Manual freezing construction ice lens thickness in-situ continuous monitoring method and system

Abstract

The invention discloses an artificial freezing construction ice lens thickness in-situ continuous monitoring method and system, and belongs to the technical field of artificial freezing construction, and the method comprises the steps: determining a freezing range in a freezing construction region, setting a plurality of to-be-detected routes in the freezing range, measuring the temperature on each to-be-detected route, recording the temperature change data along with the time, and calculating the thickness of the to-be-detected ice lens. Calculating the moving speed of the freezing frontal surface at 0 DEG C along the to-be-detected line according to the to-be-detected line, and substituting the moving speed of the freezing frontal surface into an empirical model formula to calculate the predicted thickness of the ice lens at each position on the to-be-detected line; through continuous and in-situ monitoring of the temperature on the to-be-detected route, the thickness of the ice lens in the freezing construction area can be predicted in real time, and then reference is provided for adjustment of the freezing temperature, the freezing mode and the like in the manual freezing construction process.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial freezing construction, and particularly relates to a method and system for in-situ continuous monitoring of the thickness of ice lenses in artificial freezing construction. Background Art

[0002] In the actual process of artificial freezing construction of tunnels, by precisely controlling the freezing rate on the freezing side, various freezing modes can be formed, and these modes have a significant impact on the formation process of open-type frost heave ice lenses, thereby effectively reducing the occurrence of frost heave and thaw settlement phenomena. Therefore, real-time monitoring of the evolution process of ice lenses in engineering is crucial for controlling frost heave and thaw settlement caused by artificial freezing and improving the artificial freezing construction technology of tunnels.

[0003] However, in traditional artificial freezing research, the observation of ice lenses mainly relies on microscopic observation methods such as scanning electron microscopy, computed tomography, and nuclear magnetic resonance. Although these methods have played an important role in providing high-precision observation results and revealing the formation mechanism of ice lenses, there are significant limitations in monitoring the distribution and evolution process of ice lenses in actual engineering applications. Frost heave and thaw settlement are processes gradually accumulated by the structural evolution of ice lenses. Realizing in-situ continuous observation of ice lenses throughout the process in artificial freezing construction is crucial for tunnel deformation control. However, the above traditional observation methods are all carried out by sampling on-site and then observing in the laboratory, which has hysteresis and cannot provide in-situ real-time monitoring, making it difficult to guide the construction process of artificial freezing. Summary of the Invention

[0004] The present invention aims to at least solve one of the technical problems existing in the prior art. For this purpose, the present invention proposes a method for in-situ continuous monitoring of the thickness of ice lenses in artificial freezing construction, which can achieve in-situ and real-time monitoring in the freezing construction area, predict the thickness of ice lenses, and thereby guide the construction process of artificial freezing.

[0005] The method for in-situ continuous monitoring of the thickness of ice lenses in artificial freezing construction according to the first aspect embodiment of the present invention includes: Determine the freezing range of the freezing construction area; Set a plurality of detection routes within the freezing range, and obtain the data of the temperature change with time on each detection route; Calculate the measured moving rate of the 0°C freezing front of the detection route according to the temperature change data with time; Calculate the predicted thickness of the ice lens at any position on the detection route according to the measured moving rate of the 0°C freezing front and the empirical model formula.

[0006] The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to the embodiments of the present invention has at least the following beneficial effects: After determining the freezing range in the freezing construction area, a plurality of detection routes are set within the freezing range. The temperature is measured on each detection route, and the data of the temperature change over time is recorded. The moving rate of the freezing front at 0 °C can be calculated from the detection routes, that is, the measured moving rate of the freezing front at 0 °C at any position on the detection route is calculated. Finally, the predicted thickness of the ice lens at the corresponding position is calculated according to the measured moving rate of the freezing front at 0 °C at this position and the empirical model formula; in-situ and real-time monitoring can be realized in the freezing construction area, the thickness of the ice lens can be predicted, and then the process of artificial freezing construction can be guided.

[0007] According to some embodiments of the present invention, the empirical model formula is as follows: W1 = W0 + b÷V1 a ; Wherein, W1 is the predicted thickness of the ice lens, W0 is the initial crack thickness of the in-situ soil body, a is the first parameter, b is the second parameter, and V1 is the measured moving rate of the freezing front at 0 °C; The first parameter a and the second parameter b are obtained by conducting an open freezing laboratory experiment on the soil samples within the freezing range.

[0008] According to some embodiments of the present invention, the step of obtaining the first parameter a and the second parameter b by conducting an open freezing laboratory experiment on the soil samples within the freezing range includes: Using a thin-wall soil sampler to obtain unfrozen soil samples within the freezing range; A plurality of laboratory experiment monitoring points are set on the soil sample, and the plurality of experiment monitoring points are evenly distributed along the column side surface of the cylindrical soil sample, and the distance between every two adjacent experiment monitoring points is a preset distance; The sample is subjected to open freezing. During freezing, the sample is placed vertically, the top plane of the cylindrical sample is the freezing surface, and the bottom plane is the water replenishing surface; during the freezing process, the freezing front at 0 °C moves from the top plane to the bottom plane; During the freezing experiment, the experimental temperatures of all the experiment monitoring points are obtained, and the time when the temperature of each monitoring point reaches 0 °C is recorded; According to the distance L between two adjacent experiment monitoring points and the time difference t when the temperatures of two adjacent experiment monitoring points reach 0 °C, the average velocity V of the freezing front at 0 °C between two adjacent monitoring points is calculated according to the formula V = L / t; The moving rate of the freezing front at 0 °C at each position in the vertical direction of the sample is obtained; Using a micro camera to obtain an image of the soil sample, and obtaining the laboratory experiment ice lens thickness at each position in the vertical direction of the sample according to the image; Substitute the laboratory experiment 0°C freezing front migration rate and the laboratory experiment ice lens thickness at each position into the empirical model formula, and the first parameter a and the second parameter b can be obtained by regression analysis.

[0009] According to some embodiments of the present invention, the monitoring method further includes: Draw a scatter plot based on the laboratory experiment 0°C freezing front migration rate and the laboratory experiment ice lens thickness, and obtain the relationship curve between the laboratory experiment 0°C freezing front migration rate and the laboratory experiment ice lens thickness according to the scatter plot; Obtain the initial crack thickness of the soil sample, and construct an empirical model formula based on the relationship curve and the initial crack thickness.

[0010] According to some embodiments of the present invention, the transferring the soil sample within the freezing range to an open freezing laboratory to conduct laboratory experiments to obtain the first parameter a and the second parameter b further includes: Prepare laboratory ice lens in-situ observation equipment. The observation equipment includes a specimen chamber and a monitoring computer. The specimen chamber is made of high-density polystyrene. A first semiconductor refrigeration chip is installed at the upper end of the specimen chamber. The first semiconductor refrigeration chip is used to adjust the temperature gradient between the upper and lower ends of the specimen chamber and the cooling rate at the upper end according to experimental requirements; m temperature sensors are evenly distributed on the inner wall of the specimen chamber. The distance between every two adjacent temperature sensors is k. The temperature sensors are electrically connected to the monitoring computer, and the monitoring computer monitors the temperature change of the soil sample in the specimen chamber in real time.

[0011] According to some embodiments of the present invention, the obtaining the image of the soil sample includes: The observation equipment further includes an electron microscope, a photographing chamber, a rotary lifting table and a dehumidifier. The side wall of the photographing chamber is provided with a transparent material. A second semiconductor refrigeration chip is installed at the upper end of the photographing chamber. The second semiconductor refrigeration chip is used to adjust the temperature between the upper and lower ends of the photographing chamber and the cooling rate according to experimental requirements, so that the temperature environment of the photographing chamber is the same as that of the specimen chamber. The lower end of the photographing chamber is connected to the dehumidifier. The lower end of the photographing chamber is connected to the rotary lifting table. The rotary lifting table adjusts the rotation angle and height of the photographing chamber to change the photographing surface of the soil sample. The lens of the electron microscope faces the photographing chamber; The rotary lifting table zeros the height of the photographing chamber, evenly sprays an anti-fog agent on the inner and outer walls of the photographing chamber, turns on the dehumidifier. When the humidity in the photographing chamber is lower than 30%, turn on the second semiconductor refrigeration chip. When the temperature of the photographing chamber is equal to the temperature of the specimen chamber, turn off the dehumidifier.

[0012] According to some embodiments of the present invention, the data of the temperature change over time on each of the to-be-detected routes is obtained by a chain-type temperature sensor. The chain-type temperature sensor includes a plurality of polyethylene rods and a plurality of temperature-sensitive elements. The plurality of temperature-sensitive elements are respectively installed on the plurality of polyethylene rods. The distance between every two adjacent temperature-sensitive elements is A, the length of the chain-type temperature sensor is h, and the number n of the temperature-sensitive elements satisfies A×n = h.

[0013] According to some embodiments of the present invention, the setting of a plurality of to-be-detected routes within the freezing range includes: Setting a plurality of the to-be-detected routes to be distributed in a circumferential array centered on the freezing center in the freezing construction area; Controlling each of the to-be-detected routes not to exceed the freezing range; Placing the chain-type temperature sensor on the to-be-detected route.

[0014] According to some embodiments of the present invention, the placing of the chain-type temperature sensor on the to-be-detected route includes: Drilling installation holes in each of the to-be-detected routes. The installation holes do not exceed the freezing range, and the diameter of the installation holes is not less than the outer diameter of the chain-type sensor; Cleaning the installation holes, placing the chain-type temperature sensor into the installation holes, and making the temperature-sensitive elements closely adhere to the hole walls of the installation holes; Checking the working state of the chain-type temperature sensor and calibrating the temperature of the chain-type temperature sensor.

[0015] An in-situ continuous monitoring system for the thickness of ice lenses in artificial freezing construction according to an embodiment of the second aspect of the present invention includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the method for in-situ continuous monitoring of the thickness of ice lenses in artificial freezing construction described in the above embodiments.

[0016] The in-situ continuous monitoring system for the thickness of ice lenses in artificial freezing construction according to an embodiment of the present invention has at least the following beneficial effects: After determining the freezing center in the freezing construction area, the freezing range is calculated through the freezing center. Then, a plurality of to-be-detected routes are set within the freezing range, and the temperature is measured on each to-be-detected route, and the data of the temperature change over time is recorded. The moving rate of the 0°C freezing front can be calculated from the to-be-detected route, that is, the measured moving rate of the 0°C freezing front at any position on the to-be-detected route is calculated. Finally, the predicted thickness of the ice lens at the corresponding position is calculated according to the measured moving rate of the 0°C freezing front at this position and the empirical model formula; in-situ and real-time monitoring can be realized in the freezing construction area, the thickness of the ice lens can be predicted, and further the process of artificial freezing construction can be guided. Description of the Drawings

[0017] Figure 1 is a flowchart of the in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to an embodiment of the present invention; Figure 2 is a schematic structural diagram of a chain-type temperature sensor according to an embodiment of the present invention; Figure 3 is a schematic distribution diagram of the chain-type temperature sensor within the freezing range according to an embodiment of the present invention; Figure 4 is a schematic structural diagram of an observation device according to an embodiment of the present invention; Figure 5 is a schematic structural diagram of a photography room according to an embodiment of the present invention.

[0018] Description of the drawings: Freezing construction area 10, observation device 20, chain-type temperature sensor 100, temperature-sensitive element 110, photography room 300, second semiconductor refrigeration sheet 310, monitoring computer 400, refrigeration equipment 500, electron microscope 600, rotary lifting platform 700, dehumidifier 800. Detailed implementation manners

[0019] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention, and should not be construed as a limitation to the present invention.

[0020] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as front, back, up, down, axial, circumferential, etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention.

[0021] In the description of the present invention, the meaning of "a plurality" is more than two. Understandings such as greater than, less than, exceeding, etc. do not include the present number, and understandings such as above, below, within, etc. include the present number. If there is a description of first and second, it is only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0022] In the description of the present invention, it should be noted that terms such as setting, installation, connection, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0023] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are some, but not all, of the embodiments of the present invention.

[0024] Specifically, in the actual artificial freezing construction process of tunnels, by precisely controlling the freezing rate on the freezing side, various freezing modes can be formed. These modes have a significant impact on the formation process of open-freezing ice lenses, and thus can effectively reduce the occurrence of frost heave and thaw settlement phenomena. Therefore, real-time monitoring of the ice lens evolution process in engineering is crucial for controlling frost heave and thaw settlement caused by artificial freezing and improving the artificial freezing construction technology of tunnels.

[0025] However, in traditional artificial freezing research, the observation of ice lenses mainly relies on microscopic observation methods such as scanning electron microscopy (SEM), computed tomography (CT), and nuclear magnetic resonance (NMR). Although these methods have played an important role in providing high-precision observation results and revealing the formation mechanism of ice lenses, there are significant limitations when monitoring the distribution and evolution process of ice lenses in actual engineering applications. Specifically, the traditional ice lens observation methods are all based on laboratory soil samples and require the entire test process to maintain a constant and non-fluctuating low-temperature environment. However, when applying these methods to monitor ice lenses in actual tunnel surrounding rocks, core sampling is required, and test observations are carried out after sampling. During this process, since ice lenses are extremely sensitive to temperature, the temperature fluctuations during the sampling and transportation links have a great impact on the test observation results, thus seriously affecting the accuracy of the monitoring results. In addition, frost heave and thaw settlement are the accumulation processes of ice lens structure evolution. Therefore, realizing continuous observation of ice lenses throughout the whole process in artificial freezing construction is crucial for tunnel deformation control. However, the above traditional observation methods are all discontinuous observations of laboratory tests after on-site sampling, and cannot achieve continuous observation.

[0026] An in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction provided by the present invention is mainly based on the empirical model formula of the thickness of experimental ice lenses in the laboratory and the actual moving speed of the actual freezing front during the soil freezing process in actual engineering. The monitoring method includes the following steps.

[0027] The first step is to conduct laboratory experiments to obtain the undetermined parameters of the prediction model.

[0028] Prepare the in-situ observation equipment 20 of a laboratory-made ice lens. The equipment includes a specimen chamber 200, a refrigeration device 500, a monitoring computer 400, an electron microscope 600, and a photography chamber 300. The specimen chamber 200 is made of high-density polystyrene. The first semiconductor refrigeration chips 210 are respectively installed at the upper and lower ends. The first semiconductor refrigeration chips 210 are connected to the external refrigeration device 500 through wires, allowing experimenters to precisely control the temperature and the cooling rate at the upper and lower ends of the specimen chamber 200 according to experimental requirements. m temperature sensors are evenly distributed on the inner wall of the specimen chamber 200. The positions of the temperature sensors correspond to the positions of the experimental monitoring points. The distance between two adjacent sensors is k meters, that is, the preset distance is k meters. The temperature sensors are connected to the monitoring computer 400 through data lines, and the temperature change of the soil sample in the specimen chamber 200 can be monitored in real time and accurately on the computer. The refrigeration device 500 provides a stable cold source for the specimen chamber 200. By precisely controlling the working state of the first semiconductor refrigeration chips 210, the temperature of the specimen chamber 200 can be adjusted quickly and precisely. The monitoring computer 400 is a data monitoring and processing center, connected to the temperature sensors and the electron microscope 600, receiving the real-time data of both, and providing a direct monitoring interface for experimenters. The photography chamber 300 is in the shape of a cuboid. The front and side surfaces of the outer shell are made of transparent acrylic materials, and the back surface is made of white acrylic materials. Both the upper and lower surfaces are squares. The second semiconductor refrigeration chip 310 is installed at the upper end. The second semiconductor refrigeration chip 310 is connected to the refrigeration device 500 through wires, allowing experimenters to precisely control the temperature and the cooling rate at the upper and lower ends of the specimen chamber 200 according to experimental requirements, and is used to reduce the error generated by the temperature influence during the photography of the soil sample. A dehumidification port is arranged at the lower end of the photography chamber 300. The dehumidification port is connected to a dehumidifier 800 through a silica gel pipe. The lower end of the photography chamber 300 is connected to a rotary lifting platform 700. The center of the rotary lifting platform 700 coincides with the geometric center of the bottom surface of the photography chamber 300. The rotation angle and height of the rotary lifting platform 700 can be set and adjusted outside the photography chamber 300 through an electronic servo motor to adjust the photography surface of the soil sample. The upper surface of the rotary table is made of high-density polystyrene material to further reduce the interference of temperature on the soil sample. The rotary table is provided with four adjustable rotation angles, which are 0°, 90°, 180°, and 270° respectively. The initial height of the rotary table is 0 mm, and when the rotary table descends, the height value increases. The lens of the electron microscope 600 faces the front surface of the acrylic outer shell of the photography chamber 300, and the height of the lens of the electron microscope 600, the distance from the lens to the acrylic outer shell, and the magnification can be adjusted.

[0029] Collect soil samples from the frozen construction area 10 using a thin-wall soil sampler. Take out the soil samples in the laboratory. After cutting the soil samples, carefully place the soil samples vertically in the sample chamber 200. The contact surface between the soil samples and the observation equipment 20 should be flat and tight. Close the sample chamber 200. Set the target cooling rate and freezing temperature in the refrigeration system, and turn on the freezing equipment; monitor and record the time ti when each sensor in the sample chamber 200 shows 0°C during the freezing process through the monitoring computer 400, and then calculate the average freezing front movement speed V based on the distance between adjacent sensors and the recorded time. When the temperature of the temperature sensor no longer changes and the soil samples are completely frozen, record the data and turn off the refrigeration equipment 500. Among them, V = k ÷ (t i+1 -t i ). Zero the height of the turntable in the photography room 300. Spray anti-fog agent evenly on the inner and outer walls of the photography room 300. Turn on the dehumidifier 800. When the humidity in the photography room 300 drops below 30%, turn on the refrigeration equipment 500, reduce the temperature to the specified temperature, and turn off the dehumidifier 800. Adjust the magnification of the electron microscope 600 to the specified value, adjust the height of the electron microscope 600 and the distance between the lens and the photography room 300. Observe the image in the monitoring computer 400, make the upper surface of the turntable align with the reference horizontal line, and make the central axis of the turntable align with the reference vertical line. Open the sample chamber 200, quickly and carefully transfer the soil samples from the sample chamber 200 to the rotating lifting table 700 in the photography room 300, and finely adjust the distance between the lens of the electron microscope 600 and the photography room 300 until the image seen in the monitoring computer 400 is clear. Take pictures using the photography software on the monitoring computer 400. For each layer, take pictures from four different angles by adjusting the turntable.

[0030] Second step, arrange on-site detection lines and obtain on-site real-time monitoring data.

[0031] Determine the artificial freezing construction area 10, and set the detection route to be detected and the depth of the detection route relative to the freezing center as h meters according to the actual engineering requirements. Refer to Figure 2 As shown, prepare a special chain-type temperature sensor 100 with a length of h meters. The sensor includes evenly distributed polyethylene rods, temperature-sensitive elements 110 and circuit boards. The thickness of the polyethylene rods is slightly wider than that of the temperature-sensitive elements 110, and the distance between the temperature-sensitive elements 110 is A meters. Then the positions of the temperature-sensitive elements 110 correspond to the positions of the real-time monitoring points. Therefore, multiple real-time monitoring points are set on the detection route to be detected, and the distance between every two real-time monitoring points is the preset distance, and the preset distance is A meters. The number n of the temperature-sensitive elements 110 satisfies A × n = h. The circuit board is powered by a battery and sends data to the computer. Refer to Figure 3As shown in the figure, select the route to be detected. Use a drill to drill installation holes along the route to be detected to the maximum depth required for freezing construction. The diameter of the installation hole shall not be less than the outer diameter of the special chain - type sensor. Clean the installation hole and place the special chain - type temperature sensor 100 into the installation hole to ensure that its temperature - sensitive element 110 is in close contact with the hole wall. Check the working status of the special chain - type temperature sensor 100 through a computer and calibrate the temperature of the sensor. Start the artificial freezing construction. Record the time when each temperature - sensitive element 110 on the sensor monitors the preset temperature. The preset temperature in this embodiment is 0°C.

[0032] The empirical model formula for the thickness of the ice lens is W1 = W0 + b÷V1 a , where W1 represents the predicted thickness of an ice lens in a certain section of the frozen area, V1 is the measured moving rate of the 0°C freezing front in this section, W0 is the initial crack thickness of the soil sample. The first parameter a and the second parameter b are related to the soil type and are determined through a single laboratory test. V1 = A÷△t, where △t is the time difference between the second temperature of two selected real - time monitoring points dropping to the preset temperature. When the moving rate of the actual freezing front is zero, W1 tends to infinity. When the position of the actual freezing front tends to be stable, it corresponds to the moving rate of the actual freezing front being equal to zero. Theoretically, under this condition, the thickness of the ice lens will continuously accumulate, resulting in a tendency to infinity. When the moving rate of the actual freezing front approaches infinity, the thickness of the ice lens will be equal to the initial crack thickness of the soil sample.

[0033] In the third step, substitute the on - site real - time monitoring data into the prediction model to predict the thickness of the ice lens on site in real time.

[0034] Perform grayscale processing on the photo. Use the MATLAB program to statistically analyze the average thickness W0 of the ice lens cracks in the photo. Using the origin software, according to the empirical model formula W = W0 + b÷V a , fit the experimental data W, V, and W0 to obtain the first parameter a and the second parameter b corresponding to this soil sample. Thereafter, when using the empirical model formula for the thickness of the ice lens at the same location, this set of parameters a and b can be directly used.

[0035] The monitoring method of this embodiment provides a simple and safe means for predicting the thickness of ice lenses in the construction of the engineering freezing method. Its measurement cost is relatively low, and the measuring equipment can be recycled, which not only saves energy and protects the environment but also realizes green and pollution - free operation.

[0036] The device adopted by the monitoring method of this embodiment is simple, and the process is streamlined, providing an idea and method for indirectly observing mesoscopic changes by monitoring macroscopic data, that is, predicting the growth of mesoscopic ice lenses in soil and the frost heaving effect through the moving rate of the macroscopic soil freezing front. In actual engineering, as an in-situ measurement method, this method avoids the harsh conditions that may be encountered during sampling observation, such as errors caused by difficult sampling, temperature changes, etc., and problems such as complex measurement processes.

[0037] The empirical model for predicting the thickness of ice lenses on which the monitoring method of this embodiment depends is based on a large amount of laboratory experimental data, has high reliability, and is widely applicable to various working conditions and environments.

[0038] The monitoring method of this embodiment can stably record the temperature changes of the soil in the measured area during the whole freezing process of freezing method construction, and realize continuous observation of the growth of ice lenses in each section of soil.

[0039] Refer to Figure 1 As shown, the present invention provides an in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction.

[0040] The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction includes the following steps.

[0041] Step S100, determine the freezing center of the freezing construction area 10, and determine the freezing range according to the freezing center.

[0042] After determining the freezing center of the freezing construction area 10, the actual freezing front diffuses radially outward from the freezing center, and the freezing range is determined according to the requirements of freezing construction. Ice lenses will appear within the freezing range.

[0043] Step S200, set multiple detection routes within the freezing range, and obtain the data of temperature changing with time on each detection route.

[0044] Setting multiple detection routes for real-time monitoring helps to improve the accuracy of monitoring and ensure that the predicted thickness of the actual ice lens is affected by an abnormality in a certain detection route.

[0045] Avoid the deviation of the predicted thickness of the ice lens caused by the detection route exceeding the freezing range.

[0046] Select the route to be detected on-site in the frozen construction area 10, and the route to be detected obtains the measured moving speed of the 0°C freezing front in real time. For example, the speed of the experimental freezing front can be obtained by measuring the rate of change of the position where the temperature near the route to be detected drops to 0°C. Multiple temperature sensors can be set on the route to be detected to measure the temperature change near the route to be detected through the temperature sensors; or the measured moving speed of the 0°C freezing front can be obtained by using image processing technology to obtain the rate of change of the actual freezing front position. The image processing technology can place the camera on the route to be detected.

[0047] Set multiple real-time monitoring points on the route to be detected. The multiple real-time monitoring points are evenly distributed along the moving direction of the actual freezing front, and the distance between every two adjacent real-time monitoring points is a preset distance.

[0048] When freezing construction is carried out in the frozen construction area 10, multiple real-time monitoring points need to be set on each route to be detected. During the freezing construction process, the moving situation of the actual freezing front is judged by measuring the temperature of all real-time monitoring points.

[0049] The multiple real-time monitoring points are evenly distributed along the moving direction of the actual freezing front, and it is ensured that the distance between every two adjacent real-time monitoring points is a preset distance.

[0050] Obtain the temperature of all real-time monitoring points and obtain the moment when each temperature drops to the preset temperature.

[0051] When the actual freezing front moves past the real-time monitoring point, the temperature measured by the real-time monitoring point will drop to the preset temperature. Therefore, it can be judged that the actual freezing front has reached this real-time monitoring point. So, by recording the moment when the temperature of each real-time monitoring point drops to the preset temperature, the moments corresponding to when the actual freezing front passes through multiple real-time monitoring points in sequence can be judged. Therefore, the temperature change data over time can be obtained.

[0052] Step S300, calculate the measured moving speed of the 0°C freezing front of the route to be detected according to the temperature change data over time.

[0053] Calculate the measured moving speed of the 0°C freezing front according to the preset distance and the moment.

[0054] The time consumed for the actual freezing front to move can be obtained through the time difference between the moments of any two real-time monitoring points. Then, the distance between the above two real-time monitoring points can be calculated through the preset distance. Dividing the distance by the time can obtain the average speed of the actual freezing front moving between the above two real-time monitoring points, that is, the measured moving speed of the 0°C freezing front.

[0055] Step S400, calculate the predicted thickness of ice lenses at any position on the route to be detected based on the measured moving rate of the 0°C freezing front and the empirical model formula.

[0056] Substitute the measured moving rate of the 0°C freezing front into a more accurate empirical model formula to obtain a more accurate predicted thickness of the actual ice lenses.

[0057] In some embodiments, the empirical model formula is as follows: W1 = W0 + b ÷ V1 a ; where W1 is the predicted thickness of the ice lenses, W0 is the initial crack thickness, a is the first parameter, b is the second parameter, and V1 is the measured moving rate of the 0°C freezing front.

[0058] Transfer the soil samples within the freezing range to an open freezing laboratory for experiments to obtain the first parameter a and the second parameter b.

[0059] Transfer the soil samples within the freezing range to an open freezing laboratory for experiments to obtain the first parameter a and the second parameter b, including: Obtain the soil samples within the freezing range; Set multiple experimental monitoring points on the soil samples. The multiple experimental monitoring points are evenly distributed along the moving direction of the experimental freezing front, and the distance between every two adjacent experimental monitoring points is a preset distance; Obtain the experimental temperatures of all experimental monitoring points and record the moments when each experimental temperature drops to the preset temperature; Calculate the moving rate of the 0°C freezing front in the laboratory experiment of the soil samples based on the preset distance and multiple moments; Obtain the image of the soil samples and obtain the thickness of the ice lenses in the laboratory experiment of the soil samples based on the image; Substitute the moving rate of the 0°C freezing front in the laboratory experiment and the thickness of the ice lenses in the laboratory experiment into the empirical model formula to calculate the first parameter a and the second parameter b.

[0060] When conducting a freezing experiment on the soil samples, take the freezing side of the soil samples as the starting side, and obtain the position of the experimental freezing front by measuring the temperature change or through image processing technology. For example, the rate of the experimental freezing front can be obtained by measuring the rate of change of the position where the soil sample temperature drops to 0°C, or the moving rate of the 0°C freezing front in the laboratory experiment can be obtained by obtaining the rate of change of the position of the experimental freezing front through image processing technology.

[0061] And through image processing technology, first obtain the image of the experimental ice lenses generated after the movement of the freezing front in the soil samples, and then calculate and analyze the thickness of the ice lenses in the laboratory experiment through a computer.

[0062] After obtaining the moving rate of the 0°C freezing front in the laboratory experiment and the thickness of the laboratory experiment ice lens from the above steps, since the experimental ice lens will be generated after the movement of the experimental freezing front, that is, there is a correlation between the moving rate of the 0°C freezing front in the laboratory experiment and the thickness of the laboratory experiment ice lens. Theoretically, when the moving rate of the 0°C freezing front in the laboratory experiment is zero, the experimental freezing front stays at this position for a longer time, causing the experimental ice lens at this position to continuously increase. When the position of the experimental freezing front tends to be stable, corresponding to the moving rate of the 0°C freezing front in the laboratory experiment being equal to zero, theoretically, under such conditions, the thickness of the laboratory experiment ice lens will continuously accumulate and tend to infinity. When the moving rate of the 0°C freezing front in the laboratory experiment approaches infinity, the thickness of the laboratory experiment ice lens will be equal to the thickness of the soil sample.

[0063] Therefore, based on the correlation between the moving rate of the 0°C freezing front in the laboratory experiment and the thickness of the laboratory experiment ice lens, a scatter plot is drawn with the moving rate of the 0°C freezing front in the laboratory experiment as the abscissa and the thickness of the laboratory experiment ice lens as the ordinate. Then, according to the scatter plot, the relationship curve between the moving rate of the 0°C freezing front in the laboratory experiment and the thickness of the laboratory experiment ice lens can be obtained.

[0064] Before the soil sample is subjected to the freezing experiment, the interior of the soil sample is in a loose multi-crack structure. Image analysis is performed on the soil sample, and the initial crack thickness of the cracks in the soil sample is obtained through analysis and calculation.

[0065] Due to the formation of cracks in the soil by the ice lens and the expansion of the cracks as the ice lens increases, there is also a correlation between the initial crack thickness of the cracks in the soil sample and the thickness of the ice lens. Therefore, by fitting the relevant empirical model formula based on the relationship curve between the moving rate of the 0°C freezing front in the laboratory experiment and the thickness of the laboratory experiment ice lens, the initial crack thickness can be used as a constant in the empirical model formula to correct the empirical model formula, which helps to improve the prediction accuracy of the predicted thickness of the ice lens.

[0066] Substituting the measured moving rate of the 0°C freezing front into a more accurate empirical model formula can obtain a more accurate predicted thickness of the actual ice lens.

[0067] According to the relationship curve, since experimental ice lenses are generated after the movement of the experimental freezing front, that is, there is a correlation between the movement rate of the 0°C freezing front in laboratory experiments and the thickness of the experimental ice lenses. Theoretically, when the movement rate of the 0°C freezing front in laboratory experiments is zero, the experimental freezing front stays at this position for a long time, causing the experimental ice lenses at this position to continuously increase. When the position of the experimental freezing front tends to be stable, corresponding to the movement rate of the 0°C freezing front in laboratory experiments being equal to zero, theoretically, under such conditions, the thickness of the experimental ice lenses in laboratory experiments will continuously accumulate and tend to infinity. When the movement rate of the 0°C freezing front in laboratory experiments approaches infinity, the thickness of the experimental ice lenses in laboratory experiments will be equal to the initial crack thickness of the original cracks in the soil sample.

[0068] Therefore, according to the above relationship, the image of the relationship curve is relatively close to the image of the inverse power function, and the first parameter a is greater than 0; the more the movement rate of the 0°C freezing front in laboratory experiments tends to 0, the more the thickness of the experimental ice lenses in laboratory experiments tends to infinity; the more the movement rate of the 0°C freezing front in laboratory experiments tends to infinity, the more the thickness of the experimental ice lenses in laboratory experiments tends to the initial crack thickness.

[0069] According to the empirical model formula fitted by the relationship curve, the first parameter a and the second parameter b also need to be corrected. Therefore, the relevant parameters in the scatter plot and the initial crack thickness W0 are substituted into the above empirical model formula to obtain the first parameter a and the second parameter b, and then an accurate empirical model formula is obtained.

[0070] Substitute the measured movement rate V1 of the 0°C freezing front monitored in real time on the route to be detected in the freezing construction area 10 into the empirical model formula, and calculate the predicted thickness of the actual ice lenses on the route to be detected from the empirical model formula, so as to guide the process of artificial freezing construction.

[0071] When conducting a freezing experiment on a soil sample, multiple experimental monitoring points need to be set on the soil sample, and the movement of the experimental freezing front is judged by measuring the temperature conditions of all experimental monitoring points during the freezing experiment.

[0072] To this end, in order to simulate the actual situation of the freezing construction area 10, multiple experimental monitoring points are evenly distributed along the movement direction of the experimental freezing front, and it is ensured that the distance between every two adjacent experimental monitoring points is the first preset distance.

[0073] When the experimental freezing front moves past an experimental monitoring point, the experimental temperature measured by the experimental monitoring point will drop to the preset temperature. Therefore, it can be judged that the experimental freezing front has reached this experimental monitoring point. So, by recording the experimental time when the experimental temperature of each experimental monitoring point drops to the preset temperature, the experimental times corresponding to when the experimental freezing front passes through multiple experimental monitoring points in sequence can be judged.

[0074] The time consumed for the movement of the experimental freezing front can be obtained from the time difference between the experimental moments of any two experimental monitoring points. Then, the distance between the two experimental monitoring points can be calculated through the first preset distance. By dividing the distance by the time, the average rate of movement of the experimental freezing front between the two experimental monitoring points can be obtained, which is the movement rate of the 0°C freezing front in the laboratory experiment.

[0075] The average rate of movement of the experimental freezing front between the two experimental monitoring points is the movement rate of the 0°C freezing front in the laboratory experiment. Therefore, it is necessary to count the thicknesses of all experimental ice lenses between the two experimental monitoring points to calculate the average thickness. For this purpose, images of all experimental ice lenses between the two experimental monitoring points need to be obtained.

[0076] The first thicknesses of all experimental ice lenses between the two experimental monitoring points are counted using image processing technology. Since the movement rate of the 0°C freezing front in the laboratory experiment is the average rate of movement of the experimental freezing front between the two experimental monitoring points, it is necessary to calculate the average value of the first thicknesses of all experimental ice lenses between the two experimental monitoring points to obtain the thickness of the experimental ice lens in the laboratory experiment. Then, a corresponding relationship is formed between the thickness of the experimental ice lens in the laboratory experiment and the movement rate of the 0°C freezing front in the laboratory experiment.

[0077] Taking the movement rate of the 0°C freezing front in the laboratory experiment of the experimental freezing front as the abscissa and the thickness of the experimental ice lens in the laboratory experiment as the ordinate, a coordinate system is established. Then, after all the movement rates of the 0°C freezing front in the laboratory experiment and all the thicknesses of the experimental ice lens in the laboratory experiment are put into one-to-one correspondence to form multiple coordinate points, all the coordinate points are plotted in the coordinate system to form a scatter plot.

[0078] There are some abnormal data or abnormal coordinate points that do not meet the requirements in the scatter plot. The abnormal data and abnormal coordinate points are removed. Then, multiple coordinate points are fitted to form a relationship curve so that the relationship curve can accurately show the correlation between the movement rate of the 0°C freezing front in the laboratory experiment and the thickness of the experimental ice lens in the laboratory experiment.

[0079] The present invention also provides an in-situ continuous monitoring system for the thickness of ice lenses in artificial freezing construction, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction in the above embodiment.

[0080] Take, for example, the case where the processor and the memory in the in-situ continuous monitoring system for the thickness of ice lenses constructed by artificial freezing can be connected via a bus. As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory, and can also include non-transitory memory, such as at least one disk memory, flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory optionally includes memories remotely arranged relative to the control processor, and these remote memories can be connected to the controller via a network.

[0081] The non-transitory software programs and instructions required to implement the monitoring method of the above embodiments are stored in the memory, and when executed by the processor, implement the monitoring method in the above embodiments. For example, execute the method steps S100 to step S400 described above. Figure 1 in the above.

[0082] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than those shown in the figures, or combine certain steps, or different steps.

[0083] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0084] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and their appropriate combinations.

[0085] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above figures are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0086] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist simultaneously. Here, A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one (item) of the following" or its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one (item) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0087] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the above division of units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0088] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0090] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of this application. The foregoing storage medium includes: various media that can store programs such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0091] The embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various changes without departing from the spirit of the present invention.

Claims

1. An in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction, characterized in that, Including: Determine the freezing range of the frozen construction area; Set a plurality of routes to be detected within the freezing range, and obtain the data of the temperature change with time on each route to be detected; Calculate the measured moving rate of the 0°C freezing front of the route to be detected according to the temperature change data with time; Calculate the predicted thickness of the ice lens at any position on the route to be detected according to the measured moving rate of the 0°C freezing front and the empirical model formula.

2. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 1, characterized in that The empirical model formula is as follows: W1 = W0 + b ÷ V1 a ; Wherein, W1 is the predicted thickness of the ice lens, W0 is the initial crack thickness of the in-situ soil, a is the first parameter, b is the second parameter, and V1 is the measured moving rate of the 0°C freezing front; Carry out an open freezing laboratory experiment on the soil samples within the freezing range to obtain the first parameter a and the second parameter b.

3. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 2, characterized in that The step of carrying out an open freezing laboratory experiment on the soil samples within the freezing range to obtain the first parameter a and the second parameter b includes: Use a thin-wall soil sampler to obtain unfrozen soil samples within the freezing range; Set a plurality of laboratory experiment monitoring points on the soil sample, and the plurality of experiment monitoring points are evenly distributed along the column side surface of the cylindrical soil sample, and the distance between every two adjacent experiment monitoring points is a preset distance; Carry out open freezing on the test sample. During the freezing period, the test sample is placed vertically, the top plane of the cylindrical test sample is the freezing surface, and the bottom plane is the water replenishing surface; during the freezing process, the 0°C freezing front moves from the top plane to the bottom plane; Obtain the experimental temperatures of all the experiment monitoring points during the freezing experiment process, and record the moment when the temperature of each monitoring point reaches 0°C; According to the distance L between two adjacent experiment monitoring points and the time difference t when the temperatures of two adjacent experiment monitoring points reach 0°C, calculate the average velocity V of the 0°C freezing front between two adjacent monitoring points according to the formula V = L / t; Obtain the moving rate of the 0°C freezing front of the laboratory experiment at each position along the vertical direction of the test sample; Use a microscopic camera to obtain the image of the soil sample, and obtain the thickness of the ice lens of the laboratory experiment at each position along the vertical direction of the test sample according to the image; Substitute the moving rate of the 0°C freezing front of the laboratory experiment and the thickness of the ice lens of the laboratory experiment at each position into the empirical model formula, and the first parameter a and the second parameter b can be obtained by using regression analysis.

4. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 3, characterized in that The monitoring method further includes: Draw a scatter plot according to the moving rate of the 0°C freezing front of the laboratory experiment and the thickness of the ice lens of the laboratory experiment, and obtain the relationship curve between the moving rate of the 0°C freezing front of the laboratory experiment and the thickness of the ice lens of the laboratory experiment according to the scatter plot; Obtain the initial crack thickness of the soil sample, and construct an empirical model formula according to the relationship curve and the initial crack thickness.

5. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 3, characterized in that The step of transferring the soil samples within the freezing range to an open freezing laboratory to carry out a laboratory experiment to obtain the first parameter a and the second parameter b further includes: Prepare the in-situ observation equipment for laboratory ice lenses. The observation equipment includes a specimen chamber and a monitoring computer. The specimen chamber is made of high-density polystyrene. A first semiconductor refrigeration chip is installed at the upper end of the specimen chamber, and the first semiconductor refrigeration chip is used to adjust the temperature gradient between the upper and lower ends of the specimen chamber and the cooling rate at the upper end according to experimental requirements. m temperature sensors are evenly distributed on the inner wall of the specimen chamber, and the distance between every two adjacent temperature sensors is k. The temperature sensors are electrically connected to the monitoring computer, and the monitoring computer monitors the temperature change of the soil sample in the specimen chamber in real time.

6. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 5, wherein, Obtaining the image of the soil sample includes: The observation equipment further includes an electron microscope, a photography chamber, a rotary lifting table, and a dehumidifier. The side wall of the photography chamber is provided with a transparent material, and a second semiconductor refrigeration chip is installed at the upper end of the photography chamber. The second semiconductor refrigeration chip is used to adjust the temperature between the upper and lower ends of the photography chamber and the cooling rate according to experimental requirements, so that the temperature environment of the photography chamber is the same as that of the specimen chamber. The lower end of the photography chamber is connected to the dehumidifier, the lower end of the photography chamber is connected to the rotary lifting table, and the rotary lifting table adjusts the rotation angle and height of the photography chamber to change the photographing surface of the soil sample. The lens of the electron microscope faces the photography chamber. The rotary lifting table zeros the height of the photography chamber, evenly sprays an anti-fog agent on the inner and outer walls of the photography chamber, turns on the dehumidifier. When the humidity in the photography chamber is lower than 30%, turn on the second semiconductor refrigeration chip. When the temperature of the photography chamber is equal to the temperature of the specimen chamber, turn off the dehumidifier.

7. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 1, characterized in that, Obtaining the data of the temperature change with time on each of the to-be-detected routes is realized by a chain temperature sensor. The chain temperature sensor includes a plurality of polyethylene rods and a plurality of temperature-sensitive elements. The plurality of temperature-sensitive elements are respectively installed on the plurality of polyethylene rods. The distance between every two adjacent temperature-sensitive elements is A, the length of the chain temperature sensor is h, and the number n of the temperature-sensitive elements satisfies A×n = h.

8. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 7, characterized in that, Setting a plurality of to-be-detected routes within the freezing range includes: Setting a plurality of the to-be-detected routes to be circularly arrayed around the freezing center in the freezing construction area; Controlling each of the to-be-detected routes not to exceed the freezing range; Placing the chain temperature sensor on the to-be-detected route.

9. The in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to claim 8, characterized in that Placing the chain temperature sensor on the to-be-detected route includes: Drilling installation holes on each of the to-be-detected routes. The installation holes do not exceed the freezing range, and the diameter of the installation holes is not less than the outer diameter of the chain sensor; Cleaning the installation holes, placing the chain temperature sensor into the installation holes, and making the temperature-sensitive elements closely adhere to the hole walls of the installation holes; Checking the working state of the chain temperature sensor and calibrating the temperature of the chain temperature sensor.

10. An in-situ continuous monitoring system for the thickness of ice lenses in artificial freezing construction, characterized in that, It includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the in-situ continuous monitoring method for the thickness of ice lenses in artificial freezing construction according to any one of claims 1 to 9.

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