Method and device for monitoring and identifying soil fracture under multi-effect coupling effect

Abstract

The invention relates to the technical field of soil body crack monitoring, in particular to a multi-effect coupling effect soil body crack monitoring identification method and device, and the method comprises the steps: obtaining a preset environment condition, and determining a corresponding preset environment parameter according to the preset environment condition; the temperature, the humidity, the pressure intensity and the air flow speed in the box body are adjusted according to preset environment parameters; under a preset environment condition, continuously collecting image data of the soil body sample through a binocular camera and a horizontal camera so as to monitor whether the soil body sample has cracks or not; the image data are analyzed through an edge detection algorithm and a feature extraction algorithm, crack data of the soil body sample are recognized, and the crack data comprise the crack length, the crack width and the crack area. The environment temperature, humidity, pressure intensity and other environment conditions can be precisely controlled in combination with different weather conditions, precise soil body crack image data are obtained through the binocular camera and the horizontal camera, and the development form of cracks under the multi-coupling effect can be conveniently analyzed.

Description

Technical Field

[0001] The present invention discloses a technology related to soil crack monitoring, and specifically, relates to a method and device for monitoring and identifying soil cracks under the coupling action of multiple effects. Background Art

[0002] The growth and development forms of rock and soil masses are different under different climate conditions. For example, under the influence of the coupling action of different effects such as high temperature, dryness, and hot humidity in extreme climates, different cracks will occur on the inner and outer surfaces of rock and soil, resulting in the loss of soil strength, causing landslides, and causing geological disasters such as house collapses. In the prior art, the soil environment simulation experimental device mainly simulates single conditions such as humidity and temperature on the upper surface of rock and soil, and it is difficult to obtain the law of crack development inside the soil during the experiment.

[0003] The existing soil crack monitoring devices and identification methods have the following disadvantages: only considering single influencing conditions such as humidity, temperature, or others; not realizing the action under the coupling of multiple effects such as hot humidity on rock and soil, and it is difficult to simulate the influence of different climates on rock and soil masses in actual situations; only being able to observe the crack morphology through technologies such as CT scanning or fiber Bragg gratings, and the crack identification equipment among them is expensive and the process is complex.

[0004] Therefore, it is urgent for those skilled in the art to find a new technical solution to solve the above problems. Summary of the Invention

[0005] In order to overcome the problems existing in the related technologies, the present invention discloses a method and device for monitoring and identifying soil cracks under the coupling action of multiple effects.

[0006] According to the first aspect of the embodiments disclosed by the present invention, a method for monitoring and identifying soil cracks under the coupling action of multiple effects is provided. The method includes:

[0007] Obtain preset environmental conditions, and determine corresponding preset environmental parameters according to the preset environmental conditions;

[0008] Adjust the temperature, humidity, pressure, and air flow rate inside the box according to the preset environmental parameters, where the box is used to place the soil sample;

[0009] Under the preset environmental conditions, continuously collect image data of the soil sample through a binocular camera and a horizontal camera to monitor whether cracks appear in the soil sample;

[0010] Analyze the image data through an edge detection algorithm and a feature extraction algorithm to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area.

[0011] Optionally, adjusting the temperature, humidity, pressure, and air velocity inside the box according to the preset environmental parameters includes:

[0012] Determining the target temperature, target humidity, target pressure, and target air velocity corresponding to the preset environmental parameters;

[0013] Collecting the current temperature inside the box through a temperature sensor. If the current temperature is lower than the target temperature, raising the temperature inside the box through a heating element. If the current temperature is higher than the target temperature, lowering the temperature inside the box through a cooling element;

[0014] Collecting the current humidity inside the box through a humidity sensor. If the current humidity is lower than the target humidity, increasing the humidity inside the box through a humidity controller. If the current humidity is higher than the target humidity, decreasing the humidity inside the box through a humidity controller;

[0015] Determining the current pressure inside the box based on the data collected by a pressure sensor. If the current pressure is lower than the target pressure, increasing the pressure inside the box through a compressed air source. If the current pressure is higher than the target pressure, lowering the pressure inside the box through a vacuum pump;

[0016] Adjusting the current air velocity inside the box to the target air velocity through a fan.

[0017] Optionally, continuously collecting the image data of the soil sample through a binocular camera and a horizontal camera includes:

[0018] Calculating the disparity based on the left image and the right image collected by the binocular camera , where is the disparity, is the pixel coordinate in the left image, is the pixel coordinate in the right image;

[0019] Determining the depth value based on the disparity ;

[0020] Obtaining the three-dimensional image data of the soil sample based on the depth value .

[0021] Optionally, analyzing the image data through an edge detection algorithm and a feature extraction algorithm to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area, includes:

[0022] Segmenting the image data into a crack region and a background region through a preset gray threshold;

[0023] Determine the crack edges of the crack area through an edge detection algorithm;

[0024] Extract the crack length, crack width, and crack area through a feature extraction algorithm based on the crack area and crack edges.

[0025] Optionally, the method further includes:

[0026] Under the preset environmental conditions, obtain the crack data corresponding to different monitoring time nodes;

[0027] Generate a monitoring report including the preset environmental conditions, monitoring time nodes, and crack data.

[0028] Optionally, the method further includes:

[0029] Obtain a preset number of data monitoring reports. Use the preset environmental conditions and monitoring time nodes in the data monitoring reports as inputs, and the corresponding crack data as outputs to train a neural network model to obtain a trained crack generation model;

[0030] The training process of the crack generation model includes:

[0031] According to a preset number of data monitoring reports, obtain a preset number of preset environmental conditions Ph and several monitoring time nodes Th corresponding to each preset environmental condition;

[0032] Extract the special vector Y of the monitoring time node Th corresponding to each preset environmental condition through a ResNet neural network;

[0033] Obtain the predicted value Rp of the crack data corresponding to the special vector Y through a fully connected layer;

[0034] Use the preset environmental conditions and monitoring time nodes in the data monitoring reports as inputs, and the corresponding crack data as outputs, and as the loss function for training to obtain a crack generation model, where is the true value of the crack data, is the number of all monitoring time nodes.

[0035] According to the second aspect of the disclosed embodiments of the present invention, a soil crack monitoring and identification device for multi-effect coupling is provided. The device includes: a box body, a placement table, a binocular camera, a horizontal camera, a standard light source assembly, a sensor assembly, and an environmental condition adjustment assembly;

[0036] The placement table is arranged inside the box body and is used to place the soil sample;

[0037] The binocular cameras are respectively arranged at the upper left and upper right of the placement table, the horizontal camera is arranged at a position flush with the horizontal plane of the placement table, and the binocular cameras and the horizontal camera are located inside the box body;

[0038] The standard light source assembly is arranged above the placement table and is used to provide light for the soil sample on the placement table;

[0039] The sensor assembly is used to monitor the environmental data inside the box body;

[0040] The environmental condition adjustment assembly is used to adjust the environmental data inside the box body.

[0041] Optionally, the sensor assembly includes a temperature sensor, a humidity sensor and a pressure sensor, and the environmental adjustment assembly includes: a heating element, a cooling element, a humidity controller, a compressed air source, a vacuum pump and a fan;

[0042] The temperature sensor is used to collect the temperature inside the box body, the heating element is used to increase the temperature inside the box body, and the cooling element is used to decrease the temperature inside the box body;

[0043] The humidity sensor is used to collect the humidity inside the box body, the humidity controller is used to increase the humidity inside the box body, and the humidity controller is used to decrease the humidity inside the box body;

[0044] The pressure sensor is used to collect the pressure inside the box body, the compressed air source is used to increase the pressure inside the box body, and the vacuum pump is used to decrease the pressure inside the box body;

[0045] The fan is used to adjust the air flow rate inside the box body.

[0046] Optionally, the device further includes: a balance;

[0047] The balance is arranged inside the box body, below the placement table, and is an integral structure with the placement table, and the balance is used to obtain the weight of the soil sample.

[0048] Optionally, the device further includes: a processor, and the processor is electrically connected to the binocular cameras, the horizontal camera, the standard light source assembly, the sensor assembly and the environmental condition adjustment assembly respectively;

[0049] The processor is used for:

[0050] Obtain preset environmental conditions, and determine corresponding preset environmental parameters according to the preset environmental conditions;

[0051] Control the environmental condition adjustment assembly to adjust the temperature, humidity, pressure and air flow rate inside the box body according to the preset environmental parameters;

[0052] Under the preset environmental conditions, control the binocular camera and the horizontal camera to continuously collect the image data of the soil sample.

[0053] Analyze the image data through an edge detection algorithm and a feature extraction algorithm to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area.

[0054] In summary, the present invention relates to the technical field of soil crack monitoring, specifically to a method and device for monitoring and identifying soil cracks under the coupling action of multiple effects. The method includes: obtaining preset environmental conditions, determining corresponding preset environmental parameters according to the preset environmental conditions; adjusting the temperature, humidity, pressure, and air flow rate in the box according to the preset environmental parameters; under the preset environmental conditions, continuously collect the image data of the soil sample through a binocular camera and a horizontal camera to monitor whether cracks appear in the soil sample; analyze the image data through an edge detection algorithm and a feature extraction algorithm to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area. It can accurately control environmental conditions such as temperature, humidity, and pressure in combination with different climate conditions, and obtain accurate soil crack image data through a binocular camera and a horizontal camera, which is convenient for analyzing the development form of cracks under the coupling action of multiple factors.

[0055] Weigh the mass in real time through a balance during the evolution process of soil cracks to calculate the water evaporation amount in the soil sample. By establishing a monitoring report including preset environmental conditions, monitoring time nodes, and crack data, it provides new ideas and technical references for evaluating the crack development state in engineering soil. In addition, using the data monitoring report as sample data to train a neural network model to obtain a trained crack generation model, which can predict the development form of soil cracks under specific environmental conditions.

[0056] Other features and advantages of the present invention will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. They are used together with the following specific implementation to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings:

[0058] Figure 1 is a flowchart showing a method for monitoring and identifying soil cracks under the coupling action of multiple effects according to an exemplary embodiment;

[0059] Figure 2 is according to Figure 1 shows a flowchart of a method for adjusting environmental parameters;

[0060] Figure 3 is based on Figure 1 the flowchart of a monitoring report generation method shown

[0061] Figure 4 is the structural block diagram of a soil mass crack monitoring and identification device with multi-effect coupling action shown according to an exemplary embodiment. Detailed implementation manners

[0062] The following will describe in detail the specific implementation manners disclosed in the present invention with reference to the accompanying drawings. It should be understood that the specific implementation manners described herein are only for the purpose of illustration and explanation of the present disclosure, and are not used to limit the present disclosure.

[0063] Figure 1 is the schematic flowchart of a soil mass crack monitoring and identification method with multi-effect coupling action shown according to an exemplary embodiment, as Figure 1 shown, and this method includes:

[0064] In step 101, obtain the preset environmental conditions, and determine the corresponding preset environmental parameters according to the preset environmental conditions.

[0065] Exemplarily, different climate conditions have different degrees of influence on the generation of cracks in the soil mass. In the disclosed embodiments of the present invention, data such as humidity, temperature, and pressure under different environmental conditions are simulated to explore the crack development morphology and the dynamic development characteristics of cracks under the action of multi-effect coupling.

[0066] In step 102, adjust the temperature, humidity, pressure, and air flow rate in the box according to the preset environmental parameters.

[0067] Among them, the box is used to place the soil sample.

[0068] Exemplarily, place the soil sample in the box, and adjust the temperature, humidity, pressure, and air flow rate in the box to adjust the environmental data in the box to the environmental parameters consistent with the preset environmental parameters, so as to continue to monitor the crack formation situation of the soil sample under the preset environmental conditions.

[0069] Preferably, the preset environmental conditions are the real climate environment of the soil mass. For example, take the climate conditions for the survival of the mountain rock and soil in the northwest region as the preset environmental conditions, and adjust the environmental parameters in the box to the preset environmental parameters corresponding to the preset environmental conditions, so as to simulate the survival environment around the mountain in the northwest region.

[0070] Specifically, Figure 2 is based on Figure 1 the flowchart of an environmental parameter adjustment method shown Figure 2 shown, and this step 102 includes:

[0071] In step 1021, determine the target temperature, target humidity, target pressure, and target air velocity corresponding to the preset environmental parameters.

[0072] It can be understood that an environmental condition adjustment component is provided inside the box to adjust the temperature, humidity, pressure, and air velocity inside the box to the target temperature, target humidity, target pressure, and target air velocity.

[0073] In step 1022, collect the current temperature inside the box through a temperature sensor. If the current temperature is lower than the target temperature, increase the temperature inside the box through a heating element. If the current temperature is higher than the target temperature, decrease the temperature inside the box through a cooling element.

[0074] Exemplarily, the environmental condition adjustment component includes: a heating element and a cooling element. At the same time, a temperature sensor is provided inside the box. The current temperature is collected and detected in real time through the temperature sensor, and the heating element or the cooling element is activated according to the comparison result between the current temperature and the target temperature. The heating element can be a heating pad, a heating wire, or a PTC heater, and the cooling element can be a small refrigerator, a thermoelectric cooler (TEC), or a fan.

[0075] In step 1023, collect the current humidity inside the box through a humidity sensor. If the current humidity is lower than the target humidity, increase the humidity inside the box through a humidity control machine. If the current humidity is higher than the target humidity, decrease the humidity inside the box through a humidity control machine.

[0076] Exemplarily, the environmental condition adjustment component includes: a humidity control machine. At the same time, a humidity sensor is provided inside the box. The current humidity is collected and detected in real time through the humidity sensor, and the humidity control machine is activated according to the comparison result between the current humidity and the target humidity.

[0077] In step 1024, determine the current pressure inside the box according to the data collected by the pressure sensor. If the current pressure is lower than the target pressure, increase the pressure inside the box through a compressed air source. If the current pressure is higher than the target pressure, decrease the pressure inside the box through a vacuum pump.

[0078] Exemplarily, the environmental condition adjustment component includes: a compressed air source and a vacuum pump. At the same time, a pressure sensor is provided inside the box. The current pressure data inside the box is collected through the pressure sensor, and the compressed air source or the vacuum pump is activated according to the comparison result between the current pressure and the target pressure.

[0079] In step 1025, adjust the current air velocity inside the box to the target air velocity through a fan.

[0080] Exemplarily, the environmental condition adjustment component includes: a fan, which adjusts the current air flow rate in the box to the target air flow rate by adjusting the rotation speed of the fan. It can be understood that the corresponding relationship between the rotation speed of the fan and the air flow rate can be preset in advance, so as to determine the fan rotation speed according to the target air flow rate, or the current air flow rate in the box can be monitored in real time through an air flow rate sensor, so as to gradually adjust the rotation speed of the fan according to the comparison result between the current air flow rate and the target air flow rate.

[0081] In step 103, under the preset environmental conditions, the image data of the soil sample is continuously collected through the binocular camera and the horizontal camera to monitor whether cracks appear in the soil sample.

[0082] Exemplarily, the binocular camera is used to obtain stereoscopic vision information. By taking pictures of the same scene from different angles with two cameras, two left and right images are generated. The horizontal camera is used to obtain a planar view of the scene and is usually used to supplement the information of the binocular camera. The three-dimensional model is generated according to the image data collected by the binocular camera and the horizontal camera, so as to obtain the crack data in the soil sample according to the three-dimensional model.

[0083] Specifically, continuously collecting the image data of the soil sample through the binocular camera and the horizontal camera includes:

[0084] Calculating the parallax according to the left image and the right image collected by the binocular camera , where is the parallax, is the pixel coordinate in the left image, is the pixel coordinate in the right image.

[0085] The parallax refers to the difference of the same object in the left image and the right image collected by the binocular camera, is the pixel coordinate in the left image, is the pixel coordinate in the right image. It can be understood that the left image and the right image collected by the binocular camera are first subjected to operations such as grayscale processing, edge detection, and feature extraction to respectively determine the pixel coordinates of the pixel points corresponding to the soil sample and the cracks in the left image and the right image, that is, and , and are both in the form of a pixel point coordinate matrix.

[0086] Determining the depth value according to the parallax 双目 , is the depth value, is the focal length of the binocular camera, is the baseline distance of the binocular camera.​

[0087] The binocular camera calculates depth through parallax, while the horizontal camera can estimate depth through geometric constraints (such as known object dimensions or plane equations). Finally, the depth information of both is fused. The above depth value 双目 is the depth of the binocular camera. And the depth value in the horizontal camera 水平 is determined by the actual height value M of the soil sample and the pixel height m of the soil sample in the plane image collected by the horizontal camera:

[0088] 水平 , is the focal length of the horizontal camera.

[0089] Fuse the depth information of the binocular camera and the horizontal camera with weights:

[0090] 水平 =ω 双目 + (1 - ω) 水平 , where ω is the weight coefficient, and the weight coefficient is usually determined according to the confidence level.

[0091] Obtain the three-dimensional image data of the soil sample according to the depth value.

[0092] The above 双目 and 水平 are the depth maps of the binocular camera and the horizontal camera respectively. Through the depth map and the camera internal parameters, convert the two-dimensional image points into three-dimensional point clouds.

[0093] Among them, the binocular camera point cloud is:

[0094] 双目 , where is the pixel coordinate in the image collected by the binocular camera, is the internal parameter of the binocular camera.

[0095] The horizontal camera point cloud is:

[0096] 水平 , where is the pixel coordinate in the image collected by the horizontal camera, is the internal parameter of the horizontal camera.

[0097] After merging the point clouds of the horizontal camera and the binocular camera (simply taking the union of the two point cloud matrices), a three-dimensional model of the soil sample is generated through a point cloud reconstruction algorithm. Specifically, the point cloud reconstruction algorithm includes: Poisson reconstruction algorithm or Delaunay triangulation algorithm, etc.

[0098] In step 104, the image data is analyzed through an edge detection algorithm and a feature extraction algorithm to identify the fracture data of the soil sample.

[0099] The fracture data includes fracture length, fracture width, and fracture area.

[0100] Exemplarily, it can be understood that before performing the edge detection algorithm and the feature extraction algorithm, operations such as grayscale conversion, denoising, and contrast enhancement can also be performed on the image data to remove the noise in the image data and improve the subsequent processing effect.

[0101] Specifically, the image data is analyzed through an edge detection algorithm and a feature extraction algorithm to identify the fracture data of the soil sample. The fracture data includes fracture length, fracture width, and fracture area, including:

[0102] The image data is segmented into a fracture region and a background region through a preset grayscale threshold; the fracture edge of the fracture region is determined through an edge detection algorithm; according to the fracture region and the fracture edge, the fracture length, fracture width, and fracture area are extracted through a feature extraction algorithm.

[0103] Exemplarily, after determining the fracture edge, the perimeter of the fracture is determined according to the total number of pixel points in the fracture edge, the area of the fracture is determined according to the total number of pixel points contained in the region surrounded by the fracture edge, and then the fracture length and fracture width are determined according to the fracture area and the fracture perimeter.

[0104] Figure 3 is based on Figure 1 shows a flowchart of a monitoring report generation method, as Figure 3 shown, the method includes:

[0105] In step 301, under preset environmental conditions, the fracture data corresponding to different monitoring time nodes is obtained.

[0106] Exemplarily, the fractures in the soil are gradually formed within a certain time period. This time period is divided into several different small time periods, and each small time period corresponds to a monitoring time node, so as to analyze the fracture development morphology and the dynamic development characteristics of the fractures under the action of multi-effect coupling according to the different fracture morphologies formed at each monitoring time node.

[0107] In step 302, a monitoring report including preset environmental conditions, monitoring time nodes, and fracture data is generated.

[0108] Exemplarily, a fracture data monitoring report is generated. The monitoring report records the fracture data corresponding to each monitoring time node under different preset environmental conditions, which can provide new ideas and technical references for evaluating the fracture development state in engineering soil masses.

[0109] Optionally, the method further includes:

[0110] Obtain a preset number of data monitoring reports. Using the preset environmental conditions and monitoring time nodes in the data monitoring reports as inputs and the corresponding fracture data as outputs, train a neural network model to obtain a trained fracture generation model.

[0111] Exemplarily, use a large number of data monitoring reports as sample data to train a neural network model to obtain a trained fracture generation model. According to the fracture generation model, the development form of soil fractures under specific environmental conditions can be predicted. For example, if the staff needs to obtain the fracture formation situation of the soil in a certain mountainous area in the south, they can first obtain the environmental conditions of the area and the fracture development time point that the staff wants to know, and use this time point as the monitoring time node. According to the environmental conditions, the monitoring time node, and the trained fracture generation model, the fracture data at the fracture development time point that the staff wants to know can be obtained.

[0112] Specifically, the training process of the fracture generation model includes:

[0113] According to a preset number of data monitoring reports, obtain a preset number of preset environmental conditions Ph and several monitoring time nodes Th corresponding to each preset environmental condition; extract the special vector Y of the monitoring time node Th corresponding to each preset environmental condition through the ResNet neural network; obtain the predicted value Rp of the fracture data corresponding to the special vector Y through the fully connected layer; use the preset environmental conditions and monitoring time nodes in the data monitoring report as inputs and the corresponding fracture data as outputs, and use as the loss function for training to obtain the fracture generation model, where is the true value of the fracture data, is the number of all monitoring time nodes.

[0114] Figure 4 is a structural block diagram of a soil fracture monitoring and identification device with multi-effect coupling according to an exemplary embodiment, as Figure 4As shown in the figure, the device includes: a box body 410, a placement table 420, a binocular camera 430, a horizontal camera 440, a standard light source assembly 450, a sensor assembly (not shown in the figure), and an environmental condition adjustment assembly (not shown in the figure); the placement table 420 is arranged inside the box body 410 and is used for placing soil samples; the binocular cameras 430 are respectively arranged at the upper left and upper right of the placement table 420, the horizontal camera 440 is arranged at the level flush with the placement table 420, and the binocular cameras 430 and the horizontal camera 440 are located inside the box body 410; the standard light source assembly 450 is arranged above the placement table 420 and is used to provide light for the soil samples on the placement table 420; the sensor assembly is used to monitor the environmental data inside the box body 410; the environmental condition adjustment assembly is used to adjust the environmental data inside the box body 410.

[0115] Exemplarily, pulleys are arranged below the box body 410, which can move the box body. At the same time, the lid on the box body is a detachable structure. When it is necessary to place soil samples on the placement table 420, the lid on the box body can be removed at any time.

[0116] Optionally, the sensor assembly includes a temperature sensor 460, a humidity sensor 470, and a pressure sensor 480, and the environmental adjustment assembly includes: a heating element, a cooling element, a humidity controller, a compressed air source, a vacuum pump, and a fan; the temperature sensor is used to collect the temperature inside the box, the heating element is used to increase the temperature inside the box, and the cooling element is used to decrease the temperature inside the box; the humidity sensor is used to collect the humidity inside the box, and the humidity controller has both humidifying and dehumidifying functions and is used to increase or decrease the humidity inside the box; the pressure sensor is used to collect the pressure inside the box, the compressed air source is used to increase the pressure inside the box, and the vacuum pump is used to decrease the pressure inside the box; the fan is used to adjust the air flow rate inside the box.

[0117] Optionally, the device further includes: a balance; the balance is arranged inside the box body 410, below the placement table 420, and is an integral structure with the placement table 420. The balance is used to obtain the weight of the soil sample. The balance and the placement table 420 are an integral structure, which can monitor the weight change of the soil sample at any time, and can weigh the mass in real time during the evolution of soil fissures to calculate the water evaporation amount in the soil sample.

[0118] Optionally, the device further includes: a processor, and the processor is electrically connected to the binocular camera, the horizontal camera, the standard light source assembly, the sensor assembly, and the environmental condition adjustment assembly respectively;

[0119] The processor is used for:

[0120] Obtain preset environmental conditions and determine corresponding preset environmental parameters according to the preset environmental conditions;

[0121] Control the environmental condition adjustment component to adjust the temperature, humidity, pressure, and air velocity in the box according to the preset environmental parameters;

[0122] Under the preset environmental conditions, control the binocular camera and the horizontal camera to continuously collect image data of the soil sample;

[0123] Analyze the image data through edge detection algorithms and feature extraction algorithms to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area.

[0124] It can be understood that the soil crack monitoring and identification device is connected to an external computer device 500 through a data transmission line, and can transmit the data monitored by the binocular camera, horizontal camera, sensor component, etc. to the external computer for processing. It can also be understood that the external computer device 500 can act as a processor to perform data analysis and processing work.

[0125] In summary, the present disclosure relates to the technical field of soil crack monitoring, specifically a method and device for monitoring and identifying soil cracks under the coupling action of multiple effects. The method includes: obtaining preset environmental conditions, determining corresponding preset environmental parameters according to the preset environmental conditions; adjusting the temperature, humidity, pressure, and air velocity in the box according to the preset environmental parameters; under the preset environmental conditions, continuously collect image data of the soil sample through the binocular camera and the horizontal camera to monitor whether cracks appear in the soil sample; analyze the image data through edge detection algorithms and feature extraction algorithms to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area. It can accurately control environmental conditions such as temperature, humidity, and pressure in combination with different climate conditions, and obtain accurate soil crack image data through the binocular camera and the horizontal camera, which is convenient for analyzing the development form of cracks under multiple coupling actions.

[0126] Weigh the mass in real time during the evolution of soil cracks through a balance to calculate the water evaporation amount in the soil sample. By establishing a monitoring report including preset environmental conditions, monitoring time nodes, and crack data, it provides new ideas and technical references for evaluating the crack development state in engineering soil. Moreover, using the data monitoring report as sample data to train a neural network model to obtain a trained crack generation model, which can predict the development form of soil cracks under specific environmental conditions.

[0127] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0128] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable way without conflict. To avoid unnecessary repetition, the present disclosure will not separately describe various possible combinations.

[0129] Furthermore, any combinations can be made among the various different embodiments of the present disclosure, as long as they do not violate the idea of the present disclosure, and they should also be regarded as the content disclosed by the present disclosure.

Claims

1. A method for monitoring and identifying soil cracks with multi-effect coupling action, characterized in that The method includes: Obtain preset environmental conditions, and determine corresponding preset environmental parameters according to the preset environmental conditions; Adjust the temperature, humidity, pressure, and air flow rate inside the box according to the preset environmental parameters, where the box is used to place the soil sample; Under the preset environmental conditions, continuously collect image data of the soil sample through a binocular camera and a horizontal camera to monitor whether cracks appear in the soil sample; Analyze the image data through an edge detection algorithm and a feature extraction algorithm to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area.

2. The method for monitoring and identifying soil cracks with multi-effect coupling action according to claim 1, wherein The adjusting the temperature, humidity, pressure, and air flow rate inside the box according to the preset environmental parameters includes: Determine the target temperature, target humidity, target pressure, and target air flow rate corresponding to the preset environmental parameters; Collect the current temperature inside the box through a temperature sensor. If the current temperature is lower than the target temperature, increase the temperature inside the box through a heating element. If the current temperature is higher than the target temperature, lower the temperature inside the box through a cooling element; Collect the current humidity inside the box through a humidity sensor. If the current humidity is lower than the target humidity, increase the humidity inside the box through a humidity controller. If the current humidity is higher than the target humidity, lower the humidity inside the box through a humidity controller; Determine the current pressure inside the box according to the data collected by a pressure sensor. If the current pressure is lower than the target pressure, increase the pressure inside the box through a compressed air source. If the current pressure is higher than the target pressure, lower the pressure inside the box through a vacuum pump; Adjust the current air flow rate inside the box to the target air flow rate through a fan.

3. The method for monitoring and identifying soil fissures with multi-effect coupling action according to claim 1, characterized in that, The continuously collecting image data of the soil sample through a binocular camera and a horizontal camera includes: Calculate the disparity based on the left image and the right image collected by the binocular camera , where is the disparity, is the pixel coordinate in the left image, is the pixel coordinate in the right image; Based on the parallax Determine the depth value; According to the depth value Obtain the three-dimensional image data of the soil sample.

4. The soil crack monitoring and identification method with multi-effect coupling action according to claim 1, characterized in that The analyzing the image data through an edge detection algorithm and a feature extraction algorithm to identify the crack data of the soil sample, where the crack data includes crack length, crack width, and crack area, includes: Segment the image data into a crack region and a background region through a preset gray threshold; Determine the crack edge of the crack region through an edge detection algorithm; Extract the crack length, crack width, and crack area through a feature extraction algorithm according to the crack region and the crack edge.

5. The method for monitoring and identifying soil fissures with multi-effect coupling action according to claim 1, characterized in that, The method further includes: Under the preset environmental conditions, obtain the crack data corresponding to different monitoring time nodes; Generate a monitoring report including the preset environmental conditions, monitoring time nodes, and crack data.

6. The method for monitoring and identifying soil fissures with multi-effect coupling action according to claim 5, characterized in that, The method further includes: Obtain a preset number of data monitoring reports, use the preset environmental conditions and monitoring time nodes in the data monitoring reports as inputs, and the corresponding crack data as outputs to train a neural network model to obtain a trained crack generation model; The training process of the crack generation model includes: According to a preset number of data monitoring reports, obtain a preset number of preset environmental conditions Ph and several monitoring time nodes Th corresponding to each preset environmental condition; Extract the special vector Y corresponding to the monitoring time node Th for each preset environmental condition through the ResNet neural network; Obtain the predicted value Rp of the fracture data corresponding to the special vector Y through the fully connected layer; Taking the preset environmental conditions and monitoring time nodes in the data monitoring report as inputs, and the corresponding fissure data as outputs, and as the loss function for training to obtain a fissure generation model, where is the true value of the fissure data, is the number of all monitoring time nodes.

7. An apparatus for monitoring and identifying soil fissures with multi-effect coupling action, characterized in that, The device includes: a box body, a placement table, a binocular camera, a horizontal camera, a standard light source assembly, a sensor assembly, and an environmental condition adjustment assembly; The placement table is arranged inside the box body and is used for placing soil samples; The binocular cameras are respectively arranged at the upper left and upper right of the placement table, and the horizontal camera is arranged at the level flush with the placement table. The binocular cameras and the horizontal camera are located inside the box body; The standard light source assembly is arranged above the placement table and is used to provide light for the soil samples on the placement table; The sensor assembly is used to monitor the environmental data inside the box body; The environmental condition adjustment assembly is used to adjust the environmental data inside the box body.

8. The soil crack monitoring and identification device with multi-effect coupling action according to claim 7, characterized in that, The sensor assembly includes a temperature sensor, a humidity sensor, and a pressure sensor. The environmental adjustment assembly includes: a heating element, a cooling element, a humidity controller, a compressed air source, a vacuum pump, and a fan; The temperature sensor is used to collect the temperature inside the box body. The heating element is used to increase the temperature inside the box body. The cooling element is used to decrease the temperature inside the box body; The humidity sensor is used to collect the humidity inside the box body. The humidity controller is used to increase the humidity inside the box body. The humidity controller is used to decrease the humidity inside the box body; The pressure sensor is used to collect the pressure inside the box body. The compressed air source is used to increase the pressure inside the box body. The vacuum pump is used to decrease the pressure inside the box body; The fan is used to adjust the air flow rate inside the box body.

9. The soil fissure monitoring and identification device with multi-effect coupling action according to claim 7, characterized in that The device further includes: a balance; The balance is arranged inside the box body, below the placement table, and is an integral structure with the placement table. The balance is used to obtain the weight of the soil sample.

10. The soil crack monitoring and identification device with multi-effect coupling action according to claim 7, characterized in that, The device further includes: a processor, and the processor is electrically connected to the binocular camera, the horizontal camera, the standard light source assembly, the sensor assembly, and the environmental condition adjustment assembly respectively; The processor is used for: Obtain the preset environmental conditions, and determine the corresponding preset environmental parameters according to the preset environmental conditions; Control the environmental condition adjustment assembly to adjust the temperature, humidity, pressure, and air flow rate inside the box body according to the preset environmental parameters; Under the preset environmental conditions, control the binocular camera and the horizontal camera to continuously collect the image data of the soil sample; Analyze the image data through an edge detection algorithm and a feature extraction algorithm to identify the fracture data of the soil sample. The fracture data includes fracture length, fracture width, and fracture area.

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