Method for monitoring damage of lining under freeze-thaw cycle based on multi-source physical sensing

Abstract

This invention provides a method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing, belonging to the field of lining damage monitoring technology. The method includes: setting up a multi-type sensor array at key locations of the lining structure at multiple moments during the monitoring cycle to collect multi-source physical data in real time during the freeze-thaw cycle; acquiring lining data; constructing a disease pattern discrimination criterion; determining a first monitoring result based on the disease pattern discrimination criterion and the multi-source physical data; determining a comprehensive coefficient of lining freeze-thaw damage based on the multi-source physical data and the lining data; determining a damage deterioration coefficient based on the comprehensive coefficient of lining freeze-thaw damage; and determining a final monitoring result based on the damage deterioration coefficient, the comprehensive coefficient of lining freeze-thaw damage, and the first monitoring result. According to this invention, the accuracy of lining damage monitoring results can be improved.

Description

Technical Field

[0001] This invention relates to the field of lining damage monitoring technology, and in particular to a method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing. Background Technology

[0002] In related technologies, single-sensor monitoring cannot reflect the complex mechanisms of multi-field coupling such as moisture migration, temperature change, frost heave force and structural deformation during freeze-thaw cycles. Existing assessment methods often focus on qualitative description or semi-quantitative judgment based on experience. There is a lack of a quantitative comprehensive damage assessment model that can integrate multi-source sensor data, material properties and service history. In other words, related technologies are difficult to accurately determine the damage state, development rate and remaining life of lining structures under freeze-thaw action, and it is difficult to improve the accuracy of lining damage monitoring results under freeze-thaw cycles.

[0003] The information disclosed in the background section of this application is intended only to enhance the understanding of the general background of this application and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0004] This invention provides a method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing, which can solve the technical problem that related technologies are unable to accurately determine the damage state, development rate and remaining life of lining structures under freeze-thaw cycles, and are unable to improve the accuracy of lining damage monitoring results under freeze-thaw cycles.

[0005] According to a first aspect of the present invention, a method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing is provided, comprising:

[0006] At multiple points during the monitoring cycle, multi-type sensor arrays are set up at key locations in the lining structure to collect multi-source physical data in real time during the freeze-thaw cycle.

[0007] Obtain lining data;

[0008] Establish criteria for disease pattern identification;

[0009] Based on the disease pattern discrimination criteria and the multi-source physical data, the first monitoring result is determined;

[0010] Based on the multi-source physical data and the lining data, the comprehensive coefficient of freeze-thaw damage of the lining is determined;

[0011] The damage deterioration coefficient is determined based on the comprehensive coefficient of freeze-thaw damage of the lining.

[0012] The final monitoring result is determined based on the damage deterioration coefficient, the comprehensive coefficient of freeze-thaw damage of the lining, and the first monitoring result.

[0013] According to the present invention, the multi-type sensor array includes: a temperature sensor, a moisture sensor, an earth pressure sensor, and a displacement meter, wherein the temperature sensor and the moisture sensor are disposed inside the canal foundation soil to monitor moisture migration and frost depth changes, the earth pressure sensor is disposed at the interface between the lower surface of the lining and the canal foundation soil to monitor normal frost heave force, and the displacement meter is disposed on the surface of the lining plate to monitor the geometry of the entire cross-section lining.

[0014] According to the present invention, determining a first monitoring result based on the disease pattern discrimination criteria and the multi-source physical data includes:

[0015] Based on the multi-source physical data, quantitative damage characterization indicators are determined;

[0016] The first monitoring result is determined based on the quantitative damage characterization index and the disease pattern discrimination criterion.

[0017] According to the present invention, based on the multi-source physical data, determining quantitative damage characterization indicators includes:

[0018] Based on the multi-source physical data, the initial bearing capacity value of the vulnerable part of the lining structure and the remaining bearing capacity value of the part after freeze-thaw cycles are determined.

[0019] The first difference is determined based on the initial bearing capacity value and the remaining bearing capacity value;

[0020] Based on the first difference and the initial bearing capacity value, a quantitative characterization index for damage is determined.

[0021] According to the present invention, the comprehensive coefficient of freeze-thaw damage of the lining is determined based on the multi-source physical data and the lining data, including:

[0022] Obtain the number of freeze-thaw cycles that have occurred and the duration of a single freeze-thaw cycle;

[0023] Based on the multi-source physical data, the maximum temperature difference during the freeze-thaw cycle and the real-time moisture migration per unit time are determined.

[0024] Based on the multi-source physical data, the real-time maximum normal frost heave force, initial normal frost heave force, real-time maximum lining displacement, and initial lining displacement monitored during the freeze-thaw cycle were determined.

[0025] Based on the lining data, the saturated moisture content of the lining material, the service time of the lining, and the aging and deterioration rate of the lining material are determined.

[0026] The comprehensive coefficient of freeze-thaw damage to the lining is determined based on the number of freeze-thaw cycles that have occurred, the duration of a single freeze-thaw cycle, the maximum temperature difference during the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging and decay rate of the lining material.

[0027] According to the present invention, a comprehensive coefficient for freeze-thaw damage of the lining is determined based on the number of freeze-thaw cycles, the duration of a single freeze-thaw cycle, the maximum temperature difference during the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging and decay rate of the lining material, including: according to the formula:

[0028] Determine the comprehensive coefficient of lining freeze-thaw damage caused by the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period. ,in, , and To preset weights, To determine the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period, The saturated moisture content of the lining material. The maximum normal frost heave force detected in the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. The initial normal frost heave force, This represents the real-time maximum lining displacement monitored during the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. This represents the initial lining displacement. The duration of a single freeze-thaw cycle is the number of freeze-thaw cycles that have occurred at time i in the monitoring cycle. This refers to the maximum temperature difference across freeze-thaw cycles monitored at the i-th moment of the monitoring cycle. This represents the real-time moisture migration per unit time within the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. The aging and degradation rate of the lining material. Let i be the lining usage time at the i-th moment of the monitoring cycle. This is the real-time water migration rate per unit time during the preset monitoring period. The maximum temperature difference during the freeze-thaw cycle of the preset monitoring period. The duration of a single freeze-thaw cycle is set for the preset monitoring period.

[0029] According to the present invention, the damage deterioration coefficient is determined based on the comprehensive coefficient of freeze-thaw damage of the lining, including:

[0030] Based on the comprehensive coefficient of freeze-thaw damage to the lining and the number of freeze-thaw cycles that have occurred, determine the function of the comprehensive coefficient of freeze-thaw damage to the lining as a function of the number of freeze-thaw cycles that have occurred.

[0031] Differentiate the damage comprehensive coefficient change function to determine the derivative of the damage comprehensive coefficient change function;

[0032] The damage deterioration coefficient is determined based on the derivative of the damage comprehensive coefficient change function and the lining freeze-thaw damage comprehensive coefficient.

[0033] According to the present invention, the damage deterioration coefficient is determined based on the derivative of the damage comprehensive coefficient change function and the lining freeze-thaw damage comprehensive coefficient, including: according to the formula: Determine the damage degradation coefficient caused by the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period. ,in, The derivative of the damage composite coefficient variation function. The comprehensive coefficient of freeze-thaw damage to the lining is the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle.

[0034] According to a second aspect of the present invention, a lining damage monitoring system based on multi-source physical sensing under freeze-thaw cycles is provided, comprising:

[0035] The physical data module is used to set up multi-type sensor arrays at key locations of the lining structure at multiple moments during the monitoring cycle to collect multi-source physical data in real time during the freeze-thaw cycle.

[0036] Lining data module, used to acquire lining data;

[0037] The discrimination criteria module is used to construct discrimination criteria for disease patterns;

[0038] The first result module is used to determine the first monitoring result based on the disease pattern discrimination criteria and the multi-source physical data;

[0039] The damage coefficient module is used to determine the comprehensive coefficient of freeze-thaw damage of the lining based on the multi-source physical data and the lining data.

[0040] The degradation coefficient module is used to determine the damage degradation coefficient based on the comprehensive coefficient of freeze-thaw damage of the lining.

[0041] The final result module is used to determine the final monitoring result based on the damage deterioration coefficient, the lining freeze-thaw damage comprehensive coefficient, and the first monitoring result.

[0042] Technical effects: According to the present invention, multi-source physical data and lining data during the freeze-thaw cycle can be accurately collected, and a disease pattern discrimination criterion can be constructed. Based on the disease pattern discrimination criterion and multi-source physical data, the first monitoring result is determined. At the same time, based on the multi-source physical data and lining data, the contribution of each influencing factor to the comprehensive coefficient of freeze-thaw damage of the lining can be evaluated, and the comprehensive coefficient of freeze-thaw damage of the lining can be determined. Then, based on the comprehensive coefficient of freeze-thaw damage of the lining, the damage deterioration coefficient is determined. Furthermore, based on the damage deterioration coefficient, the comprehensive coefficient of freeze-thaw damage of the lining, and the first monitoring result, the final monitoring result is determined comprehensively, thereby improving the accuracy and comprehensiveness of the monitoring results. When determining the comprehensive coefficient of freeze-thaw damage to linings, the following factors can be considered: the number of freeze-thaw cycles, the duration of a single freeze-thaw cycle, the maximum temperature difference during the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging attenuation rate of the lining material. During the calculation, the contributions of damage accumulation factors, frost heave force factors, and environmental-aging coupling factors to the comprehensive coefficient of freeze-thaw damage are comprehensively considered, thus improving the accuracy of the comprehensive coefficient. Similarly, when determining the damage deterioration coefficient, the derivative of the damage comprehensive coefficient change function and the comprehensive coefficient of freeze-thaw damage to linings can be used to determine the damage deterioration coefficient. During the calculation, the contribution of freeze-thaw cycles to the accelerated deterioration of freeze-thaw damage to the lining can be accurately assessed, further improving the accuracy of the damage deterioration coefficient.

[0043] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Other features and aspects of the invention will become clearer from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0045] Figure 1 An exemplary flowchart of a method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing according to an embodiment of the present invention is shown.

[0046] Figure 2 An exemplary schematic diagram illustrating the determination of a first monitoring result according to an embodiment of the present invention is shown;

[0047] Figure 3A schematic diagram illustrating the determination of the comprehensive coefficient of freeze-thaw damage of the lining according to an embodiment of the present invention is shown.

[0048] Figure 4 A schematic diagram illustrating the determination of the damage degradation coefficient according to an embodiment of the present invention is shown exemplarily;

[0049] Figure 5 A block diagram of a lining damage monitoring system based on multi-source physical sensing under freeze-thaw cycles according to an embodiment of the present invention is shown as an example.

[0050] Figure 6 A schematic diagram of a multi-scale damage finite element-discrete element model of a lining structure according to an embodiment of the present invention is shown as an example. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0053] Figure 1 An exemplary flowchart illustrates a method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing according to an embodiment of the present invention. The method includes:

[0054] Step S1: At multiple moments during the monitoring cycle, at key locations of the lining structure, set up arrays of multiple types of sensors to collect multi-source physical data during the freeze-thaw cycle in real time.

[0055] Step S2: Obtain lining data;

[0056] Step S3: Construct disease pattern identification criteria;

[0057] Step S4: Determine the first monitoring result based on the disease pattern discrimination criteria and the multi-source physical data;

[0058] Step S5: Determine the comprehensive coefficient of freeze-thaw damage of the lining based on the multi-source physical data and the lining data;

[0059] Step S6: Determine the damage deterioration coefficient based on the comprehensive coefficient of freeze-thaw damage of the lining;

[0060] Step S7: Determine the final monitoring result based on the damage deterioration coefficient, the lining freeze-thaw damage comprehensive coefficient, and the first monitoring result.

[0061] The method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing according to embodiments of the present invention can accurately collect multi-source physical data and lining data during the freeze-thaw cycle process, construct a disease pattern discrimination criterion, determine a first monitoring result based on the disease pattern discrimination criterion and multi-source physical data, and simultaneously assess the contribution of each influencing factor to the comprehensive coefficient of lining freeze-thaw damage based on the multi-source physical data and lining data, determine the comprehensive coefficient of lining freeze-thaw damage, and then determine the damage deterioration coefficient based on the comprehensive coefficient of lining freeze-thaw damage. Furthermore, based on the damage deterioration coefficient, the comprehensive coefficient of lining freeze-thaw damage, and the first monitoring result, the final monitoring result is comprehensively determined, thereby improving the accuracy and comprehensiveness of the monitoring results.

[0062] According to one embodiment of the present invention, in step S1, at multiple times during the monitoring cycle, at key locations of the lining structure, a multi-type sensor array is set up to collect multi-source physical data during the freeze-thaw cycle in real time.

[0063] According to one embodiment of the present invention, the multi-type sensor array includes: a temperature sensor, a moisture sensor, an earth pressure sensor, and a displacement meter, wherein the temperature sensor and the moisture sensor are disposed inside the canal foundation soil to monitor moisture migration and frost depth changes, the earth pressure sensor is disposed at the interface between the lower surface of the lining and the canal foundation soil to monitor normal frost heave force, and the displacement meter is disposed on the surface of the lining plate to monitor the geometry of the entire cross-section lining.

[0064] For example, the critical locations of the lining structure, i.e. the vulnerable parts of the lining structure, refer to stress concentration areas, joints, corners, and weak sections of the lining structure. During the compaction of the canal foundation soil, temperature and moisture sensors are installed in layers from bottom to top according to design requirements. After the canal foundation soil has completed consolidation and settlement, the lining is laid. Earth pressure sensors and displacement gauges are installed at the critical locations of the lining structure. Temperature sensors are used to monitor the temperature field distribution inside and on the surface of the lining and quantify the temperature load characteristics of freeze-thaw cycles. Moisture sensors are used to monitor changes in the moisture content of the lining material and reflect changes in moisture migration and freezing depth during freeze-thaw cycles. Earth pressure sensors are used to monitor changes in strain between the lining structure and the canal foundation soil and reflect structural deformation (caused by changes in normal frost heave force) and damage evolution. Displacement gauges are used to monitor the displacement of the lining surface (displacement perpendicular to the lining and crack opening and closing) and capture signs of damage such as structural cracking and displacement.

[0065] According to one embodiment of the present invention, in step S2, lining data is acquired.

[0066] For example, lining data refers to the inherent properties of the lining structure itself and its historical state during long-term service, which can be obtained through saturation drying tests and aging degradation tests in the laboratory.

[0067] According to one embodiment of the present invention, in step S3, a disease pattern discrimination criterion is constructed.

[0068] For example, based on indoor scaled-scale lining channel model tests, a disease pattern discrimination criterion of "freeze-thaw cycles - damage threshold - disease pattern" is established to reveal the critical conditions for the occurrence of diseases in channel lining structures. The disease pattern discrimination criterion aims to establish a quantitative mapping relationship between "freeze-thaw cycle count (external drive) → structural damage degree (internal state) → macroscopic disease morphology (failure manifestation)". The specific construction method is as follows: 1. Obtain preliminary correlation data of "freeze-thaw cycles - damage threshold - disease" through indoor model tests (conduct indoor scaled-scale full-section trapezoidal channel model freeze-thaw cycle tests, set two typical working conditions of "with groundwater recharge" and "without groundwater recharge", and conduct periodic freeze-thaw tests on the channel model made according to similarity theory in a large low-temperature environment model box. During the test, the moisture, temperature, and earth pressure of the channel foundation soil, the full-section displacement and deformation of the lining structure, and the occurrence time of macroscopic diseases such as mortar joint cracking, lining plate heave, and spalling are recorded by taking photos at regular intervals). 1. Location and evolution process: Establish a first-hand correlation database through direct observation. For example, record the first observation of microcracks in a vulnerable part (e.g., mortar joint) during the Nth freeze-thaw cycle. The corresponding monitoring data (stress, deformation) and structural state at this time are the preliminary "damage threshold" and corresponding "freeze-thaw cycles" for this disease mode ("microcrack"). 2. Reveal the disease mechanism and quantify the "damage threshold" through theoretical modeling and numerical simulation (based on the experimental data from the above steps and the interface mechanical parameters obtained from independent "freeze-thaw cycle-low temperature direct shear test", establish an analytical model of the freeze-thaw deformation feedback relationship between the lining structure containing vulnerable parts and the canal foundation soil. This model can mechanically explain how the frost heave deformation of the canal foundation soil is transmitted and leads to the redistribution and deformation of the internal forces of the lining structure, and establish a multi-scale damage model: For vulnerable parts (mortar joints), establish a numerical model of the damage evolution process dominated by the cross-scale propagation of microcracks. This model adopts the finite element-discrete element coupling (FEM-DEM) method, and the model is as follows. Figure 6 As shown, Figure 6 In This represents the overall hydraulic conductivity of the soil. This indicates that the shear stress borne by the lining structure or channel foundation soil at location x is large, enabling the simulation of the entire process of microcrack initiation, propagation, penetration, and eventual formation of macroscopic cracks within the mortar at a microscale. Based on damage mechanics theory, a quantitative damage characterization index (i.e., the quantitative damage characterization index in step S41) is proposed. Using this numerical model, the damage evolution process of the lining structure under different freeze-thaw cycles is simulated. The simulated microcrack development state is correlated with the macroscopic disease patterns observed in the above experimental steps. Thus, when the numerical simulation shows crack penetration (predicting macroscopic cracking), the corresponding damage index value is determined as the quantitative damage threshold for that disease (e.g., "penetrating cracking"). 3. The freeze-thaw cycle number and disease observation data obtained from the experiment are integrated and verified with the quantitative relationship between the damage characterization index threshold and the disease mechanism obtained from the model, ultimately forming a set of discrimination criteria that can be applied in engineering. For example, when the number of freeze-thaw cycles exceeds a certain value, and the quantitative damage characterization index obtained through monitoring data inversion or model calculation exceeds a certain threshold (e.g., 0.3), it is determined that the lining mortar joints are at high risk of penetrating cracks. When the number of freeze-thaw cycles exceeds another value, and the quantitative damage characterization index exceeds a higher threshold (e.g., 0.6), it is determined that lining plate bulging or collapse may occur. The numerical model is verified and calibrated using partial experimental data to ensure that the model can accurately reflect the actual damage evolution process, thereby improving the reliability and universality of the established discrimination criteria.

[0069] According to one embodiment of the present invention, in step S4, a first monitoring result is determined based on the disease pattern discrimination criteria and the multi-source physical data.

[0070] Figure 2 An exemplary schematic diagram illustrating the determination of a first monitoring result according to an embodiment of the present invention is shown.

[0071] Step S41: Determine quantitative damage characterization indicators based on the multi-source physical data;

[0072] Step S42: Determine the first monitoring result based on the quantitative damage characterization index and the disease pattern discrimination criterion.

[0073] For example, based on multi-source physical data, the level of loss of the bearing capacity of the lining structure is assessed, and quantitative indicators of damage are determined. These quantitative indicators are then substituted into the disease pattern discrimination criteria to determine whether the lining is currently in a certain disease pattern and at a certain stage of development, such as the initial, development, or stable stage. The first monitoring result is generated, which includes information such as disease type, location, severity (e.g., mild, moderate, severe) and development trend (e.g., accelerating, slowing down, stabilizing). This information is presented in a visual interface, such as a trend graph and a 3D model rendering, to provide engineers with intuitive monitoring conclusions.

[0074] According to an embodiment of the present invention, step S41 includes:

[0075] Step S411: Based on the multi-source physical data, determine the initial bearing capacity value of the vulnerable part of the lining structure and the remaining bearing capacity value of the part after freeze-thaw cycles.

[0076] Step S412: Determine the first difference based on the initial bearing capacity value and the remaining bearing capacity value;

[0077] Step S413: Determine the quantitative damage characterization index based on the first difference and the initial bearing capacity value.

[0078] For example, the initial bearing capacity value refers to the bearing capacity value of the lining structure before freeze-thaw cycles, obtained through freeze-thaw cycle tests on the lining channel model; the remaining bearing capacity value refers to the bearing capacity value of the lining structure after freeze-thaw cycles, obtained through freeze-thaw cycle tests on the lining channel model; the first difference refers to the change in the bearing capacity value of the lining structure after freeze-thaw cycles relative to the value before freeze-thaw cycles. For example, if the initial bearing capacity value is 100kN and the remaining bearing capacity value is 75kN, then the first difference is 25kN; the quantitative damage characterization index is used to measure the relative loss of bearing capacity of vulnerable parts of the lining structure, and can be used to reflect the characteristics of the damage data, expressed by the formula: For example, if the first difference is 25kN and the initial load-bearing capacity is 100kN, then A value of 25% indicates that the lining structure has lost 25% of its initial load-bearing capacity.

[0079] According to one embodiment of the present invention, in step S5, the comprehensive coefficient of freeze-thaw damage of the lining is determined based on the multi-source physical data and the lining data.

[0080] Figure 3 A schematic diagram illustrating the determination of the comprehensive coefficient of freeze-thaw damage to the lining according to an embodiment of the present invention is shown.

[0081] According to an embodiment of the present invention, step S5 includes:

[0082] Step S51: Obtain the number of freeze-thaw cycles that have occurred and the duration of a single freeze-thaw cycle;

[0083] Step S52: Based on the multi-source physical data, determine the maximum temperature difference during the freeze-thaw cycle and the real-time moisture migration per unit time.

[0084] Step S53: Based on the multi-source physical data, determine the real-time maximum normal frost heave force, initial normal frost heave force, real-time maximum lining displacement, and initial lining displacement monitored during the freeze-thaw cycle.

[0085] Step S54: Based on the lining data, determine the saturated moisture content of the lining material, the lining service time, and the aging and decay rate of the lining material.

[0086] Step S55: Determine the comprehensive coefficient of freeze-thaw damage of the lining based on the number of freeze-thaw cycles that have occurred, the duration of a single freeze-thaw cycle, the maximum temperature difference of the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging and decay rate of the lining material.

[0087] For example, a continuous freezing-thawing cycle is defined as one freeze-thaw cycle. For instance, if the temperature drops from above 0°C to below 0°C (freezing) and then rises back above 0°C (thawing) within a certain period, this is counted as one freeze-thaw cycle. The number of freeze-thaw cycles that have occurred refers to the cumulative frequency of freeze-thaw cycles experienced by the lining structure from the start of the monitoring period to the present. The duration of a single freeze-thaw cycle refers to the length of the freeze-thaw cycle at the current moment. The maximum temperature difference of the freeze-thaw cycle refers to the difference between the highest and lowest temperatures within the current freeze-thaw cycle, representing the temperature fluctuation amplitude of that freeze-thaw cycle. This is obtained through embedded temperature sensors. The real-time moisture migration per unit time refers to the amount of moisture migrated within the lining (or the surrounding rock-lining interface) during the current monitoring period, obtained through embedded moisture sensors. The real-time maximum normal frost heave force refers to the maximum normal frost heave force borne by the lining during the current monitoring period. That is, when water in the canal foundation soil freezes into ice, its volume expansion generates outward normal pressure on the lining. The normal direction refers to the direction perpendicular to the lining surface. The initial normal frost heave force refers to the normal frost heave force at the beginning of the monitoring period, which is determined by the outward normal pressure generated by the canal foundation soil on the lining when the lining first experiences a freeze-thaw cycle. The real-time maximum lining displacement refers to the maximum deformation displacement of the lining during the current monitoring period. That is, the lining deforms due to the frost heave force of the canal foundation soil, and the direction is also perpendicular to the lining surface, consistent with the direction of the normal frost heave force. The initial lining displacement refers to the lining displacement at the beginning of the monitoring period, which is determined by the maximum deformation displacement of the lining when the lining first experiences a freeze-thaw cycle. The saturated moisture content of lining materials refers to the moisture content of lining materials (such as concrete and cement) when they reach a saturated state. It is determined by fully saturating and then drying standard specimens of lining materials, and calculating the mass difference before and after drying. The service life of lining refers to the time that the lining has been in service up to the current time of the monitoring cycle. It is determined by subtracting the time when the lining was put into use from the current time (in years). The aging and decay rate of lining materials refers to the rate at which the lining materials age over time. Material aging leads to a decrease in the strength, frost resistance, and ability to resist freeze-thaw damage of the material. It is determined by conducting accelerated aging tests on standard specimens of lining materials.

[0088] According to an embodiment of the present invention, step S55 includes: determining the comprehensive coefficient of lining freeze-thaw damage caused by the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period according to formula (1). ,

[0089] (1)

[0090] in, , and To preset weights, To determine the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period, The saturated moisture content of the lining material. The maximum normal frost heave force detected in the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. The initial normal frost heave force, This represents the real-time maximum lining displacement monitored during the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. This represents the initial lining displacement. The duration of a single freeze-thaw cycle is the number of freeze-thaw cycles that have occurred at time i in the monitoring cycle. This refers to the maximum temperature difference across freeze-thaw cycles monitored at the i-th moment of the monitoring cycle. This represents the real-time moisture migration per unit time within the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. The aging and degradation rate of the lining material. Let i be the lining usage time at the i-th moment of the monitoring cycle. This is the real-time water migration rate per unit time during the preset monitoring period. The maximum temperature difference during the freeze-thaw cycle of the preset monitoring period. The duration of a single freeze-thaw cycle is set for the preset monitoring period.

[0091] According to one embodiment of the present invention, The saturated moisture content of the lining material. The rate of material damage accumulation, representing the effect of saturated moisture content on the material, can be obtained by simply fitting the results of accelerated aging tests on the lining material. The larger the diameter, the greater the frost heave force generated by pore water freezing during freeze-thaw cycles (because more water converts into ice, resulting in more significant volume expansion), accelerating lining damage and increasing the damage rate of freeze-thaw cycles. To monitor the number of freeze-thaw cycles that have occurred at time i of the monitoring period, the number of freeze-thaw cycles is... The larger the diameter, the more severe the fatigue damage caused by repeated freeze-thaw cycles of pore water inside the lining. The term represents the damage accumulation influencing factor, indicating the impact of accumulated losses due to freeze-thaw cycles, which increases with the number of freeze-thaw cycles. The increase, The item is growing rapidly. Approaching 0, The closer the value is to 1, the greater the accumulated losses from the freeze-thaw cycle.

[0092] According to one embodiment of the present invention, The maximum normal frost heave force detected in the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. The initial normal frost heave force, This refers to the deviation of the real-time maximum normal frost heave force from the initial normal frost heave force at the i-th moment of the monitoring cycle, within the number of freeze-thaw cycles that have occurred. The term uses the initial normal frost heave force. The deviation of the real-time maximum normal frost heave force from the initial normal frost heave force monitored at the i-th moment of the monitoring period is normalized to reflect the degree of change of the maximum normal frost heave force relative to the initial state. The greater the deviation, the more significant the change in frost heave force, leading to a greater risk of lining cracking and deformation. This represents the real-time maximum lining displacement monitored during the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. This represents the initial lining displacement. The term represents the deviation of the real-time maximum lining displacement from the initial lining displacement during the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period. Item with initial lining displacement The deviation of the real-time maximum lining displacement from the initial lining displacement is normalized within the number of freeze-thaw cycles observed at time i of the monitoring period. This normalization reflects the degree of change of the maximum lining displacement relative to the initial lining displacement. The greater the deviation, the more severe the lining deformation, and the greater the risk of damage or instability to the lining structure. The term represents the frost heave force influencing factor, indicating the impact of the mechanical damage effect of frost heave-displacement caused by the freeze-thaw process. As the normal frost heave force and lining displacement increase, their increases are mutually influential and additive. The effect of frost heave-displacement on mechanical damage will gradually increase.

[0093] According to one embodiment of the present invention, , The preset baseline moisture migration per unit time refers to the moisture migration per unit time at the beginning of monitoring; that is, the moisture migration per unit time when the lining first experiences a freeze-thaw cycle is used as the preset baseline. This refers to the maximum temperature difference across freeze-thaw cycles monitored at the i-th moment of the monitoring cycle. The duration of a single freeze-thaw cycle is the number of freeze-thaw cycles that have occurred at time i in the monitoring cycle. This is the ratio of the maximum temperature difference during a freeze-thaw cycle to the duration of a single freeze-thaw cycle, representing the amplitude of temperature fluctuations and reflecting the severity of temperature changes within the current freeze-thaw cycle. The larger the pore size, the easier it is for water to freeze / thaw, and the more drastic the phase changes in pore water become. The smaller the size, the higher the freeze-thaw frequency, and the faster the damage accumulates. The larger, This refers to the maximum temperature difference during the freeze-thaw cycle within the preset monitoring period, i.e., the average of the maximum temperature differences during all freeze-thaw cycles within the preset monitoring period. This refers to the duration of a single freeze-thaw cycle within a preset monitoring period, specifically the average duration of all single freeze-thaw cycles within that period. The preset monitoring period is the design phase of the lining process. This is the ratio of the maximum temperature difference during the freeze-thaw cycle in the preset monitoring period to the duration of a single freeze-thaw cycle in the preset monitoring period, representing the preset value for the temperature fluctuation amplitude. This represents the ratio of the severity of temperature change within the current freeze-thaw cycle to a preset value for the temperature fluctuation range, reflecting the severity of the normalized temperature change range within the current freeze-thaw cycle. The larger the value, the more drastic the temperature change, and the greater the impact on freeze-thaw damage to the lining. This represents the real-time moisture migration per unit time within the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. This refers to the real-time moisture migration per unit time during the preset monitoring period, i.e., the average moisture migration per unit time across all thawing cycles. The ratio of the real-time moisture migration per unit time at the i-th moment of the monitoring cycle to the preset baseline moisture migration per unit time reflects the drastic change in moisture migration during the current thawing cycle. The larger the size, the more active the moisture migration and the more abundant the frost heave medium. The larger the item, This is the ratio of real-time water migration per unit time during a preset monitoring period to a preset baseline water migration per unit time, indicating the degree of drastic change in water migration during the preset monitoring period. This represents the ratio of the magnitude of change in moisture migration during the current freeze-thaw cycle to the magnitude of change during a preset monitoring period, reflecting the normalized magnitude of change in moisture migration during the current freeze-thaw cycle. The larger the value, the more drastic the change in moisture migration, and the greater the impact on freeze-thaw damage to the lining after experiencing freeze-thaw cycles. The aging and degradation rate of the lining material. For the lining usage time at the i-th moment of the monitoring cycle, the exponential term... This reflects the nonlinear change in the aging of the lining material, and the aging degradation rate of the lining material. The larger the lining, the longer its service life. The longer the term, the more exponents... The faster the increase, the faster the structural damage to the lining caused by material aging and freeze-thaw cycles will grow. The term represents the environmental-aging coupling effect factor, indicating the impact of environmental factors and material performance degradation during freeze-thaw cycles on the damage to the lining structure. This effect increases with temperature changes, moisture migration, and the degree of material aging. As the temperature increases, the freeze-thaw damage to the lining caused by the coupled effects of environment and aging also increases.

[0094] According to one embodiment of the present invention, , and The preset weights represent the combined coefficients of damage accumulation, frost heave, and environmental-aging coupling factors on the freeze-thaw damage of the lining. The degree of contribution of freeze-thaw cycle damage is crucial; for example, cumulative freeze-thaw cycle damage is a core factor in assessing freeze-thaw damage in linings. The more cumulative freeze-thaw cycles, the more developed the microcrack network within the material, leading to a continuous decrease in strength / freeze-thaw resistance. Higher saturated moisture content results in greater frost heave stress, causing damage to accumulate further. The value can be set to 0.5. Frost heave failure is an important factor in assessing freeze-thaw damage to linings. Frost heave failure is sudden (e.g., sudden cracking after a strong frost heave), and the degree of damage is affected by the cumulative damage from freeze-thaw cycles. It can be set to 0.3. The coupled effect of environment and aging is a common factor in the assessment of freeze-thaw damage of linings. Both environmental impact and material aging are chronic and have a long period of influence. They will not have a significant impact on the freeze-thaw damage of linings in a short period of time. It can be set to 0.2. The term represents the influencing factor of damage accumulation. Factors affecting frost heave Environmental-aging coupling factors Under the combined influence of various factors, the larger the values ​​of each factor, the higher the comprehensive coefficient of freeze-thaw damage to the lining. The larger the value, the greater the structural damage to the lining at time i of the monitoring period after multiple freeze-thaw cycles.

[0095] In this way, the comprehensive coefficient of freeze-thaw damage to the lining can be determined based on the number of freeze-thaw cycles, the duration of a single freeze-thaw cycle, the maximum temperature difference during the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging attenuation rate of the lining material. In the calculation process, the contribution of the damage accumulation influence factor, the frost heave force influence factor, and the environment-aging coupling influence factor to the comprehensive coefficient of freeze-thaw damage to the lining is comprehensively considered, thereby improving the accuracy of the comprehensive coefficient of freeze-thaw damage to the lining.

[0096] According to one embodiment of the present invention, in step S6, the damage deterioration coefficient is determined based on the comprehensive coefficient of freeze-thaw damage of the lining.

[0097] Figure 4 A schematic diagram illustrating the determination of the damage degradation coefficient according to an embodiment of the present invention is shown.

[0098] According to an embodiment of the present invention, step S6 includes:

[0099] Step S61: Based on the comprehensive coefficient of freeze-thaw damage of the lining and the number of freeze-thaw cycles that have occurred, determine the comprehensive coefficient of freeze-thaw damage of the lining as a function of the comprehensive coefficient of damage changing with the number of freeze-thaw cycles that have occurred.

[0100] Step S62: Differentiate the damage comprehensive coefficient change function to determine the derivative of the damage comprehensive coefficient change function;

[0101] Step S63: Determine the damage deterioration coefficient based on the derivative of the damage comprehensive coefficient change function and the lining freeze-thaw damage comprehensive coefficient.

[0102] For example, by fitting the comprehensive coefficient of freeze-thaw damage to the lining with the number of freeze-thaw cycles, a function for the change of the comprehensive coefficient of freeze-thaw damage to the lining as a function of the number of freeze-thaw cycles is determined. This function reflects the corresponding change of the comprehensive coefficient of freeze-thaw damage to the lining with the number of freeze-thaw cycles. The derivative of the function is obtained by taking the derivative of the comprehensive coefficient of freeze-thaw damage, which represents the rate of change of the comprehensive coefficient of freeze-thaw damage with the number of freeze-thaw cycles. Based on the derivative of the function of the comprehensive coefficient of freeze-thaw damage to the lining and the comprehensive coefficient of freeze-thaw damage to the lining, the magnitude of the change of the comprehensive coefficient of freeze-thaw damage with the number of freeze-thaw cycles is quantified, and the damage deterioration coefficient is determined.

[0103] According to an embodiment of the present invention, step S63 includes: determining the damage degradation coefficient caused by the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period according to formula (2). ,

[0104] (2)

[0105] in, The derivative of the damage composite coefficient variation function. The comprehensive coefficient of freeze-thaw damage to the lining is the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle.

[0106] According to one embodiment of the present invention, Let be the derivative of the damage composite coefficient function, representing the rate at which damage changes with the number of freeze-thaw cycles, reflecting how quickly the damage composite coefficient changes with each freeze-thaw cycle. The term represents the reciprocal of the comprehensive coefficient of lining freeze-thaw damage caused by the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period, indicating a correction for the rate of damage change. For example, in the comprehensive coefficient of lining freeze-thaw damage... When the number of freeze-thaw cycles and the extent of damage increase rapidly within a short period of time, The item is very large. It's very small; although the number of freeze-thaw cycles increases significantly in a short period, the rate of increase each time is not very large. The term corrects for the rate of loss increase for each instance, preventing extremely high damage degradation coefficients. It reflects the actual pattern that the accelerating effect of the same number of freeze-thaw cycles weakens as damage progresses. The term also measures the damage degradation coefficient caused by the number of freeze-thaw cycles that have occurred at time i of the monitoring period. , which represents the contribution of the freeze-thaw cycle in the i-th monitoring period to the accelerated deterioration of the lining freeze-thaw damage. The larger the value, the stronger the driving effect of the freeze-thaw cycle on the damage at that moment.

[0107] In this way, the damage deterioration coefficient can be determined based on the derivative of the damage comprehensive coefficient change function and the comprehensive coefficient of lining freeze-thaw damage. During the calculation process, the contribution of freeze-thaw cycles to the accelerated deterioration of lining freeze-thaw damage can be accurately assessed, thus improving the accuracy of the damage deterioration coefficient.

[0108] According to an embodiment of the present invention, in step S7, the final monitoring result is determined based on the damage deterioration coefficient, the lining freeze-thaw damage comprehensive coefficient, and the first monitoring result.

[0109] For example, the initial monitoring results are used to diagnose the damage mode and mechanism of the lining, providing the nature, location, and manifestation of the damage. This includes determining whether the damage mode is a high risk of through-cracking at the lining mortar joints or potential heaving or collapse of local lining slabs; whether the damage is caused by expansion of the canal foundation soil due to frost heave or by subsidence of the lining foundation after thawing of the canal foundation soil. The comprehensive freeze-thaw damage coefficient is used to determine the degree of damage to the lining after multiple freeze-thaw cycles. At this stage, the lining has suffered minor damage. The surface of the lining structure may have a very small number of micro-cracks or localized peeling. The overall structural integrity is good, and no obvious structural deformation has occurred. At this point, the freeze-thaw cycle has not yet caused significant damage to the lining, and the structural function is basically normal, not affecting normal use. However, there may already be a slight decrease in physical properties. Regular inspections are recommended to monitor for early changes. At this point, the lining has suffered moderate damage, with noticeable cracks appearing on the surface. The width and depth of these cracks have increased, and localized spalling or surface loosening may occur. The structural stiffness of the lining begins to decrease, possibly accompanied by uneven settlement or localized deformation, leading to abnormal stress distribution at the interface between the lining and the canal foundation soil. At this stage, the structural function is already affected, requiring increased monitoring frequency and consideration of reinforcement or localized repair measures to prevent further damage. When the lining suffers severe damage, with large-area cracks, through-cracks, or even localized fractures, its structural integrity is severely compromised, potentially leading to significant heave or collapse. At this point, the frost heave force between the lining and the foundation has caused structural instability, significantly increasing the risk of leakage and drastically reducing the structural load-bearing capacity, posing a safety hazard. It is imperative to immediately cease use and implement comprehensive repair or replacement. The damage deterioration coefficient is used to reflect the rate of damage development. As the damage continues to increase, the risk rises, indicating that the damage is accelerating. It is necessary to assign personnel to determine the cause of the accelerated damage to prevent irreversible risks from arising from the rapid increase in damage. When the damage remains stable or continues to decrease, it indicates that the damage development is stabilizing, and continuous monitoring is sufficient.

[0110] The method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing according to embodiments of the present invention can accurately collect multi-source physical data and lining data during the freeze-thaw cycle process, construct a disease pattern discrimination criterion, determine a first monitoring result based on the disease pattern discrimination criterion and multi-source physical data, and simultaneously assess the contribution of each influencing factor to the comprehensive coefficient of lining freeze-thaw damage based on the multi-source physical data and lining data, determine the comprehensive coefficient of lining freeze-thaw damage, and then determine the damage deterioration coefficient based on the comprehensive coefficient of lining freeze-thaw damage. Furthermore, based on the damage deterioration coefficient, the comprehensive coefficient of lining freeze-thaw damage, and the first monitoring result, the final monitoring result is comprehensively determined, thereby improving the accuracy and comprehensiveness of the monitoring results. When determining the comprehensive coefficient of freeze-thaw damage to linings, the following factors can be considered: the number of freeze-thaw cycles, the duration of a single freeze-thaw cycle, the maximum temperature difference during the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging attenuation rate of the lining material. During the calculation, the contributions of damage accumulation factors, frost heave force factors, and environmental-aging coupling factors to the comprehensive coefficient of freeze-thaw damage are comprehensively considered, thus improving the accuracy of the comprehensive coefficient. Similarly, when determining the damage deterioration coefficient, the derivative of the damage comprehensive coefficient change function and the comprehensive coefficient of freeze-thaw damage to linings can be used to determine the damage deterioration coefficient. During the calculation, the contribution of freeze-thaw cycles to the accelerated deterioration of freeze-thaw damage to the lining can be accurately assessed, further improving the accuracy of the damage deterioration coefficient.

[0111] Figure 5 An exemplary block diagram of a lining damage monitoring system based on multi-source physical sensing under freeze-thaw cycles according to an embodiment of the present invention is shown, the system comprising:

[0112] The physical data module is used to set up multi-type sensor arrays at key locations of the lining structure at multiple moments during the monitoring cycle to collect multi-source physical data in real time during the freeze-thaw cycle.

[0113] Lining data module, used to acquire lining data;

[0114] The discrimination criteria module is used to construct discrimination criteria for disease patterns;

[0115] The first result module is used to determine the first monitoring result based on the disease pattern discrimination criteria and the multi-source physical data;

[0116] The damage coefficient module is used to determine the comprehensive coefficient of freeze-thaw damage of the lining based on the multi-source physical data and the lining data.

[0117] The degradation coefficient module is used to determine the damage degradation coefficient based on the comprehensive coefficient of freeze-thaw damage of the lining.

[0118] The final result module is used to determine the final monitoring result based on the damage deterioration coefficient, the lining freeze-thaw damage comprehensive coefficient, and the first monitoring result.

[0119] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0120] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are merely examples and do not limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functions and structural principles of the present invention have been demonstrated and explained in the embodiments, and any variations or modifications may be made to the implementation of the present invention without departing from the stated principles.

Claims

1. A method for monitoring damage of lining under freeze-thaw cycles based on multi-source physical sensing, characterized in that, include: At multiple points during the monitoring cycle, multi-type sensor arrays are set up at key locations in the lining structure to collect multi-source physical data in real time during the freeze-thaw cycle. Obtain lining data; Establish criteria for disease pattern identification; Based on the disease pattern discrimination criteria and the multi-source physical data, the first monitoring result is determined; Based on the multi-source physical data and the lining data, the comprehensive coefficient of freeze-thaw damage of the lining is determined; The damage deterioration coefficient is determined based on the comprehensive coefficient of freeze-thaw damage of the lining. The final monitoring result is determined based on the damage deterioration coefficient, the comprehensive coefficient of freeze-thaw damage of the lining, and the first monitoring result.

2. The multi-source physical sensing based monitoring method of lining damage under freeze-thaw cycles according to claim 1, characterized in that, The multi-type sensor array includes a temperature sensor, a moisture sensor, an earth pressure sensor, and a displacement gauge. The temperature sensor and the moisture sensor are installed inside the canal foundation soil to monitor moisture migration and changes in frost depth. The earth pressure sensor is installed at the interface between the lower surface of the lining and the canal foundation soil to monitor normal frost heave force. The displacement gauge is installed on the surface of the lining plate to monitor the geometry of the entire lining section.

3. The multi-source physical sensing based monitoring method of lining damage under freeze-thaw cycles according to claim 1, characterized in that, Based on the disease pattern discrimination criteria and the multi-source physical data, the first monitoring result is determined, including: Based on the multi-source physical data, quantitative damage characterization indicators are determined; The first monitoring result is determined based on the quantitative damage characterization index and the disease pattern discrimination criterion.

4. The multi-source physical sensing based monitoring method of lining damage under freeze-thaw cycles according to claim 3, characterized in that, Based on the multi-source physical data, quantitative damage characterization indicators are determined, including: Based on the multi-source physical data, the initial bearing capacity value of the vulnerable part of the lining structure and the remaining bearing capacity value of the part after freeze-thaw cycles are determined. The first difference is determined based on the initial bearing capacity value and the remaining bearing capacity value; Based on the first difference and the initial bearing capacity value, a quantitative characterization index for damage is determined.

5. The multi-source physical sensing based monitoring method of lining damage under freeze-thaw cycles according to claim 1, characterized in that, Based on the multi-source physical data and the lining data, the comprehensive coefficient of freeze-thaw damage to the lining is determined, including: Obtain the number of freeze-thaw cycles that have occurred and the duration of a single freeze-thaw cycle; Based on the multi-source physical data, the maximum temperature difference during the freeze-thaw cycle and the real-time moisture migration per unit time are determined. Based on the multi-source physical data, the real-time maximum normal frost heave force, initial normal frost heave force, real-time maximum lining displacement, and initial lining displacement monitored during the freeze-thaw cycle were determined. Based on the lining data, the saturated moisture content of the lining material, the service time of the lining, and the aging and deterioration rate of the lining material are determined. The comprehensive coefficient of freeze-thaw damage to the lining is determined based on the number of freeze-thaw cycles that have occurred, the duration of a single freeze-thaw cycle, the maximum temperature difference during the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging and decay rate of the lining material.

6. The multi-source physical sensing based monitoring method of lining damage under freeze-thaw cycles according to claim 5, characterized in that, The comprehensive coefficient of freeze-thaw damage to the lining is determined based on the number of freeze-thaw cycles, the duration of a single freeze-thaw cycle, the maximum temperature difference during the freeze-thaw cycle, the real-time moisture migration per unit time, the real-time maximum normal frost heave force, the initial normal frost heave force, the real-time maximum lining displacement, the initial lining displacement, the saturated moisture content of the lining material, the lining service time, and the aging and decay rate of the lining material. This includes: according to the formula: Determine the comprehensive coefficient of lining freeze-thaw damage caused by the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period. ,in, , and To preset weights, To determine the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring period, The saturated moisture content of the lining material. The maximum normal frost heave force detected in the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. The initial normal frost heave force, This represents the real-time maximum lining displacement monitored during the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. This represents the initial lining displacement. The duration of a single freeze-thaw cycle is the number of freeze-thaw cycles that have occurred at time i in the monitoring cycle. This refers to the maximum temperature difference across freeze-thaw cycles monitored at the i-th moment of the monitoring cycle. This represents the real-time moisture migration per unit time within the number of freeze-thaw cycles that have occurred at the i-th moment of the monitoring cycle. The aging and degradation rate of the lining material. Let i be the lining usage time at the i-th moment of the monitoring cycle. This is the real-time water migration rate per unit time during the preset monitoring period. The maximum temperature difference during the freeze-thaw cycle of the preset monitoring period. The duration of a single freeze-thaw cycle is set for the preset monitoring period.

7. The method for monitoring lining damage under freeze-thaw cycles based on multi-source physical sensing according to claim 1, characterized in that, Based on the comprehensive coefficient of freeze-thaw damage to the lining, the damage deterioration coefficient is determined, including: Based on the comprehensive coefficient of freeze-thaw damage to the lining and the number of freeze-thaw cycles that have occurred, determine the function of the comprehensive coefficient of freeze-thaw damage to the lining as a function of the number of freeze-thaw cycles that have occurred. Differentiate the damage comprehensive coefficient change function to determine the derivative of the damage comprehensive coefficient change function; The damage deterioration coefficient is determined based on the derivative of the damage comprehensive coefficient change function and the lining freeze-thaw damage comprehensive coefficient.

8. The multi-source physical sensing based monitoring method of lining damage under freeze-thaw cycles according to claim 7, characterized in that, The damage deterioration coefficient is determined based on the derivative of the damage comprehensive coefficient change function and the lining freeze-thaw damage comprehensive coefficient, including: according to the formula: , the damage deterioration coefficient caused by the number of freeze-thaw cycles at the i th moment of the monitoring period is determined , wherein, is the derivative of the damage comprehensive coefficient change function, is the lining freeze-thaw damage comprehensive coefficient caused by the number of freeze-thaw cycles at the i th moment of the monitoring period.

9. A multi-source physical sensing based monitoring system for monitoring damage of lining under freeze-thaw cycles, characterized in that, For performing the method of any one of claims 1-8, comprising: The physical data module is used to set up multi-type sensor arrays at key locations of the lining structure at multiple moments during the monitoring cycle to collect multi-source physical data in real time during the freeze-thaw cycle. Lining data module, used to acquire lining data; The discrimination criteria module is used to construct discrimination criteria for disease patterns; The first result module is used to determine the first monitoring result based on the disease pattern discrimination criteria and the multi-source physical data; The damage coefficient module is used to determine the comprehensive coefficient of freeze-thaw damage of the lining based on the multi-source physical data and the lining data. The degradation coefficient module is used to determine the damage degradation coefficient based on the comprehensive coefficient of freeze-thaw damage of the lining. The final result module is used to determine the final monitoring result based on the damage deterioration coefficient, the lining freeze-thaw damage comprehensive coefficient, and the first monitoring result.

Images