Method for evaluating performance of cement-emulsified asphalt mortar based on MFN fusion

Abstract

The invention discloses a cement emulsified asphalt mortar performance evaluation method based on MFN fusion. The cement emulsified asphalt mortar performance evaluation method comprises the following steps: preparing cement emulsified asphalt mortar; preparing a cement emulsified asphalt mortar test piece, and testing the original performance; constructing a fractal dimension calculation model of the pore volume of the cement-emulsified asphalt mortar, and calculating the fractal dimension of the pore volume of the cement-emulsified asphalt mortar; constructing a neural network model for evaluating the performance of the cement-emulsified asphalt mortar, and training the neural network model until the neural network model is well trained; and drilling a cement-emulsified asphalt mortar sample on site, calculating the fractal dimension of the pore volume of the cement-emulsified asphalt mortar, inputting the fractal dimension and other input parameters into the trained neural network model, and evaluating the performance of the cement-emulsified asphalt mortar. The problems that in the prior art, an evaluation method is complex, depends on manual inspection and a large number of repeated tests, damage to the track is large, and data are inaccurate are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of railway engineering material performance evaluation, and specifically relates to a method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion. Background Art

[0002] In recent years, with the rapid development of high-speed railway construction, cement emulsion asphalt mortar (CA mortar for short) has been widely used in CRTSI and CRTSII slab ballastless tracks. As an important structural layer, cement emulsion asphalt mortar can support the track structure and compensate for the deformation of the underlying layer, thereby improving the comfort of high-speed railway operation. Therefore, evaluating the performance of cement emulsion asphalt mortar is an important part of maintaining the normal operation of high-speed railways.

[0003] In the prior art, the inspection methods for the performance of cement emulsified asphalt mortar mainly focus on the following aspects:

[0004] The traditional test method is used to directly measure the mechanical properties of the material, but the performance test of cement emulsified asphalt mortar depends on a large number of field tests, such as compression test, bending test, etc. These tests are not only time-consuming and labor-intensive, but also because the sample needs to be obtained by drilling, and the track surface is covered with a large amount of high-strength reinforced concrete, the thickness of cement emulsified asphalt mortar in the structural layer is very small, and the cutting or drilling process during sampling will inevitably cause disturbance or damage to the thin layer structure. Different sampling locations will also lead to large discreteness, resulting in inaccurate test results. These inaccurate strength data cannot fully reflect the actual use status and subsequent service life of cement emulsified asphalt mortar, and will also affect the optimization decision of materials in the future. Moreover, the amount of mortar for a single sample is difficult to meet the test requirements. The high sample demand will have a certain impact on the normal operation of transportation. In addition, the traditional test method requires a large sample volume, and the repair after sampling is difficult, which further increases the maintenance cost and may also affect the long-term safety of the track.

[0005] Experienced workers observe and inspect the performance of the track. This method can effectively reduce the damage to the track itself. However, track damage usually originates from the inside and then manifests itself externally. Ordinary manual observation can only determine the location of obvious external damage and easily ignores hidden internal damage. It is impossible to accurately evaluate the specific values ​​of the performance of cement emulsified asphalt mortar, thus missing the time for timely repairs and increasing subsequent maintenance costs.

[0006] Radar detection is a commonly used method at present. It has the advantages of high accuracy and fast detection speed. In theory, it can effectively detect hidden damage inside cement emulsified asphalt mortar, as well as damage caused by loose filling foundation, voids or water immersion erosion, and high-speed train load impact. However, this method needs to be implemented on the track surface, and the track surface of high-speed railways is covered with a large amount of reinforced concrete. For the cement emulsified asphalt mortar layer covered with a large amount of steel bars, radar waves are difficult to penetrate a large amount of steel bars and accurately reflect the performance of the mortar layer, thus affecting the evaluation of the performance of cement emulsified asphalt mortar.

[0007] It can be seen that the above-mentioned performance evaluation methods of cement emulsified asphalt mortar face many challenges in practical applications. Therefore, it is urgent to develop an evaluation method for the performance of cement emulsified asphalt mortar based on MFN fusion. This evaluation method integrates the original material mix ratio, nuclear magnetic resonance technology (NMR technology for short), fractal theory, and neural network model, and can accurately, efficiently, and low-loss evaluate the performance of cement emulsified asphalt mortar. Summary of the invention

[0008] The present invention aims to overcome the many defects of the cement emulsified asphalt mortar performance evaluation method in the prior art, mainly including: complex inspection method, poor manual inspection accuracy, need for a large number of repetitive tests, great damage to the track, etc. The present invention realizes the high efficiency, accuracy and low loss of cement emulsified asphalt mortar mix design and on-site performance evaluation by introducing material (material)-fractal dimension (fractal dimension)-neural network (neural network) fusion technology (abbreviated as MFN). The application of nuclear magnetic resonance technology (abbreviated as NMR technology) can greatly reduce the number of samples in the maintenance process, reduce the difficulty of sampling and maintenance, and protect the reliability and stability of rail transportation; the microstructure of cement emulsified asphalt mortar can be accurately described and analyzed by fractal dimension, which can significantly improve the safety and reliability of rail transportation; combined with neural network technology, it can shorten the inspection and maintenance time, and reduce the traffic burden and environmental pollution caused by maintenance construction. The present invention not only solves many deficiencies in the prior art, but also realizes the evaluation of multiple performance of materials, which has important practical application value and promotion significance.

[0009] In order to solve the problems existing in the prior art, the present invention provides a method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion, and the evaluation method comprises the following steps in chronological order:

[0010] Step 1: Prepare cement emulsified asphalt mortar according to design requirements;

[0011] Step 2: Prepare several cement emulsified asphalt mortar specimens for performance testing according to the design requirements, and conduct original performance tests on the cement emulsified asphalt mortar specimens, collect original performance test data, and use the original performance test data as a reference value for the subsequent neural network model output results;

[0012] Step 3: Use a low-field nuclear magnetic resonance imager to test the pore structure of cement emulsified asphalt mortar, and process the measured pore structure data; construct a fractal dimension calculation model for the pore volume of cement emulsified asphalt mortar based on the test data and the processed data, and calculate the fractal dimension of the pore volume of cement emulsified asphalt mortar through the calculation model, and collect the fractal dimension calculation data at the same time, and use the fractal dimension calculation data as the input parameter for subsequent neural network model training;

[0013] Step 4: Construct a neural network model for evaluating the performance of cement emulsified asphalt mortar, and train the constructed neural network model; after training, the neural network model outputs the result, and compares the output result with the original performance test data. If the output result is the same or similar to the original performance test data, it is determined that the neural network model has been trained, otherwise it is debugged and optimized until the neural network model is trained, and the trained neural network model is subsequently used to evaluate the performance of cement emulsified asphalt mortar;

[0014] Step 5: Drill several cement emulsified asphalt mortar samples to be evaluated on the cement emulsified asphalt mortar layer on the side of the high-speed railway track, and perform surface treatment and cleaning; calculate the fractal dimension of the pore volume of cement emulsified asphalt mortar according to the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar, input the fractal dimension of the pore volume of cement emulsified asphalt mortar and other input parameters into the trained neural network model, and output the actual value of the performance of the cement emulsified asphalt mortar, and compare the actual value with the standard specification or design requirements. If the actual value meets the standard specification or design requirements, it means that the performance of the cement emulsified asphalt mortar to be evaluated is good, otherwise timely measures need to be taken to ensure the structural safety of the high-speed railway track.

[0015] Preferably, in step one, the mass percentage of each substance in the cement emulsified asphalt mortar is 25-35wt% for emulsified asphalt, 15-20wt% for cement, 35-40wt% for fine aggregate, 0.3-0.7wt% for UEA expansion agent, 0.01-0.03wt% for aluminum powder, 1-3wt% for silicone defoamer, 0.02-0.05wt% for sodium rosin acid, 1.5-3wt% for water reducer, 2-5wt% for silica fume, 1.5-4wt% for chloroprene rubber latex, and 5-10wt% for water; the ratio of the mass of the water to the mass of the cement is 1:1.5-4, and the ratio of the mass of the emulsified asphalt to the mass of the cement is 1.5-1.8:1.

[0016] The cement is PO 42.5 ordinary Portland cement or fast-hardening sulphoaluminate cement; the fine aggregate is any one or more of river sand, mountain sand and machine-made sand, and the particle size of the fine aggregate is 1.5-2mm; the water reducer is a high-performance polycarboxylate water reducer, and its water reduction rate is 25%.

[0017] The preparation process of the cement emulsified asphalt mortar is as follows: putting various materials into a mixer, stirring at room temperature, and mixing them evenly; the prepared cement emulsified asphalt mortar has a fluidity of 18-26s and an expansion of 240-280mm.

[0018] In any of the above schemes, it is preferred that in step 2, the molding process of the cement emulsified asphalt mortar specimen is to pour the cement emulsified asphalt mortar into a molding mold to form the specimen, the cement emulsified asphalt mortar is demoulded after standing in the molding mold for 24 hours, and cured indoors for 1 day; after the indoor curing is completed, the specimen is placed in a curing room with a temperature of 20±3°C and a humidity of 65±5% for curing, and is cured to a certain age.

[0019] The molding mold is cylindrical and rectangular. The inner cavity diameter of the cylindrical molding mold is 50 mm and the inner cavity height is 50 mm. The inner cavity length of the rectangular molding mold is 40 mm, the inner cavity width is 40 mm, and the inner cavity height is 160 mm.

[0020] In any of the above schemes, it is preferred that in step 2, the cement emulsified asphalt mortar specimen is subjected to original performance tests, including compressive strength test, elastic modulus test, flexural strength test, and weather resistance test.

[0021] For the compressive strength test, the cement emulsified asphalt mortar specimens used were cylindrical with a diameter of 50 mm and a height of 50 mm. The curing ages of the cement emulsified asphalt mortar specimens were 7 days, 14 days, and 28 days. The number of specimens for each curing age was 3. The test equipment used was an electronic universal testing machine with a loading rate of 1 mm / min. The test results of the three specimens for each curing age were averaged and used as the representative value of the compressive strength at that curing age.

[0022] For the elastic modulus test, the cement emulsified asphalt mortar specimen used was cylindrical with a diameter of 50 mm and a height of 50 mm. The curing age of the cement emulsified asphalt mortar specimen was 28 days, and the number of specimens was 1. The test equipment used was an electronic universal testing machine. The specimen was loaded at a loading rate of 1 mm / min until the compressive strength reached 0.1 MPa and then immediately unloaded. The unloading rate was the same as the loading rate. The loading and unloading process was then repeated four times, and the elastic modulus was calculated using the data from the last loading curve.

[0023] For the flexural strength test, the cement emulsified asphalt mortar specimens used were rectangular in shape, with a length of 40 mm, a width of 40 mm, and a height of 160 mm. The curing ages of the cement emulsified asphalt mortar specimens were 7 days, 14 days, and 28 days. The number of specimens for each curing age was 3, and the test equipment used was a cement mortar electric flexural testing machine. The test results of the three specimens for each curing age were averaged and used as the representative value of the flexural strength at that curing age.

[0024] For the weather resistance test, the cement emulsified asphalt mortar specimens used were rectangular in shape, with a length of 40 mm, a width of 40 mm, and a height of 160 mm. The curing age of the cement emulsified asphalt mortar specimens was 28 days. The number of specimens was 24, and the 24 specimens were evenly divided into 8 groups. After the cement emulsified asphalt mortar specimens were cured for 28 days, 4 groups of specimens were placed in a xenon lamp aging box for irradiation, and the other 4 groups of specimens continued to be placed in a curing room with a temperature of 20±3°C and a humidity of 65±5% for curing. When the irradiation time was 0h, 100h, 300h, and 500h, compression tests were carried out on the irradiated specimens and the non-irradiated specimens of the same age, respectively. The test equipment used was a universal testing machine with a loading rate of 1mm / min. The appearance changes of the specimens were checked during the compression test.

[0025] In any of the above schemes, preferably, in step 3, the method for constructing the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar comprises the following steps in chronological order:

[0026] Step (i): saturate the cement emulsified asphalt mortar specimens with a curing age of 7 days, 14 days, and 28 days with water to constant weight, and take 0.2g of cement emulsified asphalt mortar from each saturated specimen for pore structure testing, use a low-field nuclear magnetic resonance imaging device to measure the transverse relaxation time of the pore fluid in the saturated specimen and the corresponding nuclear magnetic resonance signal amount, and process the data to obtain the relationship between the transverse relaxation time of the pore fluid and the pore radius;

[0027] Step (ii): Through the nuclear magnetic resonance relaxation method, it can be obtained that the nuclear magnetic resonance signal is proportional to the water content of the saturated specimen under the same parameters. Then, the saturated specimen with known water content is tested by the physical drying weight loss method, and the corresponding relationship between the relaxation time peak area and the water mass in the cement emulsified asphalt mortar is established. The relationship between the signal amplitude and the pore volume is further fitted, and the signal amplitude is substituted into the relationship to complete the conversion of the signal amplitude and the pore volume;

[0028] Step (iii): The pores inside the cement emulsified asphalt mortar are equivalent to the spheres in the fractal dimension calculation model. In the fractal dimension calculation model, there are n groups of pores with different diameters, namely, d i(i=1,2,3,......,n), the diameter of the pore is defined as the size of the sphere; according to the equivalent principle, the diameter is greater than or equal to d i The pore diameter is converted into d i Therefore, the minimum number of balls required to cover all pores can be counted as the equivalent number of pores, that is, N δi (i=1,2,3,......,n); based on a series of pore diameters and equivalent pore numbers [d1,N δ1 ],[d2,N δ2 ],.......,[d n ,N δn ], get d i With N δi The relationship between , which is the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar.

[0029] In any of the above schemes, preferably, in step (a), the relationship between the transverse relaxation time of the pore fluid and the pore radius is: in Where, T2 is the transverse relaxation time of pore fluid, ms;

[0030] T 2表面 ——Transverse relaxation time caused by surface relaxation, ms;

[0031] ρ——surface relaxation rate, dimensionless;

[0032] ——Specific surface area of ​​pores, m 2 / g;

[0033] F s ——pore shape factor, dimensionless;

[0034] r——pore radius, nm.

[0035] In any of the above schemes, preferably, in step (ii), the relationship between the signal amplitude and the pore volume is: 7d: SA = 1480V-575.59

[0036] 14d: SA = 1480V - 575.59

[0037] 28d:

[0038] 28d: Where, SA is the signal amplitude, dimensionless;

[0039] V——pore volume, nm 3 .

[0040] In any of the above schemes, preferably, in step (iii), the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar is lnN δ =Dln(1 / r)+C, where D is the fractal dimension of the pore volume of cement emulsified asphalt mortar, dimensionless;

[0041] N δ ——equivalent pore number, pieces;

[0042] r——pore radius, nm;

[0043] C——constant, dimensionless.

[0044] In the present invention, the fractal dimension of the pore volume of cement emulsified asphalt mortar is used to describe the fractal dimension of the pore structure of the mortar, which represents the complexity of the pore arrangement. The larger the fractal dimension of the pore volume, the more pores with small pore diameters account for, and the more complex the pore arrangement; the smaller the fractal dimension of the pore volume, the more pores with large pore diameters account for, and the simpler the pore arrangement.

[0045] In any of the above schemes, preferably, in step 4, the method for constructing a neural network model for evaluating the performance of cement emulsified asphalt mortar comprises the following steps in order:

[0046] Step (A): using the amount of cement, the amount of emulsified asphalt, the fractal dimension of the pore volume of cement emulsified asphalt mortar, and the curing age as input parameters, setting the number of neurons in the input layer to four, using the compressive strength, elastic modulus, flexural strength, and weather resistance as output parameters, setting the number of neurons in the output layer to four, that is, constructing a neural network structure with four-parameter input and four-parameter output;

[0047] Step (B): To eliminate the influence of different indicators and different dimensions, normalization is performed before training the neural network model;

[0048] Step (C): In the neural network model, a smaller initial value of the weight is selected, the transfer function of the hidden layer neurons is an S-type transfer function, the transfer function of the output layer is a linear function, and the Trainlm training function is used. The number of training times is set to 10,000, the learning rate is set to 0.01, and the training target is a minimum error of 0.000001.

[0049] In any of the above schemes, it is preferred that in step five, a cement emulsified asphalt mortar sample is drilled every 100 m on the cement emulsified asphalt mortar layer on the side of the high-speed railway track, and the cement emulsified asphalt mortar sample is cylindrical with a diameter of 5 mm and a height of 5 mm; other input parameters include the amount of cement in the cement emulsified asphalt mortar sample, the amount of emulsified asphalt, and the time of on-site use.

[0050] The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion of the present invention has the following beneficial effects:

[0051] (1) In view of the problems that the evaluation method of cement emulsified asphalt mortar layer performance in the existing high-speed railway track maintenance process is complex, relies on manual inspection and a large number of repetitive tests, and causes great damage to the track, the present invention innovatively combines the material microscopic characteristics with the performance through the material (material)-fractal dimension (fractal dimension)-neural network (neural network) fusion technology (MFN for short), constructs the mix ratio design of cement emulsified asphalt mortar and the on-site performance evaluation method, thereby greatly reducing the sample amount and the damage to the track while ensuring the efficiency and accuracy of the inspection, significantly improving the convenience and reliability of the inspection, further realizing the accurate description of the internal microstructure of the cement emulsified asphalt mortar, providing an important basis for the characterization of material properties, and finally solving the problems of cumbersome inspection process, high cost, great damage and inaccurate data in the prior art.

[0052] (2) Nuclear magnetic resonance technology (NMR technology) is used to nondestructively detect the microstructure and moisture distribution inside the cement emulsified asphalt mortar. High-resolution imaging and molecular motion analysis are used to improve the understanding and control of the mortar performance. The test has high accuracy and requires fewer samples, thus avoiding damage to the track caused by large-scale sampling during maintenance.

[0053] (3) The introduction of fractal dimension can express the structural characteristics of cement emulsified asphalt mortar measured by NMR technology, making the data required for subsequent performance evaluation more accurate and efficient. It can accurately describe the microstructural characteristics of cement emulsified asphalt mortar and help optimize the accuracy of material performance evaluation.

[0054] (4) Construct a neural network model. By learning a large amount of test data, it provides a medium for the deep integration of mix proportion, fractal dimension and performance. The neural network model can process and output multiple variables, significantly improving the design efficiency and effect. At the same time, the application of the neural network model can quickly respond to different construction requirements and environmental changes, thereby improving the speed of engineering inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a flow chart of a preferred embodiment of a method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to the present invention;

[0056] Figure 2 for Figure 1 The relationship curve between the pore volume ratio and the pore radius when the curing age is 7 days in the embodiment shown;

[0057] Figure 3 for Figure 1 The relationship curve between the pore volume ratio and the pore radius when the curing age is 14 days in the embodiment shown;

[0058] Figure 4 for Figure 1 The relationship curve between the pore volume ratio and the pore radius when the curing age is 28 days in the embodiment shown. DETAILED DESCRIPTION

[0059] In order to further understand the content of the present invention, the present invention will be described in detail below in conjunction with specific embodiments.

[0060] Embodiment 1:

[0061] like Figure 1 As shown, according to a preferred embodiment of the method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion of the present invention, the evaluation method comprises the following steps in chronological order:

[0062] Step 1: Prepare cement emulsified asphalt mortar according to design requirements;

[0063] Step 2: Prepare several cement emulsified asphalt mortar specimens for performance testing according to the design requirements, and conduct original performance tests on the cement emulsified asphalt mortar specimens, collect original performance test data, and use the original performance test data as a reference value for the subsequent neural network model output results;

[0064] Step 3: Use a low-field nuclear magnetic resonance imager to test the pore structure of cement emulsified asphalt mortar, and process the measured pore structure data; construct a fractal dimension calculation model for the pore volume of cement emulsified asphalt mortar based on the test data and the processed data, and calculate the fractal dimension of the pore volume of cement emulsified asphalt mortar through the calculation model, and collect the fractal dimension calculation data at the same time, and use the fractal dimension calculation data as the input parameter for subsequent neural network model training;

[0065] Step 4: Construct a neural network model for evaluating the performance of cement emulsified asphalt mortar, and train the constructed neural network model; after training, the neural network model outputs the result, and compares the output result with the original performance test data. If the output result is the same or similar to the original performance test data, it is determined that the neural network model has been trained, otherwise it is debugged and optimized until the neural network model is trained, and the trained neural network model is subsequently used to evaluate the performance of cement emulsified asphalt mortar;

[0066] Step 5: Drill several cement emulsified asphalt mortar samples to be evaluated on the cement emulsified asphalt mortar layer on the side of the high-speed railway track, and perform surface treatment and cleaning; calculate the fractal dimension of the pore volume of cement emulsified asphalt mortar according to the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar, input the fractal dimension of the pore volume of cement emulsified asphalt mortar and other input parameters into the trained neural network model, and output the actual value of the performance of the cement emulsified asphalt mortar, and compare the actual value with the standard specification or design requirements. If the actual value meets the standard specification or design requirements, it means that the performance of the cement emulsified asphalt mortar to be evaluated is good, otherwise timely measures need to be taken to ensure the structural safety of the high-speed railway track.

[0067] In step one, the mass percentage of each substance in the cement emulsified asphalt mortar is 30wt% of emulsified asphalt, 20wt% of cement, 35wt% of fine aggregate, 0.55wt% of UEA expansion agent, 0.02wt% of aluminum powder, 1wt% of silicone defoamer, 0.03wt% of sodium rosin acid, 2.4wt% of water reducer, 3wt% of silica fume, 3wt% of chloroprene rubber latex, and 5wt% of water; the ratio of the mass of the water to the mass of the cement is 1:4, and the ratio of the mass of the emulsified asphalt to the mass of the cement is 1.5:1.

[0068] The cement is PO 42.5 ordinary Portland cement; the fine aggregate is river sand with a particle size of 1.8 mm; the water reducer is a high-performance polycarboxylate water reducer with a water reduction rate of 25%.

[0069] The preparation process of the cement emulsified asphalt mortar is to put various materials into a mixer and stir them at room temperature until they are evenly mixed; the fluidity of the prepared cement emulsified asphalt mortar is 22s and the expansion is 260mm.

[0070] In step 2, the molding process of the cement emulsified asphalt mortar specimen is to pour the cement emulsified asphalt mortar into a molding mold to form the specimen, demould the cement emulsified asphalt mortar after standing in the molding mold for 24 hours, and cure it indoors for 1 day; after the indoor curing is completed, place the specimen in a curing room with a temperature of 20±3°C and a humidity of 65±5% for curing, and cure it to a certain age. The molding mold is cylindrical and rectangular, the inner cavity diameter of the cylindrical molding mold is 50mm, the inner cavity height is 50mm, and the inner cavity length of the rectangular molding mold is 40mm, the inner cavity width is 40mm, and the inner cavity height is 160mm.

[0071] The cement emulsified asphalt mortar specimens were subjected to original performance tests, including compressive strength test, elastic modulus test, flexural strength test, and weather resistance test.

[0072] For the compressive strength test, the cement emulsified asphalt mortar specimens used were cylindrical with a diameter of 50 mm and a height of 50 mm. The curing ages of the cement emulsified asphalt mortar specimens were 7 days, 14 days, and 28 days. The number of specimens for each curing age was 3. The test equipment used was an electronic universal testing machine with a loading rate of 1 mm / min. The test results of the three specimens for each curing age were averaged and used as the representative value of the compressive strength at that curing age. The test results are shown in Table 1.

[0073] Table 1 Compressive strength test results of cement emulsified asphalt mortar specimens

[0074]

[0075] For the elastic modulus test, the cement emulsified asphalt mortar specimen used was cylindrical with a diameter of 50 mm and a height of 50 mm. The curing age of the cement emulsified asphalt mortar specimen was 28 days, and the number of specimens was 1. The test equipment used was an electronic universal testing machine. The specimen was loaded at a loading rate of 1 mm / min until the compressive strength reached 0.1 MPa and then immediately unloaded. The unloading rate was the same as the loading rate. The loading and unloading process was repeated four times. The elastic modulus was calculated using the data of the last loading curve, and the calculated result was 96.23 MPa.

[0076] For the flexural strength test, the cement emulsified asphalt mortar specimens used were rectangular in shape with a length of 40 mm, a width of 40 mm, and a height of 160 mm. The curing ages of the cement emulsified asphalt mortar specimens were 7 days, 14 days, and 28 days. The number of specimens for each curing age was 3. The test equipment used was a cement mortar electric flexural testing machine. The test results of the three specimens for each curing age were averaged and used as the representative value of the flexural strength at that curing age. The test results are shown in Table 2.

[0077] Table 2 Flexural strength test results of cement emulsified asphalt mortar specimens

[0078]

[0079] For the weather resistance test, the cement emulsified asphalt mortar specimens used were rectangular, with a length of 40 mm, a width of 40 mm, and a height of 160 mm. The curing age of the cement emulsified asphalt mortar specimens was 28 days, and the number of specimens was 24, which were evenly divided into 8 groups. After the cement emulsified asphalt mortar specimens were cured for 28 days, 4 groups of specimens were placed in a xenon lamp aging box for irradiation, and the other 4 groups of specimens continued to be placed in a curing room with a temperature of 20±3°C and a humidity of 65±5% for curing. When the irradiation time was 0h, 100h, 300h, and 500h, the irradiated specimens and the non-irradiated specimens of the same age were subjected to compression tests, respectively. The test equipment used was a universal testing machine with a loading rate of 1mm / min. The appearance changes of the specimens were checked during the compression test. The test results are shown in Table 3.

[0080] Table 3 Weathering performance test results of cement emulsified asphalt mortar specimens

[0081] Aging method 0h 100h 300h 500h Irradiation in xenon lamp box 4.92MPa 4.95MPa 5.02MPa 5.08MPa Maintenance Indoor maintenance 5.01MPa 5.09MPa 5.16MPa 5.18MPa

[0082] In step 3, the method for constructing the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar comprises the following steps in order:

[0083] Step (i): saturate the cement emulsified asphalt mortar specimens with a curing age of 7 days, 14 days, and 28 days with water to constant weight, and take 0.2g of cement emulsified asphalt mortar from each saturated specimen for pore structure testing, use a low-field nuclear magnetic resonance imaging device to measure the transverse relaxation time of the pore fluid in the saturated specimen and the corresponding nuclear magnetic resonance signal amount, and process the data to obtain the relationship between the transverse relaxation time of the pore fluid and the pore radius;

[0084] Step (ii): Through the nuclear magnetic resonance relaxation method, it can be obtained that the nuclear magnetic resonance signal is proportional to the water content of the saturated specimen under the same parameters. Then, the saturated specimen with known water content is tested by the physical drying weight loss method, and the corresponding relationship between the relaxation time peak area and the water mass in the cement emulsified asphalt mortar is established. The relationship between the signal amplitude and the pore volume is further fitted, and the signal amplitude is substituted into the relationship to complete the conversion of the signal amplitude and the pore volume;

[0085] Step (iii): The pores inside the cement emulsified asphalt mortar are equivalent to the spheres in the fractal dimension calculation model. In the fractal dimension calculation model, there are n groups of pores with different diameters, namely, d i (i=1,2,3,......,n), the diameter of the pore is defined as the size of the sphere; according to the equivalent principle, the diameter is greater than or equal to d i The pore diameter is converted into d iTherefore, the minimum number of balls required to cover all pores can be counted as the equivalent number of pores, that is, N δi (i=1,2,3,......,n); based on a series of pore diameters and equivalent pore numbers [d1,N δ1 ],[d2,N δ2 ],.......,[d n ,N δn ], get d i With N δi The relationship between , which is the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar.

[0086] In step (a), the relationship between the transverse relaxation time of the pore fluid and the pore radius is: in

[0087] Where, T2 is the transverse relaxation time of pore fluid, ms;

[0088] T 2表面 ——Transverse relaxation time caused by surface relaxation, ms;

[0089] ρ——surface relaxation rate, dimensionless;

[0090] ——Specific surface area of ​​pores, m 2 / g;

[0091] F s ——pore shape factor, dimensionless;

[0092] r——pore radius, nm.

[0093] In this embodiment, ρ=10, Fs=2.2.

[0094] The curing age is 7 days: T2 = 0.05292ms is measured, and the pore radius r = 1.0584nm is calculated;

[0095] The curing age is 14 days: T2 = 0.056724ms is measured, and the pore radius r = 1.13448nm is calculated;

[0096] The curing age is 28 days: T2 is measured to be 0.060802 ms, and the pore radius is calculated to be r = 1.21604 nm.

[0097] In step (ii), the relationship between the signal amplitude and the pore volume is:

[0098] 7d: SA = 1480V - 575.59

[0099] 14d: SA = 1480V - 575.59

[0100] 28d:

[0101] 28d: Where, SA is the signal amplitude, dimensionless;

[0102] V——pore volume, nm 3 .

[0103] Substitute the calculated pore radius into the relationship between the signal amplitude and the pore volume in step (ii) to obtain the pore size distribution diagram at each curing age, where: the relationship curve between the pore volume ratio and the pore radius when the curing age is 7 days is as follows: Figure 2 As shown in Figure 2, the relationship between the pore volume ratio and the pore radius when the curing age is 14 days is as follows: Figure 3 As shown in the figure, the relationship between the pore volume ratio and the pore radius when the curing age is 28 days is as follows: Figure 4 shown.

[0104] In step (iii), the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar is lnN δ =Dln(1 / r)+C,

[0105] Where, D is the fractal dimension of the pore volume of cement emulsified asphalt mortar, dimensionless;

[0106] N δ ——equivalent pore number, pieces;

[0107] r——pore radius, nm;

[0108] C——constant, dimensionless.

[0109] In this embodiment, C = 54.2861, ln(1 / r) and lnN δ The specific value of and the calculation result of D are shown in Table 4. It can be seen from the table that the calculation result of the fractal dimension is consistent with the pore size distribution diagram and can be used for the training of the neural network model.

[0110] Table 4 Calculation results of fractal dimension of pore volume of cement emulsified asphalt mortar

[0111] Maintenance age ln(1 / r) <![CDATA[lnN δ ]]> D 7 days 0.02 6.43E+17 3.20 14 days 0.01 1.22E+17 3.14 28 days 0.01 2.35E+17 3.36

[0112] In step 4, the method for constructing a neural network model for evaluating the performance of cement emulsified asphalt mortar includes the following steps in order:

[0113] Step (A): using the amount of cement, the amount of emulsified asphalt, the fractal dimension of the pore volume of cement emulsified asphalt mortar, and the curing age as input parameters, setting the number of neurons in the input layer to four, using the compressive strength, elastic modulus, flexural strength, and weather resistance as output parameters, setting the number of neurons in the output layer to four, that is, constructing a neural network structure with four-parameter input and four-parameter output;

[0114] Step (B): To eliminate the influence of different indicators and different dimensions, normalization is performed before training the neural network model;

[0115] Step (C): In the neural network model, a smaller initial value of the weight is selected, the transfer function of the hidden layer neurons is an S-type transfer function, the transfer function of the output layer is a linear function, and the Trainlm training function is used. The number of training times is set to 10,000, the learning rate is set to 0.01, and the training target is a minimum error of 0.000001.

[0116] The parameters are input into the neural network model, and the output results after training are shown in Table 5-7.

[0117] Table 5 Compressive strength results output by the neural network model

[0118] performance 7 days 14 days 28 days Compressive strength(MPa) 3.21 3.59 4.88

[0119] Table 6 Flexural strength results output by the neural network model

[0120] performance 7 days 14 days 28 days Flexural strength(MPa) 2.15 2.40 3.7

[0121] Table 7 Weathering performance results output by the neural network model

[0122] performance 0h 100h 300h 500h Aging exposure 4.85MPa 4.91MPa 5.06MPa 5.11MPa

[0123] In addition, the elastic modulus output by the neural network model is 95.29MPa. Compared with the data measured by the test, the error is within 5%, indicating that the neural network model has a high accuracy.

[0124] In step five, a cement emulsified asphalt mortar sample is drilled every 100 m on the cement emulsified asphalt mortar layer on the side of the high-speed railway track. The cement emulsified asphalt mortar sample is cylindrical with a diameter of 5 mm and a height of 5 mm. Other input parameters include the amount of cement in the cement emulsified asphalt mortar sample, the amount of emulsified asphalt, and the time of on-site use.

[0125] In this embodiment, 5 groups of cement emulsified asphalt mortar samples were drilled for testing, and the fractal dimension of the samples was measured according to steps 1 to 3, and D = 3.43 was obtained. The amount of cement (20wt%), the amount of emulsified asphalt (30wt%), the curing age (1000h), and the fractal dimension of the pore volume (3.43) are known and input into the trained neural network model. The output results after processing are shown in Table 8. The output results are compared with the standard specifications or design requirements. If they meet the requirements, it means that the high-speed railway track can continue to be used.

[0126] Table 8 Actual results of the neural network model output

[0127] Sample No. Compressive strength(MPa) Flexural strength(MPa) Elastic modulus (MPa) Weather resistance (MPa) 1 4.72 3.61 94.12 4.68 2 4.89 3.67 92.25 4.73 3 4.60 3.75 95.34 4.50 4 4.56 3.55 96.05 4.82 5 4.83 3.78 93.67 4.66 average value 4.72 3.67 94.29 4.68

[0128] The evaluation method of cement emulsified asphalt mortar performance based on MFN fusion in this embodiment has the following beneficial effects: in view of the problems that the evaluation method of cement emulsified asphalt mortar layer performance in the existing high-speed railway track maintenance process is complex, relies on manual inspection and a large number of repetitive tests, and causes great damage to the track, the material microscopic characteristics and performance performance are innovatively combined through the material (material)-fractal dimension (fractal dimension)-neural network (neural network) fusion technology (MFN for short), and the mix ratio design of cement emulsified asphalt mortar and the on-site performance evaluation method are constructed, thereby ensuring efficient and accurate inspection while greatly reducing the sample amount, reducing damage to the track, significantly improving the convenience and reliability of the inspection, further realizing the accurate description of the internal microstructure of the cement emulsified asphalt mortar, providing an important basis for the characterization of material properties, and finally solving the problems of cumbersome inspection process, high cost, great damage and inaccurate data in the prior art.

[0129] Embodiment 2:

[0130] According to another preferred embodiment of the method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion of the present invention, its process flow, technical principle, beneficial effects, etc. are basically the same as those of the first embodiment, except that:

[0131] In step 1, the mass percentage of each substance in the cement emulsified asphalt mortar is 31wt% of emulsified asphalt, 18wt% of cement, 36wt% of fine aggregate, 0.3wt% of UEA expansion agent, 0.01wt% of aluminum powder, 1.67wt% of organic silicon defoamer, 0.02wt% of sodium rosin acid, 1.5wt% of water reducer, 2wt% of silica fume, 1.5wt% of chloroprene rubber latex, and 8wt% of water; the mass ratio of the water to the mass of the cement is 1:2.25, and the mass ratio of the emulsified asphalt to the mass of the cement is 1.72:1. The cement is PO 42.5 ordinary Portland cement; the fine aggregate is river sand with a particle size of 1.5mm; the water reducer is a high-performance polycarboxylate water reducer with a water reduction rate of 25%. The preparation process of the cement emulsified asphalt mortar is to put various materials into a mixer, stir them at room temperature, and mix them evenly; the fluidity of the prepared cement emulsified asphalt mortar is 18s and the expansion is 240mm.

[0132] Embodiment three:

[0133] According to another preferred embodiment of the method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion of the present invention, its process flow, technical principle, beneficial effects, etc. are basically the same as those of the first embodiment, except that:

[0134] In step 1, the mass percentage of each substance in the cement emulsified asphalt mortar is 28wt% of emulsified asphalt, 17wt% of cement, 38wt% of fine aggregate, 0.7wt% of UEA expansion agent, 0.03wt% of aluminum powder, 2wt% of organic silicon defoamer, 0.05wt% of sodium rosin acid, 2wt% of water reducer, 2.22wt% of silica fume, 2wt% of chloroprene rubber latex, and 8wt% of water; the mass ratio of the water to the mass of the cement is 1:2.125, and the mass ratio of the emulsified asphalt to the mass of the cement is 1.647:1. The cement is PO 42.5 ordinary Portland cement; the fine aggregate is river sand with a particle size of 2mm; the water reducer is a high-performance polycarboxylate water reducer with a water reduction rate of 25%. The preparation process of the cement emulsified asphalt mortar is to put various materials into a mixer and stir them at room temperature until they are evenly mixed; the fluidity of the prepared cement emulsified asphalt mortar is 26s and the expansion is 280mm.

[0135] Special note: The technical solution of the present invention involves many parameters, and the synergistic effects between the various parameters need to be comprehensively considered to obtain the beneficial effects and significant progress of the present invention. Moreover, the value ranges of the various parameters in the technical solution are obtained after a large number of experiments. For each parameter and the combination of each parameter, the inventor has recorded a large amount of experimental data. Due to space limitations, the specific experimental data will not be disclosed here.

[0136] It is not difficult for those skilled in the art to understand that the evaluation method of cement emulsified asphalt mortar performance based on MFN fusion of the present invention includes any combination of the invention content and specific implementation methods of the above-mentioned invention specification and the various parts shown in the drawings. Due to the limited space and to make the specification concise, the various schemes composed of these combinations are not described one by one. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion, characterized in that: The evaluation method comprises the following steps in order: Step 1: Prepare cement emulsified asphalt mortar according to design requirements; Step 2: Prepare several cement emulsified asphalt mortar specimens for performance testing according to the design requirements, and conduct original performance tests on the cement emulsified asphalt mortar specimens, collect original performance test data, and use the original performance test data as a reference value for the subsequent neural network model output results; Step 3: Use a low-field nuclear magnetic resonance imaging device to test the pore structure of cement emulsified asphalt mortar, and process the measured pore structure data; A fractal dimension calculation model for the pore volume of cement emulsified asphalt mortar is constructed based on the test data and the processed data, and the fractal dimension of the pore volume of cement emulsified asphalt mortar is calculated by the calculation model, and the fractal dimension calculation data is collected at the same time, and the fractal dimension calculation data is used as the input parameter for the subsequent neural network model training; Step 4: Construct a neural network model for evaluating the performance of cement emulsified asphalt mortar, and train the constructed neural network model; after training, the neural network model outputs the result, and compares the output result with the original performance test data. If the output result is the same or similar to the original performance test data, it is determined that the neural network model has been trained, otherwise it is debugged and optimized until the neural network model is trained, and the trained neural network model is subsequently used to evaluate the performance of cement emulsified asphalt mortar; Step 5: Drill several cement emulsified asphalt mortar samples to be evaluated on the cement emulsified asphalt mortar layer on the side of the high-speed railway track, and perform surface treatment and cleaning; calculate the fractal dimension of the pore volume of cement emulsified asphalt mortar according to the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar, input the fractal dimension of the pore volume of cement emulsified asphalt mortar and other input parameters into the trained neural network model, and output the actual value of the performance of the cement emulsified asphalt mortar, and compare the actual value with the standard specification or design requirements. If the actual value meets the standard specification or design requirements, it means that the performance of the cement emulsified asphalt mortar to be evaluated is good, otherwise timely measures need to be taken to ensure the structural safety of the high-speed railway track.

2. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 1, characterized in that: In step 1, the mass percentage of each substance in the cement emulsified asphalt mortar is 25-35wt% of emulsified asphalt, 15-20wt% of cement, 35-40wt% of fine aggregate, 0.3-0.7wt% of UEA expansion agent, 0.01-0.03wt% of aluminum powder, 1-3wt% of organic silicon defoamer, 0.02-0.05wt% of sodium rosin acid, 1.5-3wt% of water reducer, 2-5wt% of silica fume, 1.5-4wt% of chloroprene rubber latex, and 5-10wt% of water; the mass ratio of the water to the mass of the cement is 1:1.5-4, and the mass ratio of the emulsified asphalt to the mass of the cement is 1.5-1.8:1; The cement is PO 42.5 ordinary Portland cement or fast-hardening sulphoaluminate cement; the fine aggregate is any one or more of river sand, mountain sand and machine-made sand, and the particle size of the fine aggregate is 1.5-2 mm; the water reducer is a high-performance polycarboxylate water reducer, and its water reduction rate is 25%; The preparation process of the cement emulsified asphalt mortar is as follows: putting various materials into a mixer, stirring at room temperature, and mixing them evenly; the prepared cement emulsified asphalt mortar has a fluidity of 18-26s and an expansion of 240-280mm.

3. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 2, characterized in that: In step 2, the molding process of the cement emulsified asphalt mortar specimen is as follows: pouring the cement emulsified asphalt mortar into a molding mold to form the specimen, demolding the cement emulsified asphalt mortar after standing in the molding mold for 24 hours, and curing indoors for 1 day; after the indoor curing is completed, the specimen is placed in a curing room with a temperature of 20±3°C and a humidity of 65±5% for curing, and is cured to a certain age; The molding mold is cylindrical and rectangular. The inner cavity diameter of the cylindrical molding mold is 50 mm and the inner cavity height is 50 mm. The inner cavity length of the rectangular molding mold is 40 mm, the inner cavity width is 40 mm, and the inner cavity height is 160 mm.

4. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 3 is characterized in that: In step 2, the cement emulsified asphalt mortar specimens are subjected to original performance tests, including compressive strength test, elastic modulus test, flexural strength test, and weather resistance test; For the compressive strength test, the cement emulsified asphalt mortar specimens used were cylindrical, with a diameter of 50 mm and a height of 50 mm. The curing ages of the cement emulsified asphalt mortar specimens were 7 days, 14 days, and 28 days. The number of specimens for each curing age was 3. The test equipment used was an electronic universal testing machine with a loading rate of 1 mm / min. The test results of the 3 specimens for each curing age were averaged and used as the representative value of the compressive strength at that curing age. For the elastic modulus test, the cement emulsified asphalt mortar specimen used was cylindrical, with a diameter of 50 mm and a height of 50 mm. The curing age of the cement emulsified asphalt mortar specimen was 28 days, and the number of specimens was 1. The test equipment used was an electronic universal testing machine. The specimen was loaded at a loading rate of 1 mm / min until the compressive strength reached 0.1 MPa, and then immediately unloaded. The unloading rate was the same as the loading rate, and then the loading and unloading process was repeated four times. The elastic modulus was calculated based on the data of the last loading curve. For the flexural strength test, the cement emulsified asphalt mortar specimens used were rectangular, with a length of 40 mm, a width of 40 mm, and a height of 160 mm. The curing ages of the cement emulsified asphalt mortar specimens were 7 days, 14 days, and 28 days, and the number of specimens for each curing age was 3. The test equipment used was a cement mortar electric flexural testing machine. The test results of the 3 specimens for each curing age were averaged and used as the representative value of the flexural strength at that curing age. For the weather resistance test, the cement emulsified asphalt mortar specimens used were rectangular in shape, with a length of 40 mm, a width of 40 mm, and a height of 160 mm. The curing age of the cement emulsified asphalt mortar specimens was 28 days. The number of specimens was 24, and the 24 specimens were evenly divided into 8 groups. After the cement emulsified asphalt mortar specimens were cured for 28 days, 4 groups of specimens were placed in a xenon lamp aging box for irradiation, and the other 4 groups of specimens continued to be placed in a curing room with a temperature of 20±3°C and a humidity of 65±5% for curing. When the irradiation time was 0h, 100h, 300h, and 500h, compression tests were carried out on the irradiated specimens and the non-irradiated specimens of the same age, respectively. The test equipment used was a universal testing machine with a loading rate of 1mm / min. The appearance changes of the specimens were checked during the compression test.

5. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 4, characterized in that: In step 3, the method for constructing the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar includes the following steps in order: Step (i): saturate the cement emulsified asphalt mortar specimens with a curing age of 7 days, 14 days, and 28 days with water to constant weight, and take 0.2g of cement emulsified asphalt mortar from each saturated specimen for pore structure testing, use a low-field nuclear magnetic resonance imaging device to measure the transverse relaxation time of the pore fluid in the saturated specimen and the corresponding nuclear magnetic resonance signal amount, and process the data to obtain the relationship between the transverse relaxation time of the pore fluid and the pore radius; Step (ii): Through the nuclear magnetic resonance relaxation method, it can be obtained that the nuclear magnetic resonance signal is proportional to the water content of the saturated specimen under the same parameters. Then, the saturated specimen with known water content is tested by the physical drying weight loss method, and the corresponding relationship between the relaxation time peak area and the water mass in the cement emulsified asphalt mortar is established. The relationship between the signal amplitude and the pore volume is further fitted, and the signal amplitude is substituted into the relationship to complete the conversion of the signal amplitude and the pore volume; Step (iii): The pores inside the cement emulsified asphalt mortar are equivalent to the spheres in the fractal dimension calculation model. In the fractal dimension calculation model, there are n groups of pores with different diameters, namely, d i (i=1,2,3,......,n), the diameter of the pore is defined as the size of the sphere; according to the equivalent principle, the diameter is greater than or equal to d i The pore diameter is converted into d i Therefore, the minimum number of balls required to cover all pores can be counted as the equivalent number of pores, that is, N δi (i=1,2,3,......,n); based on a series of pore diameters and equivalent pore numbers [d1,N δ1 ],[d2,N δ2 ],.......,[d n ,N δn ], get d i With N δi The relationship between , which is the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar.

6. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 5, characterized in that: In step (a), the relationship between the transverse relaxation time of the pore fluid and the pore radius is: in Where, T2 is the transverse relaxation time of pore fluid, ms; T 2表面 ——Transverse relaxation time caused by surface relaxation, ms; ρ——surface relaxation rate, dimensionless; ——Specific surface area of ​​pores, m 2 / g; F s ——pore shape factor, dimensionless; r——pore radius, nm.

7. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 6, characterized in that: In step (ii), the relationship between the signal amplitude and the pore volume is: 7d: SA = 1480V - 575.59 14d: SA = 1480V - 575.59 28d: SA=1271.6V-101.64 (when hour) 28d: SA = 1480V-575.59 (when hour) Where, SA is the signal amplitude, dimensionless; V——pore volume, nm 3 .

8. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 7, characterized in that: In step (iii), the fractal dimension calculation model of the pore volume of cement emulsified asphalt mortar is lnN δ =Dln(1 / r)+C, Where, D is the fractal dimension of the pore volume of cement emulsified asphalt mortar, dimensionless; N δ ——equivalent pore number, pieces; r——pore radius, nm; C——constant, dimensionless.

9. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 8, characterized in that: In step 4, the method for constructing a neural network model for evaluating the performance of cement emulsified asphalt mortar includes the following steps in order: Step (A): using the amount of cement, the amount of emulsified asphalt, the fractal dimension of the pore volume of cement emulsified asphalt mortar, and the curing age as input parameters, setting the number of neurons in the input layer to four, using the compressive strength, elastic modulus, flexural strength, and weather resistance as output parameters, setting the number of neurons in the output layer to four, that is, constructing a neural network structure with four-parameter input and four-parameter output; Step (B): To eliminate the influence of different indicators and different dimensions, normalization is performed before training the neural network model; Step (C): In the neural network model, a smaller initial value of the weight is selected, the transfer function of the hidden layer neurons is an S-type transfer function, the transfer function of the output layer is a linear function, and the Trainlm training function is used. The number of training times is set to 10,000, the learning rate is set to 0.01, and the training target is a minimum error of 0.000001.

10. The method for evaluating the performance of cement emulsified asphalt mortar based on MFN fusion according to claim 9, characterized in that: In step five, a cement emulsified asphalt mortar sample is drilled every 100 m on the cement emulsified asphalt mortar layer on the side of the high-speed railway track. The cement emulsified asphalt mortar sample is cylindrical with a diameter of 5 mm and a height of 5 mm. Other input parameters include the amount of cement in the cement emulsified asphalt mortar sample, the amount of emulsified asphalt, and the time of on-site use.

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