utilize , As the starting node of the support structure in the initial surrounding rock image and the current surrounding rock image, using , As the terminal node of the support structure in the initial and current surrounding rock images, the formula used to calculate the slope of the support structure in the initial and current surrounding rock images is as follows:

[0070]

[0071]

[0072] in, , These represent the slopes of the surrounding rock support structure in the initial and current surrounding rock images, respectively. , and These represent the x and y coordinates of two feature points in the support structure of the initial surrounding rock image. , and These are the x and y coordinates of two feature points in the current surrounding rock image support structure;

[0073] The formula used to calculate the change in inclination angle of the surrounding rock support structure based on the slope is:

[0074]

[0075]

[0076]

[0077] in, This indicates the change in the inclination angle of the surrounding rock support structure. , These are the tilt angles under the initial surrounding rock image and the current surrounding rock image, respectively;

[0078] Feature points are set at both ends of the crack at the junction of the surrounding rock and the surrounding rock. , As the location of feature points in the initial surrounding rock image, and , The formula used to calculate the displacement of the crack at the junction of the surrounding rock, based on the location of the feature point in the current surrounding rock image, is as follows:

[0079]

[0080]

[0081] in, This indicates the displacement of the crack at the junction of the surrounding rock and the surrounding rock. , and , These represent the x and y coordinates of two feature points on the crack at the junction in the initial surrounding rock image. , and , These are the x and y coordinates of two feature points on the crack at the junction in the current surrounding rock image. This represents the deformation rate of the crack at the junction of the surrounding rock and the surrounding rock. This represents the time interval between the acquisition of the current surrounding rock image and the initial surrounding rock image.

[0082] It should be noted that the purpose of generating the surrounding rock deformation risk index is to quantify the deformation risk of the surrounding rock by comprehensively considering horizontal and vertical displacement, changes in dip angle, and crack displacement, thus providing an intuitive assessment standard. The design takes into account the influence of various deformation factors. In particular, the use of exponential functions to handle changes in tilt angle can effectively amplify potential risks, reflecting that small changes in tilt may lead to a significant increase in risk. In addition, the setting of risk index can help engineers quickly judge the safety status of the surrounding rock under different deformation states and formulate corresponding response strategies. For example, by combining the changing trend of risk index, construction methods can be adjusted in a timely manner, support measures can be strengthened, or surrounding rock can be reinforced, thereby effectively reducing safety hazards.

[0083] Therefore, it is necessary to generate a surrounding rock deformation risk index, based on the following formula:

[0084]

[0085] in, This represents the surrounding rock deformation risk index; in the above formula, and An increase in the value of will lead to an increase in its absolute value, thereby increasing the surrounding rock deformation risk index. The value also increases because when the absolute value of these displacements increases, it means that the surrounding rock has undergone more significant deformation. This deformation leads to a decrease in the stability of the surrounding rock and increases the risk of deformation and crack development. Therefore, the surrounding rock deformation risk index... And it also increases accordingly; The increase will make The risk index of surrounding rock deformation is reduced, thereby reducing the risk index of surrounding rock deformation. The increase is because an increase in the inclination angle of the surrounding rock support structure indicates factors such as increased external loads, increased internal pressure, and changes in geological conditions. These factors can lead to further deformation or even instability of the surrounding rock. (The formula...) The exponential form of the inclination angle amplifies changes in the risk assessment. Even small changes in inclination can significantly affect the risk index, reflecting the sensitivity of the surrounding rock under stress. This means that increased rock inclination will raise concerns about the overall stability. Enlargement will lead to The increase is due to the fact that when the displacement of the crack at the junction of the surrounding rock increases, it means that the deformation rate of the crack at the junction of the surrounding rock increases, which threatens the structural integrity of the surrounding rock. The increase of cracks is usually related to the fatigue of the surrounding rock material, stress concentration or changes in the external environment, such as water level changes, earthquakes, etc. These situations may lead to further damage to the surrounding rock, thus increasing the deformation risk index of the surrounding rock.

[0086] formula In, molecules are The increment of 1 is used to adjust the surrounding rock risk index when the horizontal and vertical displacements of the surrounding rock at the tunnel location are both zero. It remains a valid value; adding 1 provides a baseline for the risk index. In practical applications, even if the surrounding rock displacement is zero, a certain risk still exists. Therefore, introducing a baseline value can better reflect the natural state of the surrounding rock when no displacement occurs and provides a reference point. The reason for adding 1 is the same as above: during monitoring and assessment, the state of cracks at the junction of the surrounding rock changes over time. By adding 1, the comparison of the risk index between different time points becomes more reasonable and consistent, avoiding situations where the index cannot be compared due to certain states being zero.

[0087] It should be noted that comparing the surrounding rock deformation risk index with the established safety threshold enables real-time monitoring and early warning of the tunnel's surrounding rock condition. When the risk exceeds the safety threshold, an alarm must be issued promptly to ensure the safety of construction and operation personnel and optimize resource allocation. The safety threshold is set based on historical data, engineering experience, risk tolerance, and relevant technical standards to ensure that it effectively reflects the dynamic state of the surrounding rock and is adjusted in a timely manner as the project progresses, thereby achieving scientific decision-making and effective risk management.

[0088] Therefore, it is necessary to compare the generated surrounding rock deformation risk index with the safety threshold to determine whether the surrounding rock deformation risk index exceeds the established safety threshold. The logical formula used is as follows:

[0089]

[0090] in, This represents the logical judgment value for determining whether to trigger the early warning mechanism. hour, This indicates a risk of deformation in the surrounding rock of the tunnel, triggering an alarm message; when hour, This indicates that no risk of deformation of the surrounding rock in the tunnel has been detected, and there is no need to trigger an alarm at this time. The established safety threshold.

[0091] Please see Figure 2 The present invention also provides a method for monitoring tunnel surrounding rock deformation based on visual recognition. The monitoring method employs the aforementioned visual recognition-based tunnel surrounding rock deformation monitoring system, comprising:

[0092] Step 1: Use visual recognition technology to acquire the initial surrounding rock image before tunnel construction, and acquire the current surrounding rock image in real time during construction. The image acquisition module is a high-resolution camera and an image processing unit.

[0093] Step 2: Analyze and compare the initial surrounding rock image with the current surrounding rock image, calculate the horizontal and vertical displacement of the surrounding rock at the tunnel entrance and exit, as well as the change in the tilt angle of the surrounding rock support structure, and calculate the deformation rate of the cracks at the surrounding rock junction by monitoring the displacement of the cracks at the surrounding rock junction.

[0094] Step 3: Generate the surrounding rock deformation risk index by comprehensively considering the calculated horizontal and vertical displacements inside the surrounding rock, the change in the inclination angle of the surrounding rock support structure, and the deformation rate of cracks at the junction of the surrounding rock.

[0095] Step 4: Set a safety threshold. Compare the generated surrounding rock deformation risk index with the safety threshold to determine whether the surrounding rock deformation risk index exceeds the set safety threshold. If it exceeds the safety threshold, trigger the early warning mechanism and send an alarm message.

[0096] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0097] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0098] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0099] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A tunnel surrounding rock deformation monitoring system based on visual recognition, characterized in that, The specific steps include: The image acquisition module is used to acquire the initial surrounding rock image before tunnel construction using visual recognition technology, and to acquire the current surrounding rock image in real time during construction. The image acquisition module is a high-resolution camera and an image processing unit. The surrounding rock deformation parameter calculation module is used to analyze and compare the initial surrounding rock image with the current surrounding rock image, calculate the horizontal and vertical displacement of the surrounding rock at the tunnel entrance and exit, as well as the change in the tilt angle of the surrounding rock support structure, and calculate the deformation rate of the cracks at the surrounding rock junction by monitoring the displacement of the cracks at the surrounding rock junction. The deformation risk index generation module is used to generate a surrounding rock deformation risk index based on the calculated horizontal and vertical displacement inside the surrounding rock, the change in the inclination angle of the surrounding rock support structure, and the deformation rate of the cracks at the junction of the surrounding rock. The safety monitoring and early warning module is used to set a safety threshold, compare the generated surrounding rock deformation risk index with the safety threshold, determine whether the surrounding rock deformation risk index exceeds the set safety threshold, and if it exceeds the safety threshold, trigger the early warning mechanism and send alarm information. The formula used to generate the surrounding rock deformation risk index is as follows: ； in, This indicates the risk index of surrounding rock deformation. , These represent the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit, respectively. This indicates the change in the inclination angle of the surrounding rock support structure. This represents the deformation rate of the crack at the junction of the surrounding rock and the surrounding rock.

2. The tunnel surrounding rock deformation monitoring system based on visual recognition according to claim 1, characterized in that, The method used to acquire and analyze the initial and current surrounding rock images before tunnel construction, and to compare these images, is as follows: Before tunnel construction, a high-resolution camera is used to scan the surrounding rock of the tunnel to obtain clear initial images of the surrounding rock. The images are preprocessed by the image processing unit, including noise reduction, contrast enhancement and brightness adjustment, to improve the accuracy of subsequent identification. Image segmentation technology is used to separate key areas from the background image. The key areas include tunnel entrances and exits, support structure nodes, and junctions with surrounding rock. Feature point detection algorithms are used in these key areas to mark multiple feature points in the key areas of the initial and current surrounding rock images, ensuring that these areas are fully covered. The coordinates of each feature point are recorded, and the feature points in the key areas of the current and initial surrounding rock images are aligned.

3. The tunnel surrounding rock deformation monitoring system based on visual recognition according to claim 2, characterized in that, The horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit, as well as the changes in the inclination angle of the nodes of the surrounding rock support structure, are calculated. The deformation rate of the cracks at the surrounding rock junctions is calculated by monitoring the displacement of the cracks at these junctions. The method used is as follows: Select using feature point matching algorithm The feature points are evenly distributed on the surface and inside of the surrounding rock at the tunnel entrance and exit. For each matched feature point, let the coordinates of the feature point in the initial surrounding rock image be... The coordinates of the feature points in the current surrounding rock image are: The formulas used to calculate the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit are as follows: ； ； in, , These represent the horizontal and vertical displacements of the surrounding rock at the tunnel entrance and exit, respectively. , These represent the current surrounding rock image, specifically the first... The x and y coordinates of each feature point , These represent the first and second images of the initial surrounding rock. The x and y coordinates of each feature point This is the index of feature points in the initial surrounding rock image. This represents the current acquisition time of the surrounding rock image. The current surrounding rock image is the first one compared to the initial surrounding rock image. Feature point indices aligned with feature points, and , This represents the total number of feature points in the surrounding rock image. The starting and ending nodes of the surrounding rock support structure are selected as matching feature points to calculate the change in tilt angle. Let the two feature points of the support structure in the initial surrounding rock image be... , Let the feature points corresponding to the support structure matching in the current surrounding rock image be... , and utilize , As the starting node of the support structure in the initial surrounding rock image and the current surrounding rock image, using , As the terminal node of the support structure in the initial and current surrounding rock images, the formula used to calculate the slope of the support structure in the initial and current surrounding rock images is as follows: ； ； in, , These represent the slopes of the surrounding rock support structure in the initial and current surrounding rock images, respectively. , and These represent the x and y coordinates of two feature points in the support structure of the initial surrounding rock image. , and These are the x and y coordinates of two feature points in the current surrounding rock image support structure; The formula used to calculate the change in inclination angle of the surrounding rock support structure based on the slope is: ； ； ； in, This indicates the change in the inclination angle of the surrounding rock support structure. , These are the tilt angles under the initial surrounding rock image and the current surrounding rock image, respectively; Feature points are set at both ends of the crack at the junction of the surrounding rock and the surrounding rock. , As the location of feature points in the initial surrounding rock image, and , The formula used to calculate the displacement of the crack at the junction of the surrounding rock, based on the location of the feature point in the current surrounding rock image, is as follows: ； ； in, This indicates the displacement of the crack at the junction of the surrounding rock and the surrounding rock. , and , These represent the x and y coordinates of two feature points on the crack at the junction in the initial surrounding rock image. , and , These are the x and y coordinates of two feature points on the crack at the junction in the current surrounding rock image. This represents the deformation rate of the crack at the junction of the surrounding rock and the surrounding rock. This represents the time interval between the acquisition of the current surrounding rock image and the initial surrounding rock image.

4. The tunnel surrounding rock deformation monitoring system based on visual recognition according to claim 1, characterized in that, The generated surrounding rock deformation risk index is compared with a safety threshold to determine whether the surrounding rock deformation risk index exceeds the established safety threshold. The logical formula used is as follows: ； in, This represents the logical judgment value for determining whether to trigger the early warning mechanism. hour, This indicates a risk of deformation in the surrounding rock of the tunnel, triggering an alarm message; when hour, This indicates that no risk of deformation of the surrounding rock in the tunnel has been detected, and there is no need to trigger an alarm at this time. The established safety threshold.

5. A method for monitoring tunnel surrounding rock deformation based on visual recognition, characterized in that, The monitoring method employs a tunnel surrounding rock deformation monitoring system based on visual recognition as described in any one of claims 1-4, comprising: Step 1: Use visual recognition technology to acquire the initial surrounding rock image before tunnel construction, and acquire the current surrounding rock image in real time during construction. The image acquisition module is a high-resolution camera and an image processing unit. Step 2: Analyze and compare the initial surrounding rock image with the current surrounding rock image, calculate the horizontal and vertical displacement of the surrounding rock at the tunnel entrance and exit, as well as the change in the tilt angle of the surrounding rock support structure, and calculate the deformation rate of the cracks at the surrounding rock junction by monitoring the displacement of the cracks at the surrounding rock junction. Step 3: Generate the surrounding rock deformation risk index by comprehensively considering the calculated horizontal and vertical displacements inside the surrounding rock, the change in the inclination angle of the surrounding rock support structure, and the deformation rate of cracks at the junction of the surrounding rock. Step 4: Set a safety threshold. Compare the generated surrounding rock deformation risk index with the safety threshold to determine whether the surrounding rock deformation risk index exceeds the set safety threshold. If it exceeds the safety threshold, trigger the early warning mechanism and send an alarm message.

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