Method for calibrating and measuring dry density and moisture content of soil body based on active heating optical fiber

Abstract

The invention relates to a soil dry density and moisture content calibration and measurement method and device based on an active heating optical fiber, computer equipment and a computer readable storage medium. The method comprises the following steps: configuring first test soil samples with specified dry densities and different mass moisture contents; obtaining temperature characteristic values of the first test soil samples under the conditions of specified dry density and different mass moisture contents; fitting a temperature characteristic value-mass moisture content calibration formula; respectively heating and testing the second test soil samples with different mass moisture contents under different dry density conditions to obtain a temperature characteristic value-mass moisture content calibration formula under different dry density conditions; establishing a calibration correction model which simultaneously considers two parameters of dry density and mass moisture content; and obtaining the dry density or the mass moisture content of the to-be-detected soil body. By adopting the method, the limitation that a traditional model is only suitable for a single dry density condition can be broken through, and accurate measurement on the in-situ soil body under different dry density and mass moisture content conditions is realized.

Description

Technical Field

[0001] The present application relates to the field of geotechnical engineering and geological engineering technology, and in particular to a soil dry density and moisture content calibration and measurement method, device, computer equipment and computer-readable storage medium based on active heating optical fiber. Background Art

[0002] Soil moisture field is one of the important physical fields in geological geotechnical engineering and agricultural ecological environment, and is of great significance to the study of soil ecological characteristics and engineering performance. As the core indicator of soil moisture status, accurate measurement of moisture content is crucial. Understanding the distribution law of moisture content is the key to exploring the mechanism of water migration and storage in soil.

[0003] In recent years, the moisture content measurement method based on the active heating fiber optic (AHFO) method has attracted wide attention due to its advantages such as small size, anti-interference, long distance, distribution and strong durability. It has been successfully applied in the field of engineering geology. The active heating method is to bury the optical fiber with internal heating function into the soil. After the power is turned on and heated, the heat will be conducted and diffused to the surrounding soil. The moisture content of the soil is calculated by the temperature characteristic value measured by the optical fiber. The core is to establish a calibration model between the temperature characteristic value and the moisture content. At present, most of these models are established under the condition that the dry density is basically unchanged. However, in practical applications, due to the complex field conditions, the dry density of soil in different landforms and different depths is different. The difference in dry density will not only change the thermal parameters of the soil, but also may affect the relationship between the temperature characteristic value and the moisture content, which may greatly affect the measurement accuracy. Therefore, it is necessary to consider the influence of the soil dry density on the calibration model, correct the calibration model, and improve the measurement accuracy of the in-situ soil. It is of great practical significance. Summary of the invention

[0004] Based on this, it is necessary to provide a soil dry density and moisture content calibration and measurement method, device, computer equipment and computer-readable storage medium based on active heating optical fiber to address the above technical problems, which can solve the error problem caused by ignoring the difference in soil dry density in the traditional technology and causing the calibration model to have a high-precision and distributed measurement of the in-situ soil under the conditions of changing dry density and mass moisture content.

[0005] In a first aspect, the present application provides a soil dry density and moisture content calibration and measurement method based on active heating optical fiber, the method is used to obtain the dry density or mass moisture content of the soil to be measured, including:

[0006] Step S1, configuring first test soil samples with specified dry density and different mass moisture contents;

[0007] Step S2, burying an active heating type optical fiber sensor in each first test soil sample, heating it with a specified heating power, and obtaining a temperature characteristic value of each first test soil sample under conditions of a specified dry density and different mass moisture contents;

[0008] Step S3, fitting a temperature characteristic value-mass moisture content calibration formula according to the temperature characteristic values ​​and different mass moisture contents obtained in steps S1 and S2;

[0009] Step S4, for each first test soil sample, the automatic compaction device sequentially changes the height of each first test soil sample to obtain each second test soil sample with different mass moisture content under different dry density conditions;

[0010] Step S5, performing heating tests on the second test soil samples with different mass moisture contents under different dry density conditions obtained in step S4, and obtaining a temperature characteristic value-mass moisture content calibration formula under different dry density conditions;

[0011] Step S6, according to the variation law of the target parameter with dry density in the temperature characteristic value-mass moisture content calibration formula obtained in step S5, a calibration correction model that considers both dry density and mass moisture content is established;

[0012] Step S7, obtaining the dry density or mass moisture content of the soil to be tested; when obtaining the dry density of the soil to be tested, measuring the temperature characteristic value by the active heating method, and substituting the temperature characteristic value into the calibration correction model to obtain the long-term change law of the mass moisture content of the soil to be tested; when obtaining the mass moisture content of the soil to be tested, measuring the temperature characteristic value by the active heating method, and substituting the temperature characteristic value into the calibration correction model to obtain the long-term change law of the mass dry density of the soil to be tested.

[0013] In one embodiment, the temperature characteristic value of each first test soil sample under the conditions of specified dry density and different mass moisture content in step S2 is as follows:

[0014]

[0015] Where, T t is the temperature characteristic value, in °C; T(t) is the sensor temperature corresponding to the heating time t, in °C; T0 is the initial ambient temperature, in °C; Q is the heating power per unit length, in Wm -1 ; λ is the thermal conductivity of the soil, in W m -1 K -1 ; R is the thermal resistance between the sensor and the soil wall per unit length, in m KW -1 ; K is the thermal diffusion coefficient of the soil, in m 2 s -1; a is the outer diameter of the sensor, in m; c = 1.7811 = exp(γ) and γ = 0.5772, γ is the Euler constant.

[0016] In one embodiment, fitting the temperature characteristic value-mass moisture content calibration formula in step S3 includes:

[0017] use The Konrad calibration model fits the following temperature characteristic value-mass moisture content calibration formula:

[0018]

[0019] in, A, B, and C are all target parameters; where κ is an empirical parameter determined according to soil type and freezing state; n is porosity; λ sat is the saturated thermal conductivity; dry is the dry thermal conductivity; ρ d is the dry density in g / cm 3 ρ w is the density of water in g / cm 3 .

[0020] In one embodiment, the temperature characteristic value-mass moisture content calibration formula obtained under different dry density conditions in step S5 is as follows:

[0021]

[0022] In the formula, A1, B1, and C are all constants.

[0023] In one embodiment, establishing a calibration correction model that considers both dry density and mass moisture content in step S6 includes:

[0024] Step S601, based on and Konrad calibration model concluded that the dry density is inversely proportional to the target parameter in the calibration formula;

[0025] Step S602, substituting the target parameters in the temperature characteristic value-mass moisture content calibration formula obtained when the dry density of the second test soil sample is the first preset value into the temperature characteristic value-mass moisture content calibration formula obtained when the dry density of the second test soil sample is the second preset value, and analyzing the influence of the target parameters on the mass moisture content calibration result;

[0026] Step S603, based on the analysis result of the influence of the target parameter on the mass moisture content calibration result obtained in step S602, a method of simultaneously considering dry density and mass moisture content is proposed. and Konrad calibration correction model, as follows:

[0027]

[0028] Where A2, B2 and C2 are temperature characteristic values ​​T t With mass moisture content w, dry density ρ d The fitting parameters of .

[0029] In one embodiment, step S7 includes:

[0030] Step 701, performing a heating test on a soil body to be tested with a known dry density or mass moisture content;

[0031] Step 702, measuring the temperature characteristic value by active heating method, substituting the temperature characteristic value into the calibration correction model, and obtaining the long-term variation law of mass moisture content or dry density.

[0032] In one embodiment, the method further comprises:

[0033] When the mass moisture content remains unchanged, the calibration correction model can be simplified into the following expression:

[0034]

[0035] In the formula, and B d =C2 is the fitting parameter.

[0036] In a second aspect, the present application also provides a soil dry density and moisture content calibration and measurement device based on active heating optical fiber, comprising:

[0037] A test soil sample configuration module, used for configuring each first test soil sample with a specified dry density and different mass moisture content;

[0038] A heating test module is used to bury an active heating type optical fiber sensor in each first test soil sample, and obtain a temperature characteristic value of each first test soil sample under conditions of a specified dry density and different mass moisture contents after heating with a specified heating power;

[0039] The calibration formula fitting module is used to fit the temperature characteristic value-mass moisture content calibration formula according to the temperature characteristic value and different mass moisture contents obtained by the test soil sample configuration module and the heating test module;

[0040] A dry density adjustment module is used to change the height of each first test soil sample in turn by an automatic compaction device for each first test soil sample, so as to obtain each second test soil sample with different mass moisture content under different dry density conditions;

[0041] A fitting module for different dry density calibration formulas is used to perform heating tests on the second test soil samples with different mass moisture contents under different dry density conditions obtained in the dry density adjustment module, and obtain temperature characteristic value-mass moisture content calibration formulas under different dry density conditions;

[0042] The calibration correction model establishment module is used to establish a calibration correction model that considers both dry density and mass moisture content according to the variation law of the target parameter in the temperature characteristic value-mass moisture content calibration formula obtained by the different dry density calibration formula fitting modules with the dry density;

[0043] The calibration correction model calling module is used to obtain the dry density or mass moisture content of the soil to be tested; when obtaining the dry density of the soil to be tested, the temperature characteristic value is measured by the active heating method, and the temperature characteristic value is substituted into the calibration correction model to obtain the long-term change law of the mass moisture content of the soil to be tested; when obtaining the mass moisture content of the soil to be tested, the temperature characteristic value is measured by the active heating method, and the temperature characteristic value is substituted into the calibration correction model to obtain the long-term change law of the mass dry density of the soil to be tested.

[0044] In a third aspect, the present application also provides a computer device including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps of a soil dry density and moisture content calibration and measurement method based on active heating optical fiber.

[0045] In a fourth aspect, the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a soil dry density and moisture content calibration and measurement method based on active heating optical fiber.

[0046] The above-mentioned soil dry density and moisture content calibration and measurement method, device, computer equipment and computer-readable storage medium based on active heating optical fiber, compared with traditional technology, have the following advantages: the present application proposes a correction model that simultaneously considers the two key factors of dry density and mass moisture content, breaking through the limitation that the traditional model is only applicable to a single dry density condition, and realizes the accurate measurement of in-situ soil under different dry density and mass moisture content conditions; the present application is not only applicable to surface soil, but also to soil at different depths and different landform conditions, meeting the high-precision monitoring requirements of in-situ soil under complex geological conditions, and has wide applicability; the present application requires few parameters, only the dry density and mass moisture content of the soil at the depth need to be corrected, and the process of determining thermal resistance and correcting moisture content is simple; the present application is economical and safe, easy to operate, strong in anti-interference ability, and reliable and effective in accuracy; the active heating optical fiber used in the present application has high durability, low equipment maintenance cost, and is suitable for long-term monitoring needs; the present application helps to improve the accuracy of active heating optical fiber technology in in-situ soil moisture content measurement and promote the promotion and application of this technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic flow chart of a method for calibrating and measuring soil dry density and moisture content based on active heating optical fiber in one embodiment;

[0048] Figure 2 It is a flow chart of a soil dry density and moisture content calibration and measurement method based on active heating optical fiber in one embodiment;

[0049] Figure 3 The present invention is a test device for a soil dry density and moisture content calibration and measurement method based on active heating optical fiber in one embodiment; wherein 1 is an AH-FBG corundum tube sensor, 2 is an FBG demodulator, 3 is a DC power supply, 4 is a computer, 5 is a soil sample, 6 is an automatic compaction device, 7 is a plastic film, and 8 is a hole;

[0050] Figure 4 In one embodiment, the dry density is different and Konrad calibration model fitting results;

[0051] Figure 5 The effect of three parameters A, B and C on the water content calibration result under Q = 35W / m, t = 20min in an embodiment;

[0052] Figure 6(a) shows an example of an embodiment when Q = 35 W / m, t = 20 min and Konrad calibration correction model results and Comparison chart of Konrad model fitting results;

[0053] Figure 6(b) shows an example of an embodiment when Q = 10 W / m, t = 10 min and Konrad calibration correction model results and Comparison chart of Konrad model fitting results;

[0054] Figure 7 is the temperature characteristic value (T t ) and dry density (ρ d ) of the fitting results. DETAILED DESCRIPTION

[0055] At present, the in-situ measurement technologies for soil moisture content mainly include time domain reflectometry (TDR), frequency domain reflectometry (FDR), capacitance method and neutron method. These methods show good accuracy and efficiency in point measurement, but the limitations of these methods are also very obvious, and it is difficult to achieve distributed measurement of soil over a large range and at a certain depth; in addition, remote sensing, infrared thermal imaging, ultrasound, resistivity tomography and ground penetrating radar, although they can obtain the distribution of moisture content over a large range on the surface, have low measurement accuracy, limited spatial resolution, and high equipment cost, which makes it difficult to meet the needs of deep underground and large-scale applications.

[0056] The present application discloses a soil dry density and moisture content calibration and measurement method based on active heating optical fiber. d The soil samples were pre-treated with different moisture contents w and then calibrated to obtain the temperature characteristic value T t , fitting T t –w calibration formula, the automatic compaction device changes the soil height in sequence to obtain different dry densities ρ d The soil samples with different moisture contents were heated and tested for a constant dry density soil sample to obtain different dry densities ρ d Lower T t –w calibration formula; according to the change law of parameters A, B, C with dry density, establish a method that takes into account dry density ρ d and mass moisture content w and Konrad calibration correction model. In practical applications, for any one of the parameters (dry density ρ d or mass moisture content w) of in-situ soil, T measured by active heating method t, and substitute it into the calibration correction model, so as to monitor the long-term variation of another parameter. The method of the present invention is applicable to in-situ soil bodies with different depths, different landforms and large dry density changes. The influence of dry density on the measurement results is taken into account, and the measurement error of the active heating optical fiber sensor can be significantly reduced, and the accuracy of in-situ soil measurement can be improved.

[0057] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0058] In an exemplary embodiment, Figure 1 As shown in the figure, a soil dry density and moisture content calibration and measurement method based on active heating optical fiber is provided. For the soil to be measured, the following steps S1 to S7 are performed to calculate the dry density (ρ d ) or mass moisture content (w) parameters, including:

[0059] Step S1, configuring first test soil samples with specified dry density and different mass moisture contents;

[0060] Exemplarily, a constant dry density ρ is configured d The soil samples are pretreated with different mass moisture contents w to obtain the first test soil samples.

[0061] Step S2, burying an active heating type optical fiber sensor in each first test soil sample, heating it with a specified heating power, and obtaining a temperature characteristic value of each first test soil sample under conditions of a specified dry density and different mass moisture contents;

[0062] For example, an active heating type optical fiber sensor is buried in a soil sample to be tested (i.e., each first test soil sample), and is heated for a certain period of time with a heating power Q to obtain a constant dry density ρ d and temperature characteristic value T under different mass water content w t .

[0063] Step S3, fitting a temperature characteristic value-mass moisture content calibration formula according to the temperature characteristic values ​​and different mass moisture contents obtained in steps S1 and S2;

[0064] For example, according to the temperature characteristic value T obtained in step S1 and step S2 t and mass moisture content w, fitting T t –w calibration formula.

[0065] Step S4, for each first test soil sample, the automatic compaction device sequentially changes the height of each first test soil sample to obtain each second test soil sample with different mass moisture content under different dry density conditions;

[0066] Exemplarily, the soil height of each first test soil sample is changed in sequence by the automatic compaction device to obtain different dry densities ρ d , and then get different dry densities ρ d The second test soil samples with each mass moisture content w under the conditions.

[0067] Step S5, performing heating tests on the second test soil samples with different mass moisture contents under different dry density conditions obtained in step S4, and obtaining a temperature characteristic value-mass moisture content calibration formula under different dry density conditions;

[0068] Exemplarily, the soil samples obtained in step S4, i.e., each second test soil sample, for a constant dry density ρ d The soil sample was heated and the T t –w calibration results, repeat the above heating process for each second test soil sample at different heights to obtain different dry densities ρ d Lower T t –w calibration formula.

[0069] Step S6, according to the variation law of the target parameter with dry density in the temperature characteristic value-mass moisture content calibration formula obtained in step S5, a calibration correction model that considers both dry density and mass moisture content is established;

[0070] For example, according to the calibration formula obtained in step S5, according to the variation law of parameters A, B, and C with dry density, a calibration formula that takes into account dry density (ρ d ) and moisture content (w) and Konrad calibration correction model.

[0071] Step S7, obtaining the dry density or mass moisture content of the soil to be measured; in the case of obtaining the dry density of the soil to be measured, measuring the temperature characteristic value by the active heating method, and substituting the temperature characteristic value into the calibration correction model to obtain the long-term change law of the mass moisture content of the soil to be measured; in the case of obtaining the mass moisture content of the soil to be measured, measuring the temperature characteristic value by the active heating method, and substituting the temperature characteristic value into the calibration correction model to obtain the long-term change law of the mass dry density of the soil to be measured;

[0072] For example, according to the calibration correction model established in step S6, in practical applications, for any one of the parameters (dry density ρ d and mass moisture content w), i.e., the soil to be tested, is measured by the active heating method. t, and substitute it into the calibration correction model, so that the long-term variation law of another parameter can be monitored.

[0073] In an exemplary embodiment, in step S2, the temperature characteristic value of each first test soil sample under the conditions of dry density and different mass moisture content is specified, that is, T in step S2 t The expression is as follows:

[0074]

[0075] Where, T t is the temperature characteristic value, in °C; T(t) is the sensor temperature corresponding to the heating time t, in °C; T0 is the initial ambient temperature, in °C; Q is the heating power per unit length, in Wm -1 ; λ is the thermal conductivity of the soil, in Wm -1 K -1 ; R is the thermal resistance between the FBG (Fiber Bragg Grating) corundum tube sensor and the soil wall per unit length, in mKW -1 ; K is the thermal diffusion coefficient of the soil, in m 2 s -1 ; α is the outer diameter of the sensor, in m; c = 1.7811 = exp(γ) and γ = 0.5772, γ is the Euler constant.

[0076] In an exemplary embodiment, fitting the temperature characteristic value-mass moisture content calibration formula in step S3 includes:

[0077] by The Tt–w calibration formula is fitted by the Konrad model as follows:

[0078]

[0079] in, A, B, and C are all target parameters; where κ is an empirical parameter related to soil type and freezing state; n is porosity; λ sat is the saturated thermal conductivity; dry is the dry thermal conductivity; ρ d is the dry density in g / cm 3 ρ w is the density of water in g / cm 3 .

[0080] In an exemplary embodiment, different dry densities ρ are obtained in step S5. d Temperature characteristic value T under the condition t -The calibration formula of mass moisture content w is as follows:

[0081]

[0082] In the formula, A1, B1, and C are all constants.

[0083] In an exemplary embodiment, in step S6, a calibration correction model considering both dry density and mass moisture content is established, that is, a calibration correction model considering both dry density (ρ d ) and moisture content (w) The specific steps of the Konrad calibration correction model include:

[0084] Step S601, based on and Konrad calibration model concluded that the dry density is inversely proportional to the target parameter in the calibration formula;

[0085] Specifically, according to and Konrad calibration model, we know that as the dry density ρ d As the value increases, the parameters A, B, and C in the calibration formula decrease continuously, and their changes are affected by the soil dry density ρ d significant impact.

[0086] Step S602, substituting the target parameters in the temperature characteristic value-mass moisture content calibration formula obtained when the dry density of the second test soil sample is the first preset value into the temperature characteristic value-mass moisture content calibration formula obtained when the dry density of the second test soil sample is the second preset value, and analyzing the influence of the target parameters on the mass moisture content calibration result;

[0087] Specifically, the dry density is 1.2 g / cm 3 The parameters of the first preset value are respectively substituted into the dry density 1.5g / cm 3 (i.e., the second preset value) is calibrated by analyzing the effect of calibration parameters A, B, and C on the water content calibration result T t The influence of parameter A on T of medium and high moisture content (>4%) is analyzed and the following conclusions are drawn: parameter A significantly affects T of medium and high moisture content (>4%). t ; Parameter C for low moisture content (<4%) T t The impact is greater, and its impact exceeds that of A; parameter B has a smaller impact and can be ignored.

[0088] Step S603, based on the analysis in step S602, it is proposed to simultaneously consider the dry density ρ d and the calibration model of mass moisture content w, namely and Konrad calibration correction model:

[0089]

[0090] Where A2, B2 and C2 are temperature characteristic values ​​T t With mass moisture content w, dry density ρ d The fitting parameters of .

[0091] In an exemplary embodiment, step S7 in actual application specifically includes the following steps:

[0092] Step 701, performing a heating test on a soil body to be tested with a known dry density or mass moisture content;

[0093] For example, for any known parameter (dry density ρ d Or mass moisture content w) of the in-situ soil (i.e. the soil to be tested) is heated.

[0094] Step 702, measuring the temperature characteristic value by an active heating method, substituting the temperature characteristic value into a calibration correction model, and obtaining the long-term variation law of the mass moisture content or dry density;

[0095] For example, T measured by active heating method t , substituting it into the calibration correction model, we can get another parameter (mass moisture content w or dry density ρ d ).

[0096] In an exemplary embodiment, when the mass water content w is constant, the calibration correction model can be simplified to T t -ρ d expression:

[0097]

[0098] In the formula, and B d =C2 is the fitting parameter.

[0099] like Figure 2 As shown, the present application designs a soil dry density and moisture content calibration and measurement method based on active heating optical fiber. For the soil to be measured, the following steps S1 to S7 are performed to obtain the dry density ρ d and mass moisture content w and Konrad calibration correction model, the dry density of the soil to be tested (ρ d ) or mass moisture content (w):

[0100] Step S1, configure constant dry density ρ d The soil samples were pre-treated with different mass moisture contents w and then subjected to calibration experiments;

[0101] Step S2: bury the active heating type optical fiber sensor in the soil sample to be tested, and heat it with heating power Q for a certain time to obtain a constant dry density ρ d and temperature characteristic value T under different mass water content w t , that is, the temperature characteristic value T t ;

[0102] Step S3, based on the T obtained in step S1 and step S2 t and w, fitting T t –w calibration formula;

[0103] Step S4, the automatic compaction device changes the soil height in sequence to obtain different dry densities ρ d , and then get different dry densities ρ d Soil samples with various mass moisture content w under the conditions;

[0104] Step S5, according to the soil samples obtained in step S4, respectively, a constant dry density ρ d The soil samples were heated and tested to obtain different dry densities ρ d Lower T t –w calibration formula;

[0105] Step S6, according to the calibration formula obtained in step S5, according to the parameters A, B, C in the formula with the dry density ρ d The change law of the dry density (ρ d ) and moisture content (w) and Konrad calibration correction model;

[0106] Step S7, according to the calibration correction model established in step S6, in practical application, for any one of the parameters (dry density ρ d or mass moisture content w) of in-situ soil, T measured by active heating method t , and substitute it into the calibration correction model, so that the long-term variation law of another parameter can be monitored.

[0107] The present invention provides a soil dry density and moisture content calibration and measurement method based on active heating optical fiber. The test device refers to Figure 3The AH-FBG corundum tube sensor 1 is inserted into a constant soil sample 5 treated with different moisture contents. The automatic compaction device 6 forms soil samples with different dry densities by changing the height of the soil. The AH-FBG corundum tube sensor 1 can move up and down at the hole 8. The cable and optical cable of the AH-FBG corundum tube are respectively connected to the FBG demodulator 2 and the DC power supply 3. The FBG demodulator 2 is connected to the computer 4 and controlled by the demodulation software on the computer 4. After the heating test, the temperature data of the soil sample collected by the FBG demodulator 2 is transmitted to the computer 4 for recording.

[0108] Still refer to Figure 2 , for the soil to be tested, execute the following steps S1 to S7 to calculate the dry density or mass moisture content of the soil to be tested:

[0109] Step S1, configure constant dry density ρ d Soil samples were pretreated with different mass moisture contents w;

[0110] Step S2: bury the active heating type optical fiber sensor in the soil sample to be tested, and heat it with heating power Q for a certain time to obtain a constant dry density ρ d and temperature characteristic value T under different mass water content w t ;

[0111] T in step S2 t The expression is as follows:

[0112]

[0113] Where, T t is the temperature characteristic value (℃), T(t) is the sensor temperature corresponding to the heating time t (℃), T0 is the initial ambient temperature (℃), Q is the heating power per unit length (W m -1 ), λ is the thermal conductivity of the soil (W m -1 K -1 ), R is the thermal resistance between the FBG corundum tube sensor and the soil wall per unit length (m KW -1 ), K is the thermal diffusion coefficient of the soil (m 2 s -1 ), a is the outer diameter of the sensor (m), c = 1.7811 = exp(γ) and γ = 0.5772, γ is the Euler constant.

[0114] Step S3, based on the T obtained in step S1 and step S2 t and w, fitting T t –w calibration formula;

[0115] In step S3, and Konrad model to fit Tt The –w calibration formula is as follows:

[0116]

[0117] in, In the formula, κ is an empirical parameter that is related to soil type and freezing state, n is porosity, and λ is sat is the saturated thermal conductivity, λ dry is the dry thermal conductivity, ρ d is the dry density (g / cm 3 ), ρ w is the density of water (g / cm 3 ).

[0118] Step S4, the automatic compaction device changes the soil height in sequence to obtain different dry densities ρ d , and then get different dry densities ρ d Soil samples with various mass moisture content w under the conditions;

[0119] Step S5, based on the soil sample obtained in step S4, for a certain constant dry density ρ d The soil sample was heated and the T t –w calibration results, repeat the above heating process for soil samples at different heights to obtain different dry densities ρ d Lower T t –w calibration formula;

[0120] In step S5, the dry density under different conditions ρ d Lower T t The –w calibration formula is as follows:

[0121]

[0122] In the formula, A, B, and C are all constants.

[0123] Step S6, according to the calibration formula obtained in step S5, according to the change law of parameters A, B, C with dry density, establish a calibration formula that takes into account dry density (ρ d ) and moisture content (w) and Konrad calibration correction model;

[0124] It is proposed to consider the dry density ρ d and mass moisture content w The Konrad calibration correction model is as follows:

[0125]

[0126] Where A2, B2 and C2 are temperature characteristic values ​​T t With mass moisture content w, dry density ρ d The fitting parameters of .

[0127] Step S7, according to the calibration correction model established in step S6, in practical application, for any one of the parameters (dry density ρ d and mass moisture content w) of the in-situ soil, T measured by the active heating method t , and substitute it into the calibration correction model, so that the long-term change law of another parameter can be monitored. The specific steps are as follows:

[0128] Step S701: for any known parameter (dry density ρ d or mass moisture content w) for heating test;

[0129] Step S702, T measured by active heating method t , substituting it into the calibration correction model, we can get another parameter (mass moisture content w or dry density ρ d ).

[0130] The following is an application example of a soil dry density and moisture content calibration and measurement method based on active heating optical fiber designed by the present invention.

[0131] In one embodiment, an indoor test using the method and hardware device of the present invention to monitor soils with different dry densities and mass moisture contents includes:

[0132] Step 1: Prepare soil samples of a constant dry density with different mass moisture contents. The specific steps are as follows:

[0133] (1) preparing first test soil samples having a mass moisture content of 0 g / g, 0.04 g / g, 0.08 g / g, 0.12 g / g, 0.16 g / g, 0.20 g / g, 0.24 g / g, 0.28 g / g, and 0.32 g / g;

[0134] (2) Control the dry density of the first test soil sample at each moisture content to be 1.2 g / cm 3 ;

[0135] (3) The first test soil samples prepared in step (2) are compacted and filled in layers into a 20 cm×15 cm×20 cm test box (a 20 cm×20 cm test box has a hole on one side).

[0136] Step 2: slowly insert the AH-FBG corundum tube sensor with a length of 15 cm and a diameter of 6 mm into the soil sample of the test box configured in step 1 along the hole on the test box;

[0137] Step 3: 1.2 g / cm 3 The soil samples with the moisture content of 0g / g, 0.04g / g, 0.08g / g, 0.12g / g, 0.16g / g, 0.20g / g, 0.24g / g, 0.28g / g, and 0.32g / g were heated and tested with the heating parameters of 35W / m and 20min. t value, fitting the T t –w calibration formula;

[0138] Step 4: Then use the automatic compaction device to compact to the next constant dry density, and repeat step 3 until all dry densities are measured (increase 0.1g / cm each time). 3 , from 1.2g / cm 3 Up to 1.6g / cm 3 ), and obtain different dry densities ρ d Lower T t –w calibration formula, obtain Figure 4 At different dry densities shown From the fitting result diagram of the Konrad calibration model, we can see that there are differences in the calibration results under different soil dry densities, especially when the dry density is small; as the dry density increases, the difference in the calibration results becomes smaller.

[0139] Step 5: The parameters A, B, and C in the formula increase with the increase of dry density. 3 Substitute the three parameters of 1.5g / cm separately 3 The comparison results are shown in the calibration formula of Figure 5 A and C have a greater impact on the calibration results, among which A mainly affects T t , C mainly affects T at low moisture content t , while parameter B has little effect. A method considering dry density and mass moisture content is proposed. and Konrad calibration correction model:

[0140]

[0141] Where A2, B2 and C2 are temperature characteristic values ​​(T t ) and mass moisture content (w), dry density (ρ d )’s fitting parameters.

[0142] Furthermore, in order to compare with the calibration model without considering the dry density, the above formula can be rearranged as follows:

[0143]

[0144] Calculate T from the fitting results t , so we can get and Konrad calibration correction model T t The fitting results of θ are compared in Figure 6(a) when Q = 35 W / m and t = 20 min. and Konrad calibration correction model results and and Konrad model fitting results, Figure 6(b) compares the results when Q = 10 W / m, t = 10 min and Konrad calibration correction model results and and Konrad model fitting results. It can be seen that Compared with the Konrad model, and Konrad calibration correction model can more realistically describe T t -θ relationship, and has better fitting results at low water content, R 2 is 0.974. Overall, The Konrad calibration correction model can better reflect the influence of dry density on the calibration results, which proves that the calibration correction model has good applicability.

[0145] In one embodiment, the method of the present invention is applied to perform a feasibility test, including:

[0146] Step 1, The Konrad calibration correction model takes into account the two parameters of mass moisture content and dry density. Therefore, the model can not only describe the changes of moisture content and temperature characteristic values, but also the changes of dry density and temperature characteristic values. When the mass moisture content remains unchanged, the temperature characteristic value changes with the dry density;

[0147] Step 2: Arrange the calibration correction model into T t -ρ d expression:

[0148]

[0149] In the formula, and B d =C2 is the fitting parameter.

[0150] Step 3: Perform a heating test under the heating parameter conditions of 35W / m and 20min. The specific steps are as follows:

[0151] (1) Prepare soil samples with mass moisture contents of 0 g / g, 0.04 g / g, 0.08 g / g, 0.12 g / g, and 0.21 g / g respectively;

[0152] (2) The dry density of each soil sample with different moisture content is controlled to be 1.2 g / cm 3 ;

[0153] (3) The soil samples prepared in step (2) are compacted and filled in layers into a 20 cm × 15 cm × 20 cm test box (a hole is opened on one side of the 20 cm × 20 cm box);

[0154] (4) Slowly insert the AH-FBG corundum tube sensor with a length of 15 cm and a diameter of 6 mm into the soil sample of the test box filled in step (3) along the hole on the test box;

[0155] (5) Conduct heating test;

[0156] (6) The dry density of each soil sample with different moisture content is changed to 1.3 g / cm by the automatic compaction device. 3 , 1.4g / cm 3 , 1.5g / cm 3 , 1.6g / cm 3 Afterwards, heat tests were performed separately.

[0157] Step 4: Get Figure 7 Temperature characteristic value (T t ) and dry density (ρ d ). It can be seen that T t With ρ d The greater the dry density of the soil, the more solid matter is contained in the unit volume of the soil, the denser the arrangement of the soil particles, the greater the contact area between the particles, the greater the thermal conductivity of the soil, and finally the T t The smaller the soil moisture content, the lower the T t The more sensitive it is to the change of dry density; when the soil moisture content is 0.21g / g, T t It is basically unaffected by dry density. In addition, the calibration correction model has a good effect in fitting the measured data. Except for the soil sample with a moisture content of 0.12g / g, the fitting coefficients of the other moisture content soil samples are all greater than 0.85, and the fitting coefficient in dry soil is as high as 0.97. This shows andKonrad calibration correction model can not only describe T t -w relationship, can also describe T t -ρ d relationship, so the model is feasible.

[0158] At least a portion of the steps in the flowcharts involved in the embodiments described above may include multiple steps or multiple stages. These steps or stages may be executed at different times, or may be executed in turn or alternation with other steps or at least a portion of the steps or stages in other steps.

[0159] Based on the same inventive concept, the embodiment of the present application also provides a soil dry density and moisture content calibration and measurement device based on active heating optical fiber for realizing the soil dry density and moisture content calibration and measurement method based on active heating optical fiber. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the soil dry density and moisture content calibration and measurement device based on active heating optical fiber provided below can refer to the limitations of the soil dry density and moisture content calibration and measurement method based on active heating optical fiber above, and will not be repeated here.

[0160] In an exemplary embodiment, a soil dry density and moisture content calibration and measurement device based on active heating optical fiber is provided, comprising:

[0161] A test soil sample configuration module, used for configuring each first test soil sample with a specified dry density and different mass moisture content;

[0162] A heating test module is used to bury an active heating type optical fiber sensor in each first test soil sample, and obtain a temperature characteristic value of each first test soil sample under conditions of a specified dry density and different mass moisture contents after heating with a specified heating power;

[0163] The calibration formula fitting module is used to fit the temperature characteristic value-mass moisture content calibration formula according to the temperature characteristic value and different mass moisture contents obtained by the test soil sample configuration module and the heating test module;

[0164] A dry density adjustment module is used to change the height of each first test soil sample in turn by an automatic compaction device for each first test soil sample, so as to obtain each second test soil sample with different mass moisture content under different dry density conditions;

[0165] A fitting module for different dry density calibration formulas is used to perform heating tests on the second test soil samples with different mass moisture contents under different dry density conditions obtained in the dry density adjustment module, and obtain temperature characteristic value-mass moisture content calibration formulas under different dry density conditions;

[0166] The calibration correction model establishment module is used to establish a calibration correction model that considers both dry density and mass moisture content according to the variation law of the target parameter in the temperature characteristic value-mass moisture content calibration formula obtained by the different dry density calibration formula fitting modules with the dry density;

[0167] The calibration correction model calling module is used to obtain the dry density or mass moisture content of the soil to be tested; when obtaining the dry density of the soil to be tested, the temperature characteristic value is measured by the active heating method, and the temperature characteristic value is substituted into the calibration correction model to obtain the long-term change law of the mass moisture content of the soil to be tested; when obtaining the mass moisture content of the soil to be tested, the temperature characteristic value is measured by the active heating method, and the temperature characteristic value is substituted into the calibration correction model to obtain the long-term change law of the mass dry density of the soil to be tested.

[0168] Each module in the soil dry density and moisture content calibration and measurement device based on active heating optical fiber can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0169] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0170] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0171] For those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, and these modifications and improvements are all within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A soil dry density and moisture content calibration and measurement method based on active heating optical fiber, characterized in that: The method is used to obtain the dry density or mass moisture content of the soil to be tested, and comprises: Step S1, configuring first test soil samples with specified dry density and different mass moisture contents; Step S2, burying an active heating type optical fiber sensor in each first test soil sample, heating it with a specified heating power, and obtaining a temperature characteristic value of each first test soil sample under conditions of a specified dry density and different mass moisture contents; Step S3, fitting a temperature characteristic value-mass moisture content calibration formula according to the temperature characteristic values ​​and different mass moisture contents obtained in steps S1 and S2; Step S4, for each first test soil sample, the automatic compaction device sequentially changes the height of each first test soil sample to obtain each second test soil sample with different mass moisture content under different dry density conditions; Step S5, performing heating tests on the second test soil samples with different mass moisture contents under different dry density conditions obtained in step S4, and obtaining a temperature characteristic value-mass moisture content calibration formula under different dry density conditions; Step S6, according to the variation law of the target parameter with dry density in the temperature characteristic value-mass moisture content calibration formula obtained in step S5, a calibration correction model that considers both dry density and mass moisture content is established; Step S7, obtaining the dry density or mass moisture content of the soil to be tested; when obtaining the dry density of the soil to be tested, measuring the temperature characteristic value by the active heating method, and substituting the temperature characteristic value into the calibration correction model to obtain the long-term change law of the mass moisture content of the soil to be tested; when obtaining the mass moisture content of the soil to be tested, measuring the temperature characteristic value by the active heating method, and substituting the temperature characteristic value into the calibration correction model to obtain the long-term change law of the mass dry density of the soil to be tested.

2. The method according to claim 1, characterized in that The temperature characteristic value of each first test soil sample under the specified dry density and different mass moisture content in step S2 is as follows: Where, T t is the temperature characteristic value, in °C; T(t) is the sensor temperature corresponding to the heating time t, in °C; T0 is the initial ambient temperature, in °C; Q is the heating power per unit length, in Wm -1 ; λ is the thermal conductivity of the soil, in W m -1 K -1 ; R is the thermal resistance between the sensor and the soil wall per unit length, in m KW -1 ; K is the thermal diffusion coefficient of the soil, in m 2 s -1 ; a is the outer diameter of the sensor, in m; c = 1.7811 = exp(γ) and γ = 0.5772, γ is the Euler constant.

3. The method according to claim 2, characterized in that The temperature characteristic value-mass moisture content calibration formula fitted in step S3 includes: use The Konrad calibration model fits the following temperature characteristic value-mass moisture content calibration formula: in, A, B, and C are all target parameters; where κ is an empirical parameter determined according to soil type and freezing state; n is porosity; λ sat is the saturated thermal conductivity; dry is the dry thermal conductivity; ρ d is the dry density in g / cm 3 ρ w is the density of water in g / cm 3 .

4. The method according to claim 4, characterized in that: The temperature characteristic value-mass moisture content calibration formula obtained in step S5 under different dry density conditions is as follows: In the formula, A1, B1, and C are all constants.

5. The method according to claim 4, characterized in that The step S6 of establishing a calibration correction model that considers both dry density and mass moisture content simultaneously includes: Step S601, based on and Konrad calibration model concluded that the dry density is inversely proportional to the target parameter in the calibration formula; Step S602, substituting the target parameters in the temperature characteristic value-mass moisture content calibration formula obtained when the dry density of the second test soil sample is the first preset value into the temperature characteristic value-mass moisture content calibration formula obtained when the dry density of the second test soil sample is the second preset value, and analyzing the influence of the target parameters on the mass moisture content calibration result; Step S603, based on the analysis result of the influence of the target parameter on the mass moisture content calibration result obtained in step S602, a method of simultaneously considering dry density and mass moisture content is proposed. and Konrad calibration correction model, as follows: Where A2, B2 and C2 are temperature characteristic values ​​T t With mass moisture content w, dry density ρ d The fitting parameters of .

6. The method according to claim 5, characterized in that The step S7 comprises: Step 701, performing a heating test on a soil body to be tested with a known dry density or mass moisture content; Step 702, measuring the temperature characteristic value by active heating method, substituting the temperature characteristic value into the calibration correction model, and obtaining the long-term variation law of mass moisture content or dry density.

7. The method according to claim 6, characterized in that The method further comprises: When the mass moisture content remains unchanged, the calibration correction model can be simplified into the following expression: In the formula, and B d =C2 is the fitting parameter.

8. A soil dry density and moisture content calibration and measurement device based on active heating optical fiber, characterized in that: The device comprises: A test soil sample configuration module, used for configuring each first test soil sample with a specified dry density and different mass moisture content; A heating test module is used to bury an active heating type optical fiber sensor in each first test soil sample, and obtain a temperature characteristic value of each first test soil sample under conditions of a specified dry density and different mass moisture contents after heating with a specified heating power; The calibration formula fitting module is used to fit the temperature characteristic value-mass moisture content calibration formula according to the temperature characteristic value and different mass moisture contents obtained by the test soil sample configuration module and the heating test module; A dry density adjustment module is used to change the height of each first test soil sample in turn by an automatic compaction device for each first test soil sample, so as to obtain each second test soil sample with different mass moisture content under different dry density conditions; A fitting module for different dry density calibration formulas is used to perform heating tests on the second test soil samples with different mass moisture contents under different dry density conditions obtained in the dry density adjustment module, and obtain temperature characteristic value-mass moisture content calibration formulas under different dry density conditions; The calibration correction model establishment module is used to establish a calibration correction model that considers both dry density and mass moisture content according to the variation law of the target parameter in the temperature characteristic value-mass moisture content calibration formula obtained by the different dry density calibration formula fitting modules with the dry density; The calibration correction model calling module is used to obtain the dry density or mass moisture content of the soil to be tested; when obtaining the dry density of the soil to be tested, the temperature characteristic value is measured by the active heating method, and the temperature characteristic value is substituted into the calibration correction model to obtain the long-term change law of the mass moisture content of the soil to be tested; when obtaining the mass moisture content of the soil to be tested, the temperature characteristic value is measured by the active heating method, and the temperature characteristic value is substituted into the calibration correction model to obtain the long-term change law of the mass dry density of the soil to be tested.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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