Intelligent testing method for soil moisture content in museum collections of environmental cultural relics

Abstract

The present invention discloses an intelligent soil moisture content testing method for collection of environmental cultural relics, and relates to the field of intelligent testing technology. The method comprises: obtaining soil samples with externally acting consolidating agents, and stratifying the soil samples to determine the first soil layer and the second soil layer; constructing a soil simulation model; performing temperature testing on the soil samples, and obtaining the first soil layer test data sample and the second soil layer test data sample; collecting the original soil layer test data sample corresponding to the soil samples without the acting consolidating agent; performing consolidation impact analysis, and obtaining the consolidation-moisture content impact index sample; training the moisture content testing model according to the consolidation-moisture content impact index sample, and calling the moisture content testing model to predict and control soil cracking. The method solves the technical problem that the soil moisture content test in the prior art is not accurate and stable enough, and the soil is tested in layers by the consolidating agent, so as to achieve the technical effect of improving the accuracy and stability of the moisture content test.

Description

Technical Field

[0001] The invention relates to the field of intelligent testing technology, and in particular to an intelligent testing method for soil moisture content of cultural relics in a collection environment. Background Art

[0002] In museums, archaeological sites and the protection of historical and cultural heritage, the preservation environment of cultural relics is crucial to their long-term preservation and state maintenance. As an important part of the preservation environment of cultural relics, the moisture content of soil is one of the key factors affecting the stability and preservation state of cultural relics. The preservation environment of cultural relics usually faces various complex challenges, such as temperature and humidity changes, microbial erosion, chemical corrosion, etc. These factors may indirectly affect the cultural relics themselves by affecting the soil moisture content. Although traditional soil moisture test methods, such as weighing method and resistance method, can reflect the moisture content of soil to a certain extent, they often have problems such as long test cycle, complex operation and susceptibility to interference. In addition, these methods often ignore the effect of consolidating agents on soil moisture content, while consolidating agents are often used to reinforce soil in cultural relic protection to improve its stability and bearing capacity. The interaction between consolidating agents and soil will change the physical and chemical properties of soil, thereby affecting its moisture state, which may cause traditional test methods to fail to accurately reflect the true state of the cultural relic preservation environment. Summary of the invention

[0003] The embodiment of the present application provides an intelligent soil moisture content testing method for museum environmental cultural relics, which solves the technical problem that soil moisture content testing in the prior art is not accurate and stable enough.

[0004] In view of the above problems, an embodiment of the present application provides an intelligent testing method for soil moisture content of museum environmental cultural relics.

[0005] The present application embodiment provides an intelligent soil moisture content testing method for collection of environmental cultural relics, the method comprising:

[0006] A soil sample with an external consolidator is obtained, and the soil sample is layered to determine a first soil layer and a second soil layer, wherein the first soil layer is an unconsolidated inner soil layer, and the second soil layer is a consolidated outer soil layer; a soil simulation model of the soil sample is constructed; a temperature test sample of the collection environment is set, and the soil simulation model is called to perform a temperature test on the soil sample with the temperature test sample to obtain a first soil layer test data sample and a second soil layer test data sample; an original soil layer test data sample corresponding to the soil sample without the consolidator is collected; a consolidation influence analysis is performed based on the first soil layer test data sample, the second soil layer test data sample, and the original soil layer test data sample, and a consolidation-water content influence index sample is obtained; a water content test model is trained based on the consolidation-water content influence index sample, and the trained water content test model is called to perform soil cracking prediction and control.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] First, a soil sample with an external consolidating agent is obtained, and the soil sample is layered to determine the first soil layer and the second soil layer. The first soil layer is an unconsolidated inner soil layer, and the second soil layer is an outer soil layer with consolidation. Next, a soil simulation model of the soil sample is constructed. By setting the temperature test sample of the collection environment, the soil simulation model is called to perform a temperature test on the soil sample with the temperature test sample, and the first soil layer test data sample and the second soil layer test data sample are obtained. Next, the original soil layer test data sample corresponding to the soil sample without the consolidating agent is collected. Then, the consolidation impact analysis is performed based on the first soil layer test data sample, the second soil layer test data sample and the original soil layer test data sample, and the consolidation-water content impact index sample is obtained. Finally, the water content test model is trained based on the consolidation-water content impact index sample, and the trained water content test model is called to predict and control soil cracking. The technical problem that the soil water content test in the prior art is not accurate and stable is solved, and the soil is layered tested by the consolidating agent to achieve the technical effect of improving the accuracy and stability of the water content test. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 A schematic flow chart of an intelligent soil moisture content testing method for museum environmental cultural relics provided in an embodiment of the present application.

[0011] Figure 2 A schematic diagram of a process for predicting and controlling soil cracking by calling a trained moisture content test model in the intelligent soil moisture content test method for collection of environmental cultural relics provided in an embodiment of the present application. DETAILED DESCRIPTION

[0012] The embodiment of the present application solves the technical problem that the soil moisture content test in the prior art is not accurate and stable enough by providing an intelligent soil moisture content test method for museum environmental cultural relics.

[0013] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0014] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0015] Embodiment 1

[0016] like Figure 1 As shown, the embodiment of the present application provides an intelligent testing method for soil moisture content of cultural relics in a collection environment, wherein the method comprises:

[0017] A soil sample with an externally acting consolidating agent is obtained, and the soil sample is layered to determine a first soil layer and a second soil layer, wherein the first soil layer is an unconsolidated inner soil layer, and the second soil layer is a consolidated outer soil layer.

[0018] Soil samples with consolidators were obtained from the collection environment, and the soil samples were carefully stratified to distinguish the unconsolidated inner soil layer (first soil layer) and the consolidated outer soil layer (second soil layer). Specifically, the soil samples were stratified. Since the external consolidator usually acts on the outer layer of the soil, the boundary between the inner and outer soil layers can be determined by observation, touch or instrumentation. The first part is the unconsolidated inner soil layer (first soil layer), which is usually located in the center or inside of the sample and is not affected or less affected by the consolidator; the second part is the consolidated outer soil layer (second soil layer), which is located on the outside of the sample and is affected by the consolidator, and the bonding force between soil particles is enhanced. By obtaining soil samples with external consolidators and dividing them into two parts, the unconsolidated inner soil layer and the consolidated outer soil layer, the effect of the consolidator on the moisture content of the inner and outer soil layers can be obtained.

[0019] Furthermore, obtaining a soil sample of an externally acting consolidating agent, the method further comprises:

[0020] The soil type distribution of the target collection area is obtained, and a plurality of soil simulation models are set according to the soil type distribution, wherein each soil simulation model corresponds to a soil type; and the plurality of soil simulation models are integrated to perform soil control on the target collection area.

[0021] Preferably, soil samples are collected at different locations in the target collection area to ensure that the sampling points cover all possible soil types, and the collected soil samples are sent to the laboratory for analysis, including soil particle size analysis, chemical composition analysis, physical property measurement, etc., to determine the accurate soil type. According to the analysis results, the soil type distribution of the target collection area is obtained. According to the soil type distribution, multiple soil simulation models are set, wherein each soil simulation model corresponds to a soil type, and the soil simulation model can accurately simulate the physical, chemical and mechanical properties of various soil types. Multiple soil simulation models are integrated into a unified management and control system to ensure data sharing and collaborative work between the models. The integrated management and control system is used to monitor the soil in the target collection area in real time. The stability and safety of the soil are evaluated by collecting and analyzing various sensor data (such as temperature, humidity, displacement, etc.).

[0022] A soil simulation model of the soil sample is constructed.

[0023] Based on the soil samples, a soil simulation model is constructed using modeling software. The soil simulation model can reflect the temperature distribution and changes inside the soil, as well as the impact of temperature on soil properties (such as strength, deformation, etc.). The constructed soil simulation model is verified by comparing it with experimental data or other reliable data. If there is a large difference between the model prediction results and the actual situation, the model needs to be adjusted and optimized.

[0024] A temperature test sample of the collection environment is set, and the soil simulation model is called to perform a temperature test on the soil sample using the temperature test sample to obtain a first soil layer test data sample and a second soil layer test data sample.

[0025] Define a series of temperature test samples based on the actual temperature change or expected temperature change range of the target collection area. These temperature test samples cover the possible minimum temperature, maximum temperature, and the rate and mode of temperature change. For example, design the temperature test samples as a series of discrete temperature values ​​or a continuous temperature change curve. Use simulation software or platform, take the defined temperature test samples as input conditions, call the soil simulation model, and set appropriate boundary conditions and initial conditions according to the requirements of the model to simulate the state of the soil in the actual environment. Run the soil simulation model to simulate the response of the soil under different temperature test samples, monitor the temperature distribution, heat conduction and heat convection of the soil during the simulation process, and record relevant data. Extract the test data samples of the first soil layer (unconsolidated inner soil layer) and the test data samples of the second soil layer (consolidated outer soil layer) from the simulation results. The test data samples of the first soil layer and the second soil layer include temperature change and moisture content data.

[0026] Collect the original soil layer test data samples corresponding to the soil samples without consolidation agent.

[0027] In order to conduct comparative analysis, it is necessary to collect original soil layer test data samples corresponding to soil samples without consolidation agent. The original soil layer test data samples will be used as benchmark data to evaluate the specific impact of consolidation agent on soil moisture content.

[0028] A consolidation impact analysis is performed based on the first soil layer test data sample, the second soil layer test data sample and the original soil layer test data sample to obtain a consolidation-water content impact index sample.

[0029] Based on the acquired test data samples of the first soil layer, the second soil layer and the original soil layer, the consolidation impact analysis is performed. By comparing the data differences of different soil layers, the influence of the consolidating agent on the soil moisture content is evaluated, and the consolidation-moisture content impact index sample is obtained. Specifically, by calculating the difference between the second soil layer (after consolidation) and the original soil layer, for example, the change in moisture content after consolidation can be calculated as: moisture content = (second soil layer moisture content - original soil layer moisture content) / original soil layer moisture content * 100%.

[0030] Further, performing consolidation influence analysis according to the first soil layer test data sample, the second soil layer test data sample and the original soil layer test data sample includes:

[0031] The first soil layer test data sample and the original soil layer test data sample are compared to obtain a difference test data set; consolidation influence analysis is performed based on the difference test data set to obtain the influence of moisture content stability, moisture content change rate and moisture content spatial distribution; analysis is performed based on the moisture content stability influence, moisture content change rate influence and moisture content spatial distribution influence to obtain a consolidation-moisture content influence index sample.

[0032] The test data samples of the first soil layer (unconsolidated inner soil layer) and the test data samples of the original soil layer are compared. The key parameter for comparison is the moisture content, because it directly reflects the moisture condition of the soil layer, and consolidation treatment often affects the moisture of the soil layer. For each pair of compared data (original soil layer and first soil layer), the difference in moisture content is calculated. All calculated difference values ​​are sorted into a difference test data set, which will be used for subsequent consolidation impact analysis. Analyze the trend of moisture content change over time in the difference test data set. If the difference value fluctuates greatly, it means that the consolidation treatment has a greater impact on the stability of moisture content; otherwise, the impact is small. Calculate the rate of change of moisture content difference over time in the difference test data set, which can be obtained by linear fitting. The magnitude of the change rate directly reflects the impact of consolidation on the speed of moisture content change. Analyze the spatial distribution of moisture content differences at different locations (or depths) to obtain the impact of consolidation on the distribution of moisture content inside the soil layer. According to the impact of moisture content stability, the impact of moisture content change rate and the impact of moisture content spatial distribution, the consolidation-moisture content impact index sample is obtained. The sample of consolidation-moisture content influence indicators includes the specific way and degree of influence of consolidation on moisture content.

[0033] Furthermore, the method further comprises:

[0034] A thickness test sample is set, wherein the thickness test sample is a second soil layer of different thickness; based on the thickness test sample, a first soil layer test data sample set and a second soil layer test data sample set are obtained; according to the first soil layer test data sample set and the second soil layer test data sample set, the consolidation-water content influencing index sample is optimized.

[0035] In order to optimize the consolidation-water content influence index sample, it is necessary to set the second soil layer of different thicknesses as thickness test samples and obtain the corresponding test data based on these samples. Specifically, determine the different thickness ranges of the second soil layer (the soil layer after consolidation). For each selected thickness, prepare the corresponding test samples, and these samples have the same initial conditions (such as water content, density, etc.) for comparison. For each thickness test sample, a corresponding unconsolidated first soil layer (inner soil layer) test data sample is required. Test each second soil layer (the soil layer after consolidation) of different thicknesses to obtain relevant data including water content, mechanical properties, etc. Ensure the accuracy and consistency of the data. According to the test data sample set of the first soil layer and the second soil layer, analyze the effect of consolidation on water content at different thicknesses, which can be achieved by comparing the water content before and after consolidation at different thicknesses. Based on the above analysis results, the existing consolidation-water content influence index samples are optimized. For example, if it is found that thickness has a significant effect on water content stability, a factor reflecting the thickness factor can be added to the index.

[0036] Furthermore, the method for setting a thickness test sample further includes:

[0037] Collect consolidation property information of the consolidating agent, including consolidating agent type and consolidating agent concentration; obtain soil property information of the soil sample, including soil material and soil molecular particle size; perform consolidation diffusion analysis based on the consolidation property information and the soil property information to obtain a consolidation diffusion index; perform diffusion distribution processing on the thickness test sample according to the consolidation diffusion index, and output the processed thickness test sample.

[0038] Preferably, the consolidation property information of the consolidator is collected, including the type of consolidator and the concentration of the consolidator. Among them, different types of consolidators may have different chemical properties and mechanisms of action, and the concentration of the consolidator directly affects the diffusion speed and effect of the consolidator in the soil. The soil property information of the soil sample is obtained, including the soil material and the molecular particle size of the soil. Among them, the absorption and reaction ability of soils of different materials to the consolidator may be different; the molecular particle size of the soil determines the pore structure and permeability of the soil, which in turn affects the diffusion effect of the consolidator. Combined with the consolidation property information of the consolidator and the soil property information of the soil sample, a consolidation diffusion analysis is performed. Through analysis, the parameters such as the diffusion ability, diffusion speed and diffusion range of the consolidator in the soil are evaluated, and the consolidation diffusion index is calculated accordingly. Using the obtained consolidation diffusion index, the diffusion distribution processing of the thickness test sample is carried out by simulating the diffusion process of the consolidator in the actual environment. According to the diffusion speed and range of the consolidating agent, the distribution of the consolidating agent in the test samples of different thicknesses is adjusted to ensure that the consolidating agent can be evenly distributed in the soil in practical applications. The thickness test samples after the diffusion distribution treatment are marked and recorded, including the distribution of the consolidating agent after treatment and the possible diffusion effect. Through the above process, the diffusion characteristics of the consolidating agent in the soil can be obtained more accurately, and the diffusion distribution treatment of the thickness test samples can be carried out accordingly, so as to ensure that the consolidating agent can give full play to its consolidation effect in practical applications.

[0039] Furthermore, after collecting the consolidation property information of the consolidating agent, the method further includes:

[0040] According to the consolidation property information of the consolidating agent, a failure temperature threshold is obtained, wherein the failure temperature threshold is a temperature boundary value that characterizes the failure of the consolidating agent; and a temperature test sample is set according to the failure temperature threshold as a constraint condition.

[0041] Preferably, according to the consolidation property information of the consolidating agent, a failure temperature threshold is obtained from big data, and the failure temperature threshold is a temperature boundary value that characterizes the failure of the consolidating agent. According to the failure temperature threshold, a series of temperature test samples are set. These temperature test samples cover the normal working temperature of the consolidating agent and the range close to the failure temperature, so as to evaluate the performance of the consolidating agent under different temperature conditions.

[0042] A moisture content test model is trained according to the consolidation-moisture content influence index sample, and the trained moisture content test model is called to perform soil cracking prediction and control.

[0043] Consolidation-water content influencing index samples, including consolidating agent type, concentration, soil material, molecular particle size and corresponding water content data. Select appropriate machine learning or deep learning models according to the characteristics of the problem and the nature of the data. For example, if the data set is small and the features are simple, you can choose a linear regression or decision tree model; if the data set is large and the features are complex, you can consider using models such as neural networks or random forests. Divide the consolidation-water content influencing index samples into training sets and test sets, use the training set data to train the water content test model, and optimize the model performance by adjusting the model's hyperparameters. During the training process, you can use cross-validation and other techniques to evaluate the generalization ability of the model. Use the test set data to evaluate the performance of the trained model. Common evaluation indicators include mean square error (MSE), root mean square error (RMSE), determination coefficient (R²), etc. If the performance of the model does not meet the requirements, you can adjust the model structure or hyperparameters, and then retrain and evaluate. Call the trained water content test model, input new consolidating agent and soil property information, and the model will output the predicted water content. Based on the predicted moisture content, soil cracking is predicted and controlled to prevent soil cracking due to insufficient soil moisture content.

[0044] Furthermore, if Figure 2 As shown, the trained moisture content test model is called to predict and control soil cracking. The method includes:

[0045] Record a moisture content test data set of the soil to be tested, and construct a first moisture content change distribution according to the moisture content test data set; collect the consolidator parameters of the soil to be tested; call the trained moisture content test model to obtain the consolidation-moisture content real-time impact index according to the consolidator parameters; and perform soil cracking prediction and control on the first moisture content change distribution according to the consolidation-moisture content real-time impact index.

[0046] At different time points and / or different spatial locations (such as different depths of the soil), record the moisture content test data of the soil to be tested to ensure the accuracy and reliability of the data. Multiple measurements may be required to obtain the average value or reduce the error. These moisture content data are sorted according to time series or spatial distribution to construct an initial moisture content test data set. According to the moisture content test data set, the trend of moisture content change over time or space is analyzed, and statistical methods or visualization tools (such as charts, images, etc.) are used to present this change trend, and the first moisture content change distribution is constructed. Before predicting the moisture content, it is necessary to collect the parameters of the consolidating agent used in the soil to be tested, including the type, concentration, addition amount, and addition time of the consolidating agent. The collected consolidating agent parameters are used as input to call the trained moisture content test model. The moisture content test model will output the real-time impact index of consolidation-moisture content based on these parameters and the previously learned consolidation-moisture content influence law. The real-time impact index of consolidation-moisture content reflects the real-time influence of the consolidating agent on the moisture content change. According to the real-time impact index of consolidation-water content, the distribution of the first water content change is predicted and adjusted. If the model predicts that the consolidator will cause a significant change in water content, then corresponding control measures need to be taken to optimize or stabilize the water content, including adjusting the parameters of the consolidator (such as concentration, addition amount, etc.), changing the construction method, increasing the monitoring frequency, etc. After implementing the control measures, it is necessary to continue to monitor the changes in water content and adjust and optimize the control measures according to the actual situation. For example, soil cracking warning, water maintenance reminder, etc.

[0047] Furthermore, the soil cracking prediction and control is performed on the moisture content change distribution according to the consolidation-moisture content real-time impact index, and the method includes:

[0048] The first moisture content change distribution is optimized according to the consolidation-moisture content real-time impact index, and a second moisture content change distribution is output; the soil moisture content abnormal probability is predicted for the second moisture content change distribution based on the Markov chain, and a time series window under the expected abnormal probability is obtained; according to the time series window, a predicted moisture content of the soil to be tested is generated; when the predicted moisture content is less than the preset moisture content, soil cracking reminder information is generated.

[0049] Preferably, the distribution of moisture content change is optimized, and the abnormal probability of soil moisture content is predicted based on the Markov chain, and finally the soil cracking reminder information is generated. Specifically, the consolidation-moisture content real-time impact index is used to optimize the first moisture content change distribution, including the correction of the moisture content change trend, combined with the influence of the consolidating agent on the moisture content, and the moisture content change under the action of the consolidating agent is predicted. By correcting the moisture content change trend, the second moisture content change distribution is output, and the second moisture content change distribution more accurately reflects the moisture content change under the action of the consolidating agent. Markov chain is a probability model for predicting future states, which assumes that the future state is only related to the current state and has nothing to do with the past state. The second moisture content change distribution is converted into a state transition probability matrix of the Markov chain, and the state transition probability matrix describes the probability of transferring from one moisture content state to another moisture content state. Using the Markov chain prediction method, the moisture content state that reaches the expected abnormal probability at a certain point in the future is calculated. Here, the abnormal probability can be set according to engineering requirements or safety standards. Through calculation, the time series window under the expected abnormal probability is obtained, that is, in which time period in the future, the water content has a high probability of reaching or exceeding the set abnormal value. According to the time series window, the predicted water content of the soil to be tested is generated. According to the actual situation, a preset water content is set to represent the limit of the minimum water content of the soil. If the predicted water content is less than the preset water content, a soil cracking reminder message is generated. These reminder messages are sent to relevant personnel in an appropriate manner (such as SMS, email, report, etc.) so that timely actions can be taken to ensure the stability and safety of the soil. Through the above process, the distribution of water content changes can be optimized according to the real-time impact index of consolidation-water content, and the Markov chain can be used to predict the abnormal probability of soil water content, and finally generate soil cracking reminder information, providing strong support for the management and maintenance of the soil.

[0050] In summary, the embodiments of the present application have at least the following technical effects:

[0051] First, a soil sample with an external consolidating agent is obtained, and the soil sample is layered to determine the first soil layer and the second soil layer. The first soil layer is an unconsolidated inner soil layer, and the second soil layer is an outer soil layer with consolidation. Next, a soil simulation model of the soil sample is constructed. By setting the temperature test sample of the collection environment, the soil simulation model is called to perform a temperature test on the soil sample with the temperature test sample, and the first soil layer test data sample and the second soil layer test data sample are obtained. Next, the original soil layer test data sample corresponding to the soil sample without the consolidating agent is collected. Then, the consolidation impact analysis is performed based on the first soil layer test data sample, the second soil layer test data sample and the original soil layer test data sample, and the consolidation-water content impact index sample is obtained. Finally, the water content test model is trained based on the consolidation-water content impact index sample, and the trained water content test model is called to predict and control soil cracking. The technical problem that the soil water content test in the prior art is not accurate and stable is solved, and the soil is layered tested by the consolidating agent to achieve the technical effect of improving the accuracy and stability of the water content test.

[0052] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0054] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An intelligent soil moisture content testing method for collection of environmental cultural relics, characterized in that: The method comprises: Obtaining a soil sample with an externally acting consolidating agent, and stratifying the soil sample to determine a first soil layer and a second soil layer, wherein the first soil layer is an unconsolidated inner soil layer, and the second soil layer is a consolidated outer soil layer; constructing a soil simulation model of the soil sample; Setting a temperature test sample of the collection environment, calling the soil simulation model to perform a temperature test on the soil sample using the temperature test sample, and obtaining a first soil layer test data sample and a second soil layer test data sample; Collect the original soil layer test data samples corresponding to the soil samples without consolidation agent; Perform consolidation influence analysis based on the first soil layer test data sample, the second soil layer test data sample and the original soil layer test data sample to obtain a consolidation-water content influence index sample; Training a moisture content test model according to the consolidation-moisture content influencing index sample, and calling the trained moisture content test model to predict and control soil cracking; Call the trained moisture content test model to predict and control soil cracking. The methods include: Recording a moisture content test data set of the soil to be tested, and constructing a first moisture content change distribution according to the moisture content test data set; Collecting the consolidating agent parameters of the soil to be tested; Calling the trained moisture content test model to obtain the real-time impact index of consolidation-moisture content according to the consolidating agent parameters; Perform soil cracking prediction and control on the first moisture content change distribution according to the consolidation-moisture content real-time impact index; The soil cracking prediction and control is performed on the first moisture content change distribution according to the consolidation-moisture content real-time impact index, and the method includes: Optimizing the first moisture content change distribution according to the consolidation-moisture content real-time impact index, and outputting a second moisture content change distribution; Based on the Markov chain, the soil moisture content abnormal probability is predicted for the second moisture content change distribution, and a time series window under the expected abnormal probability is obtained; Generating a predicted moisture content of the soil body to be tested according to the time series window; When the predicted moisture content is less than the preset moisture content, generating soil cracking warning information; Performing consolidation influence analysis according to the first soil layer test data sample, the second soil layer test data sample and the original soil layer test data sample includes: Compare the first soil layer test data sample with the original soil layer test data sample to obtain a difference test data set; Perform consolidation impact analysis based on the difference test data set to obtain the impact of moisture content stability, moisture content change rate and moisture content spatial distribution; According to the influence of moisture content stability, moisture content change rate and moisture content spatial distribution, an analysis is performed to obtain a sample of consolidation-moisture content influence indicators.

2. The intelligent soil moisture content testing method for collection of environmental cultural relics according to claim 1 is characterized in that: The method further comprises: Setting a thickness test sample, wherein the thickness test sample is a second soil layer of different thickness; According to the thickness test samples, a first soil layer test data sample set and a second soil layer test data sample set are obtained; According to the first soil layer test data sample set and the second soil layer test data sample set, the consolidation-water content influencing index sample is optimized.

3. The intelligent soil moisture content testing method for collection of environmental cultural relics according to claim 2 is characterized in that: The method for setting a thickness test sample further includes: Collecting the consolidation property information of the consolidating agent, including the type of consolidating agent and the concentration of the consolidating agent; Obtaining soil property information of the soil sample, including soil material and soil molecular particle size; Performing consolidation diffusion analysis according to the consolidation property information and the soil property information to obtain a consolidation diffusion index; The thickness test sample is subjected to diffusion distribution processing according to the consolidation diffusion index, and the processed thickness test sample is output.

4. The intelligent soil moisture content testing method for collection of environmental cultural relics according to claim 3 is characterized in that: After collecting the consolidation property information of the consolidating agent, the method further includes: According to the consolidation property information of the consolidating agent, a failure temperature threshold is obtained, wherein the failure temperature threshold is a temperature boundary value indicating the failure of the consolidating agent; A temperature test sample is set according to the failure temperature threshold as a constraint condition.

5. The intelligent soil moisture content testing method for collection of environmental cultural relics according to claim 1, characterized in that: Obtaining a soil sample of an externally acting consolidating agent, the method further comprises: Obtaining soil type distribution in the target collection area, and setting a plurality of soil simulation models according to the soil type distribution, wherein each soil simulation model corresponds to a soil type; The multiple soil simulation models are integrated to perform soil control on the target collection area.

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