Method and system for analyzing stability of soil aggregate

Abstract

The invention provides a soil aggregate stability analysis method and system, and relates to the technical field of soil quality evaluation.The method includes the steps that after drip irrigation water added with a fluorescent tracer agent is adopted for irrigating soil in a root zone under a film, dry screening is conducted on the soil, and an aggregate with the fluorescent tracer agent after dry screening is obtained and recorded as a target aggregate; loading the mixed fertilizer liquid into the target aggregate round by round, obtaining a permeation signal of the target aggregate under each loading round, determining a stage of the target aggregate under each loading round based on the permeation signal, and setting an instability condition for each type of target aggregate; and continuously loading the target aggregate until the instability condition is met, deriving the loading round times when the target aggregate is unstable, comparing the loading round times with the preset life loading round times, and judging that the stability of the target aggregate is qualified if the loading round times when the target aggregate is unstable are greater than the preset life loading round times.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of soil quality evaluation, in particular to a soil aggregate stability analysis method and system. BACKGROUND

[0002] As the basic unit of soil structure, the stability of soil aggregate directly affects the pore structure, water infiltration, nutrient retention and erosion resistance of soil. At present, the methods for evaluating the stability of soil aggregate mostly rely on traditional wet sieving method, dry sieving method or simulated rainfall test. Although these methods are simple to operate, they are often difficult to dynamically and quantitatively reflect the progressive destabilization process of aggregate under continuous external force. Especially for the response mechanism of soil aggregate under irrigation, fertilization and other agricultural management measures, the existing technology lacks correlation analysis between the microstructure changes in the aggregate and the external fluid infiltration behavior. In addition, the existing methods usually ignore the signal feature extraction and type division in the aggregate destabilization process, which leads to insufficient understanding of the stability mechanism of the aggregate and limits the accuracy and practicality of the evaluation results.

[0003] The above information disclosed in the background section is only intended to strengthen the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0004] The purpose of the present application is to provide a soil aggregate stability analysis method and system to solve the problems raised in the background.

[0005] To achieve the above purpose, the present application provides the following technical solutions: A soil aggregate stability analysis method, the specific steps include: Step 1: After irrigating the soil under the root zone of the film with drip irrigation water added with a fluorescent tracer, dry screening is performed to obtain aggregate with fluorescent tracer after dry screening, which is denoted as target aggregate; Step 2: Load mixed fertilizer liquid into the target aggregate in rounds, and obtain the infiltration signal of the target aggregate under each loading round, the infiltration signal including flux-resistance response signal, micro-aggregate peeling signal and flux path reconstruction signal; Step 3: Determine the stage of the target aggregate under each loading round based on the infiltration signal, which includes skeleton destabilization stage, progressive erosion stage, functional degradation stage or other stages, and set destabilization conditions for the target aggregate in each stage; Step 4: continuously loading the target aggregate until the destabilization condition is met, deriving the loading wheel number when the target aggregate is destabilized, and comparing it with the preset service life loading wheel number, if the loading wheel number when the target aggregate is destabilized is greater than the preset service life loading wheel number, it is judged that the target aggregate stability is qualified.

[0006] Further, the sub-membrane root zone soil refers to the soil body within the vertical depth range of 5-20 cm below the center line of the drip irrigation belt; The soil body is dry screened using a 2mm screen sleeve, and if the retained aggregate in the screen sleeve has fluorescent tracer on its surface, the retained aggregate is referred to as the aggregate with fluorescent tracer after dry screening.

[0007] Further, the logic for obtaining the infiltration signal of each loading wheel is to use a micro-infiltration device to make the mixed fertilizer solution pass through the target aggregate from top to bottom, and to obtain the volume of the mixed fertilizer solution passing through the target aggregate at each loading wheel, referred to as the flux of the mixed solution, the mean and variance of the flow rate of the mixed fertilizer solution at the bottom end of the target aggregate during each loading wheel, the pressure at the top and bottom ends of the target aggregate at the last moment of each loading wheel, and the reduced mass of the target aggregate at the last moment of each loading wheel. For each loading wheel, the flux-resistance response coefficient is calculated based on the flux of the mixed fertilizer solution at the loading wheel and the pressure at the top and bottom ends of the target aggregate at the last moment of the loading wheel, referred to as the flux-resistance response signal of the target aggregate at the loading wheel. Based on the flux of the mixed fertilizer solution at each loading wheel and the reduced mass of the target aggregate at the last moment of each loading wheel, the aggregate stripping rate is calculated, referred to as the micro-aggregate stripping signal. Based on the flux of the mixed fertilizer solution at each loading wheel and the mean and variance of the flow rate of the mixed fertilizer solution at the bottom end of the target aggregate during each loading wheel, the flux path reconstruction coefficient is calculated, referred to as the flux path reconstruction signal.

[0008] Further, the logic for calculating the flux-resistance response coefficient is to calculate the pressure difference at the top and bottom ends of the target aggregate at the last moment of the loading wheel, and to divide the difference by the flux of the mixed fertilizer solution at the loading wheel to obtain the flux-resistance response coefficient.

[0009] Further, the logic for calculating the aggregate stripping rate is to divide the reduced mass of the target aggregate at the last moment of the loading wheel by the flux of the mixed fertilizer solution at the loading wheel to obtain the aggregate stripping rate.

[0010] Further, the logic for calculating the flux path reconstruction coefficient is as follows: the velocity variance of the mixed fertilizer solution at the bottom of the aggregate in each loading cycle is divided by the mean to obtain the velocity variation coefficient in that loading cycle. The velocity variation coefficient of the previous loading cycle is subtracted from the velocity variation coefficient of the previous loading cycle, and the result of the subtraction is divided by the velocity variation coefficient of the previous loading cycle to obtain the flux path reconstruction coefficient.

[0011] Furthermore, the logic for determining the stage of the target aggregate in each loading round is as follows: normalize the flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient, and construct a column vector from the normalized flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient for each loading round. Following the chronological order, the stages of the target aggregate under the first three loading rounds are referred to as other stages. Starting from the fourth loading round, for each loading round, the column vectors of this loading round and the two loading rounds before it are used to construct a flux feature matrix. The eigenvalues ​​and corresponding eigenvectors of the flux matrix are calculated, and the eigenvector corresponding to the largest eigenvalue is obtained. The eigenvector corresponding to each component in the column vector of this loading round is calculated. If the absolute difference between the flux-resistance response coefficient and the corresponding component in the eigenvector is the largest, then the stage of the target aggregate under this loading round is the skeletal instability stage. If the absolute difference between the aggregate stripping rate and the corresponding component in the eigenvector is the largest, then the stage of the target aggregate under this loading round is the progressive erosion stage. If the absolute difference between the flux path reconstruction coefficient and the corresponding component in the eigenvector is the largest, then the stage of the target aggregate under this loading round is the functional degradation stage. If there is more than one maximum absolute difference, the target aggregate will be in another stage in this loading round.

[0012] Furthermore, the logic for setting the instability condition is as follows: the relative difference between the flux-resistance response coefficient and the flux-resistance response coefficient of the previous loading cycle is called the rate of change of the flux-resistance response coefficient; the relative difference between the aggregate stripping rate and the aggregate stripping rate of the previous loading cycle is called the rate of change of the aggregate stripping rate; and the relative difference between the flux path reconstruction coefficient and the flux path reconstruction coefficient of the previous loading cycle is called the rate of change of the flux path reconstruction coefficient. For the flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient, set corresponding thresholds and corresponding rate of change thresholds respectively; The basic instability condition is that at least one of the flux-resistance response coefficient, agglomerate stripping rate, and flux path reconstruction coefficient is greater than the corresponding threshold. For target aggregates at other stages, their instability condition is set as the basic instability condition. For target aggregates in the skeletal instability stage, the instability condition is set as follows: either the basic instability condition is met or the rate of change of the flux-resistance response coefficient is greater than the corresponding flux-resistance response coefficient change rate threshold. For target aggregates in the progressive erosion stage, their instability condition is set as follows: either the basic instability condition is met or the rate of change of the aggregate peeling rate is greater than the corresponding threshold for the rate of change of the aggregate peeling rate. For target aggregates in the functional degradation stage, their instability condition is set as follows: either the basic instability condition is met or the rate of change of the flux path reconstruction coefficient is greater than the corresponding flux path reconstruction coefficient rate of change threshold.

[0013] This invention further provides an analysis system for soil aggregate stability, the system being used in the aforementioned method for analyzing soil aggregate stability, specifically comprising: The screening module is used to dry screen the soil in the root zone under the film after irrigating it with drip irrigation water containing fluorescent tracers and to obtain aggregates containing fluorescent tracers after dry screening, which are recorded as target aggregates. The feature extraction module is used to load the mixed fertilizer solution into the target aggregate in rounds and obtain the permeation signal of the target aggregate in each loading round. The permeation signal includes flux-resistance response signal, micro-aggregate stripping signal and flux path reconstruction signal. The classification and judgment module is used to determine the stage of the target aggregate under each loading round based on the penetration signal. It includes the skeleton instability stage, the progressive erosion stage, the functional degradation stage or other stages, and sets the instability conditions for the target aggregate under each stage. The pass / fail judgment module is used to continuously load the target aggregate until the instability condition is met, output the number of loading cycles when the target aggregate becomes unstable, and compare it with the preset lifetime loading cycle number. If the number of loading cycles when the instability occurs is greater than the preset lifetime loading cycle number, the stability of the target aggregate is judged to be qualified.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention achieves precise capture and analysis of the dynamic response process of soil aggregates under simulated irrigation and fertilization environments by introducing a method combining fluorescent tracer labeling and multi-signal permeability monitoring. By extracting flux-resistance response signals, micro-aggregate stripping signals, and flux path reconstruction signals, the system identifies the type and stage of aggregate instability, thereby enabling quantitative evaluation of aggregate stability under continuous loading. This method not only improves the timeliness and accuracy of aggregate stability evaluation but also provides a scientific basis for soil structure optimization and irrigation and fertilization management, contributing to the advancement of sustainable agricultural development and soil health management technologies. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 The curve showing the variation of the loading cycle with the flux-resistance response coefficient; Figure 3 The curve shows the change in agglomerate stripping rate as a function of flux-resistance response coefficient; Figure 4 The curve showing the variation of flux path reconstruction coefficient with flux-resistance response coefficient; Figure 5 This is a schematic diagram of the overall system structure of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0017] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0018] Example: Please see Figures 1-5 The present invention provides a technical solution: A method for analyzing the stability of soil aggregates, comprising the following steps: Step 1: After irrigating the root zone soil under the film with drip irrigation water containing fluorescent tracer, dry sieve the soil and obtain the aggregates containing fluorescent tracer after dry sieve, which are recorded as target aggregates; Furthermore, the soil in the root zone under the film refers to the soil within a vertical depth range of 5–20 cm below the center line of the drip irrigation tape; in this embodiment, 2 kg of the soil is taken and dry-sieved.

[0019] In subsurface drip irrigation, the transport of water and nutrients is mainly concentrated in the moist zone below the drip tape, especially within a depth of 5–20 cm from the centerline of the drip tape. This is the area where root activity is most frequent and water and nutrient exchange is most active. Analyzing the soil in this area can more realistically and typically reflect the impact of drip irrigation on aggregate stability.

[0020] The soil is dry-sieved using a 2mm sieve. If the surface of the aggregates retained in the sieve contains a fluorescent tracer, the retained aggregates are called aggregates containing a fluorescent tracer after dry sieving.

[0021] Fluorescent tracers are substances that fluoresce under ultraviolet or blue light. When added to drip irrigation water, they migrate with the water and adsorb onto the surface of soil particles in the wetting path. Since soil irrigation is required, fluorescent tracers that do not affect soil properties and decompose automatically over time should be selected.

[0022] Step 2: Load the mixed fertilizer solution into the target aggregate in rounds and obtain the permeation signal of the target aggregate in each loading round. The permeation signal includes the flux-resistance response signal, the micro-aggregate stripping signal and the flux path reconstruction signal. Furthermore, the loading cycles are time intervals with equal time intervals; The logic for obtaining the permeation signal for each loading round is as follows: A micro-permeation device is used to allow the mixed fertilizer solution to pass through the target aggregate from top to bottom. The volume of the mixed fertilizer solution passing through the target aggregate in each loading round is obtained, in ml, and is called the flux of the mixed solution. At the outlet of the micro-permeation device, a calibrated container is set up, and the volume inside the container before and after each loading round is recorded. The difference between the volumes before and after loading is calculated; this difference is the flux of the mixed solution. The mean and variance of the flow velocity of the mixed fertilizer solution at the bottom of the target aggregate during each loading round are also measured, in ml. The flow rate is m / s. At the outlet of the permeation chamber, a laser Doppler velocimeter or an image-based particle velocimeter system is also arranged to collect the flow rate of the mixed fertilizer solution at time intervals. The flow rates of all mixed fertilizer solutions collected in one loading cycle are analyzed to obtain the mean and variance of the flow rates of the mixed fertilizer solution. The pressure at the top and bottom of the target agglomerate at the last moment of each loading cycle is measured in Pa, and the mass reduction of the target agglomerate at the last moment of each loading cycle is measured in g. Pressure sensors are arranged at the bottom center and top center of the agglomerate to collect the pressure at the arrangement location.

[0023] For each loading cycle, the flux-resistance response coefficient is calculated based on the flux of the mixed fertilizer solution in that loading cycle and the pressure at the top and bottom of the target agglomerates at the last moment of that loading cycle. This coefficient is called the flux-resistance response signal of the target agglomerates in that loading cycle. Furthermore, the logic for calculating the flux-resistance response coefficient is as follows: calculate the pressure difference between the top and bottom of the target aggregate at the last moment of the loading cycle, and divide this difference by the flux of the mixed fertilizer solution in that loading cycle to obtain the flux-resistance response coefficient. The flux-resistance response coefficient reflects the pressure difference that the fluid needs to overcome to pass through the aggregate under a unit flux. Essentially, it reflects the unobstructedness of the pore channels and the structural integrity of the aggregate. The "skeleton" of the aggregate mainly refers to the stable three-dimensional network formed by relatively coarse particles such as sand and powder connected and supported by cementing substances such as organic matter, clay, root exudates, and mycelium. A stable and complete skeleton will form a pore system with a reasonable pore size distribution and low tortuosity, allowing water to flow smoothly, resulting in a low and stable flux-resistance response coefficient. If the flux-resistance response coefficient is high, it indicates that the pressure difference that the fluid needs to overcome to pass through the aggregate is large, which is usually related to the decrease in porosity and the increase in tortuosity within the aggregate. These phenomena are all manifestations of skeleton loosening.

[0024] The agglomerate stripping rate, known as the microagglomerate stripping signal, is calculated based on the flux of the mixed fertilizer solution at the last moment of each loading cycle and the reduction in target agglomerates at the end of each loading cycle. The logic for calculating the agglomerate stripping rate is as follows: the mass reduction of target agglomerates at the end of each loading cycle is divided by the flux of the mixed fertilizer solution in that cycle. The agglomerate stripping rate reflects the mass lost by the agglomerates per unit volume of fluid erosion; it directly quantifies the agglomerates' ability to resist external erosion and dispersion. A higher value indicates poorer erosion resistance. This means that microparticles or small agglomerates on the agglomerate surface are more easily carried away by the water flow, leading to an increasingly loose outer structure of the agglomerates, continuously weakening the binding force, and constant erosion of the agglomerates. In severe cases, this phenomenon can even cause the agglomerates to disintegrate directly.

[0025] The flux path reconstruction coefficient, known as the flux path reconstruction signal, is calculated based on the flux of the mixed fertilizer solution in each loading round, the mean and variance of the flow velocity of the mixed fertilizer solution at the bottom of the target aggregate during each loading round.

[0026] The logic for calculating the flux path reconstruction coefficient is as follows: The velocity variance of the mixed fertilizer solution at the bottom of the aggregate in each loading cycle is divided by the mean to obtain the velocity variation coefficient for that loading cycle. The velocity variation coefficient of the previous loading cycle is subtracted from this coefficient, and the result is divided by the velocity variation coefficient of the previous loading cycle to obtain the flux path reconstruction coefficient. The flux path reconstruction coefficient reflects the dynamic evolution and reconstruction process of the dominant flow paths within the aggregate. It characterizes the change in the "disorder" or "uniformity" of the water flow distribution within the aggregate. A functionally stable aggregate has a complex but relatively homogeneous internal pore network, allowing water to flow in a relatively dispersed and stable manner, resulting in a low and stable velocity variation coefficient. At this point, it can homogenize water potential and buffer solute transport. A higher value indicates that the flow path is undergoing drastic reorganization. A lower value means that the previously relatively uniform flow field has been broken, leading to extremely uneven velocity distribution; the function of transporting water and nutrients is directly degraded.

[0027] Step 3: Determine the stage of the target aggregate under each loading round based on the penetration signal. This includes the skeleton instability stage, the progressive erosion stage, the functional degradation stage, or other stages, and set instability conditions for the target aggregate under each stage. Furthermore, the logic for determining the stage of the target aggregate in each loading round is as follows: normalize the flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient, and construct a column vector from the normalized flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient for each loading round. Following the chronological order, the stages of the target aggregates in the first three loading rounds are referred to as other stages. Starting from the fourth loading round, for each loading round, the column vectors of the loading round and the two loading rounds before it are used to construct a flux feature matrix. The eigenvalues ​​and corresponding eigenvectors of the flux matrix are calculated, and the eigenvector corresponding to the largest eigenvalue is obtained.

[0028] The largest eigenvalue represents the strength of the most significant and energetic pattern (principal component) in the data change or distribution within this three-round time window. The eigenvector corresponding to this largest eigenvalue defines what this strongest pattern is. It is a three-dimensional vector, whose three components correspond to the weights or contributions of the flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient, respectively, in the three observation dimensions.

[0029] Calculate the absolute difference between each component in the column vector of the loading cycle and the corresponding component in the feature vector. If the absolute difference between the flux-resistance response coefficient and the corresponding component in the feature vector is the largest, then the target agglomerate is in the skeletal instability stage under the loading cycle. If the absolute difference between the agglomerate stripping rate and the corresponding component in the feature vector is the largest, then the target agglomerate is in the progressive erosion stage under the loading cycle. If the absolute difference between the flux path reconstruction coefficient and the corresponding component in the feature vector is the largest, then the target agglomerate is in the functional degradation stage under the loading cycle. Since the previous text has already performed normalization, the coefficients compared here are all normalized coefficients.

[0030] The largest eigenvector represents the dominant pattern (i.e., the "background trend") of the recent aggregate state evolution. Calculating the absolute difference between the current signal and this vector is to identify which physical process has experienced the most significant "abnormal deviation" at that moment. This deviation signifies a sudden change in the dominant dynamic mechanism of the system—a sharp deviation in the drag response indicates critical instability of the skeletal structure, a prominent deviation in the peeling rate indicates that accelerated surface erosion has become the main cause, and a significant deviation in the path reconstruction coefficient points to a turbulent degradation of the internal flow field function. Therefore, by detecting the point of maximum deviation from the recent trend, the algorithm can accurately capture the transition moments of different dominant mechanisms during aggregate instability, thereby achieving dynamic discrimination of its destructive stage.

[0031] If there is more than one maximum absolute difference, it indicates that the aforementioned dominant mechanism does not exist, and the target aggregate is in another stage under this loading round.

[0032] Furthermore, the logic for setting the instability condition is as follows: the relative difference between the flux-resistance response coefficient and the flux-resistance response coefficient of the previous loading cycle is called the rate of change of the flux-resistance response coefficient; the relative difference between the aggregate stripping rate and the aggregate stripping rate of the previous loading cycle is called the rate of change of the aggregate stripping rate; and the relative difference between the flux path reconstruction coefficient and the flux path reconstruction coefficient of the previous loading cycle is called the rate of change of the flux path reconstruction coefficient. For the flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient, corresponding thresholds and corresponding rate of change thresholds are set respectively. The corresponding thresholds and rate of change thresholds can be determined by inviting experts in the field to conduct demonstration and analysis on the flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient calculated by the method in this application, and to give relevant thresholds in combination with the specific local soil conditions. This is the prior art and will not be elaborated here.

[0033] The existence of at least one of the flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient exceeding its corresponding threshold is designated as a fundamental instability condition. This fundamental instability condition (threshold determination) constitutes the first line of defense. It sets absolute performance thresholds for each of the three core coefficients (flux-resistance response coefficient, aggregate stripping rate, and flux path reconstruction coefficient). This is analogous to setting safety limits for parameters such as temperature and vibration of machinery. When any coefficient exceeds its threshold, regardless of the current stage, instability is directly identified. This ensures that the method can capture the most typical and common deterioration states—for example, when the resistance coefficient exceeds the threshold, it indicates that permeability has deteriorated to an unacceptable level; when the stripping rate exceeds the threshold, it means that the risk of nutrient loss is too high.

[0034] The instability conditions in other stages are the basic instability conditions; since no single factor clearly dominates in other stages, their instability conditions are set as the basic instability conditions.

[0035] For target aggregates in the skeletal instability stage, the instability condition is set as follows: either the basic instability condition is met or the rate of change of the flux-resistance response coefficient is greater than the corresponding flux-resistance response coefficient change rate threshold. The dominant condition in the skeletal instability stage is that when the rate of change of the flux-resistance response coefficient exceeds its specific threshold, skeletal instability is often manifested as a sharp increase in resistance, which means structural collapse; the soil aggregates lose stability.

[0036] For target aggregates in the progressive erosion stage, the instability condition is set as follows: either the basic instability condition is met, or the rate of change of aggregate stripping rate exceeds the corresponding threshold for the rate of change of aggregate stripping rate. In the progressive erosion stage, the material in soil aggregates is continuously eroded and lost, becoming dominant. When the rate of change of aggregate stripping rate exceeds the corresponding threshold for the rate of change of aggregate stripping rate, the erosion process is self-reinforcing, deviating from a relatively linear or slow loss pattern and entering a state of accelerated deterioration. The soil aggregate stability deteriorates into uncontrolled behavior.

[0037] For target aggregates in the functional degradation stage, their instability condition is set as follows: either the basic instability condition is met or the rate of change of the flux path reconstruction coefficient is greater than the corresponding flux path reconstruction coefficient rate of change threshold; the phenomenon corresponding to the flux path reconstruction coefficient is dominant in the functional degradation stage, and the rate of change of the flux path reconstruction coefficient is greater than the corresponding flux path reconstruction coefficient rate of change threshold. This indicates that the internal flow field is undergoing drastic, nonlinear reorganization. This usually means that the microstructure network inside the aggregate that originally supported its buffering and homogenization functions is rapidly failing, causing the water flow to be forced to concentrate in a few constantly changing and unstable paths. In this state, even if the aggregate's mass (stripping rate) and overall resistance have not yet reached the basic instability threshold, its core ecological functions as a "water and nutrient carrier"—such as homogenizing water potential, slowly releasing nutrients, and maintaining the stability of the root zone microenvironment—are on the verge of collapse.

[0038] This application subjected the screened aggregates to 20 rounds of trial loading; please refer to [link to relevant documentation]. Figures 2-4 Please see Figure 2 , Figure 2 The curve showing the variation of the flux-resistance response coefficient with the number of loading cycles. Figure 3 The curve shows the change in agglomerate stripping rate as a function of flux-resistance response coefficient. Figure 4 The curve shows the variation of the flux path reconstruction coefficient with the flux-resistance response coefficient.

[0039] Step 4: Continuously load the target aggregate until the instability condition is met. Derive the number of loading cycles when the target aggregate becomes unstable and compare it with the preset lifetime loading cycle number. If the number of loading cycles when the instability occurs is greater than the preset lifetime loading cycle number, the stability of the target aggregate is deemed acceptable.

[0040] The preset lifetime loading cycle can be achieved using existing technology. Soil samples can be collected from multiple locations in non-irrigated areas. For each sample, steps 2-4 are performed to obtain the number of loading cycles required to achieve instability. The average value is then calculated. Based on actual needs, a certain percentage of the average number of loading cycles is taken as the lifetime loading cycle number. In this example, since the soil aggregates to be analyzed have undergone multiple irrigation cycles, equivalent to multiple loading cycles as described in this application, judging soil stability is mainly for better soil management. Therefore, it is necessary to issue an early warning before the soil aggregates are about to become unstable. According to the investigation, in this embodiment, the execution time of the soil instability improvement strategy is usually 5%-8% of the average value. To allow sufficient response time, this embodiment takes 10% of the average number of loading cycles as the lifetime loading cycle number. If there are stricter soil stability requirements, the percentage can be increased.

[0041] Please see Figure 5The present invention further provides an analysis system for soil aggregate stability, the system being used in the aforementioned method for analyzing soil aggregate stability, specifically comprising: The screening module is used to dry screen the soil in the root zone under the film after irrigating it with drip irrigation water containing fluorescent tracers and to obtain aggregates containing fluorescent tracers after dry screening, which are recorded as target aggregates. The feature extraction module is used to load the mixed fertilizer solution into the target aggregate in rounds and obtain the permeation signal of the target aggregate in each loading round. The permeation signal includes flux-resistance response signal, micro-aggregate stripping signal and flux path reconstruction signal. The classification and judgment module is used to determine the stage of the target aggregate under each loading round based on the penetration signal. It includes the skeleton instability stage, the progressive erosion stage, the functional degradation stage or other stages, and sets the instability conditions for the target aggregate under each stage. The pass / fail judgment module is used to continuously load the target aggregate until the instability condition is met, output the number of loading cycles when the target aggregate becomes unstable, and compare it with the preset lifetime loading cycle number. If the number of loading cycles when the instability occurs is greater than the preset lifetime loading cycle number, the stability of the target aggregate is judged to be qualified.

[0042] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0043] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0044] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0045] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that cannot be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. An analysis method for soil aggregate stability, characterized by, The specific steps include: Step 1: After irrigating the sub-membrane root zone soil with drip irrigation water added with a fluorescent tracer, dry screening is performed to obtain fluorescent tracer-containing aggregates after dry screening, denoted as target aggregates; Step 2: loading mixed fertilizer solution into the target aggregates in each round, and obtaining the penetration signal of the target aggregates under each loading round, the penetration signal including flux-resistance response signal, micro-aggregate peeling signal and flux path reconstruction signal; Step 3: determining the stage of the target aggregates under each loading round based on the penetration signal, which includes being divided into skeleton instability stage, gradual erosion stage, functional degradation stage or other stages, and setting instability conditions for the target aggregates in each stage; Step 4: continuously loading the target aggregates until the instability conditions are met, deriving the loading round number when the target aggregates are unstable, and comparing it with the preset life loading round number, if the loading round number when the target aggregates are unstable is greater than the preset life loading round number, it is judged that the stability of the target aggregates is qualified.

2. The method of soil aggregate stability analysis according to claim 1, characterized in that: The sub-membrane root zone soil refers to the soil body within the vertical depth range of 5-20 cm below the center line of the drip irrigation belt; The soil body is dry screened using a 2mm screen sleeve, and if the fluorescent tracer exists on the surface of the retained aggregates in the screen sleeve, the retained aggregates are referred to as fluorescent tracer-containing aggregates after dry screening.

3. The method of claim 1, wherein the method is used to analyze the stability of soil aggregates. The logic for obtaining the penetration signal of each loading round is: using a micro-infiltration device, the mixed fertilizer solution passes through the target aggregates from top to bottom, and the volume of the mixed fertilizer solution passing through the target aggregates under each loading round is obtained, referred to as the flux of the mixed solution, the mean and variance of the flow rate of the mixed fertilizer solution at the bottom end of the target aggregates during each loading round, the pressure at the top and bottom ends of the target aggregates at the last moment of each loading round, and the reduced mass of the target aggregates at the last moment of each loading round; For each loading round, the flux-resistance response coefficient is calculated based on the flux of the mixed fertilizer solution under the loading round and the pressure at the top and bottom ends of the target aggregates at the last moment of the loading round, referred to as the flux-resistance response signal of the target aggregates under the loading round; Based on the flux of the mixed fertilizer solution under each loading round and the reduced mass of the target aggregates at the last moment of each loading round, the aggregate peeling rate is calculated, referred to as the micro-aggregate peeling signal; Based on the flux of the mixed fertilizer solution under each loading round, the mean and variance of the flow rate of the mixed fertilizer solution at the bottom end of the target aggregates during each loading round, the flux path reconstruction coefficient is calculated, referred to as the flux path reconstruction signal.

4. The method of soil aggregate stability analysis according to claim 3, wherein: The logic for calculating the flux-resistance response coefficient is: calculating the pressure difference at the top and bottom ends of the target aggregates at the last moment of the loading round, dividing the difference by the flux of the mixed fertilizer solution under the loading round to obtain the flux-resistance response coefficient.

5. The method of claim 3, wherein the soil aggregate stability is determined by: The logic for calculating the aggregate peeling rate is: dividing the reduced mass of the target aggregates at the last moment of the loading round by the flux of the mixed fertilizer solution under the loading round to obtain the aggregate peeling rate.

6. The method of claim 3, wherein the soil aggregate stability is determined by: The logic of calculating the flux path reconstruction coefficient is: the variance of the flow rate of the mixture of the bottom of the agglomerate under each loading round is divided by the average value to obtain the flow rate variation coefficient under the loading round, the flow rate variation coefficient under the loading round is subtracted from the flow rate variation coefficient of the previous loading round, and the result of the subtraction is divided by the flow rate variation coefficient of the previous loading round to obtain the flux path reconstruction coefficient.

7. The method of claim 3, wherein the soil aggregate stability is determined by: The logic of determining the stage of the target agglomerate under each loading round is: normalizing the flux-resistance response coefficient, the agglomerate stripping rate and the flux path reconstruction coefficient, and forming a column vector of the normalized flux-resistance response coefficient, the agglomerate stripping rate and the flux path reconstruction coefficient under each loading round; In time sequence, the stage of the target agglomerate under the first three loading rounds is called other stages, and starting from the fourth loading round, for each loading round, the column vectors of the loading round and the previous two loading rounds form a flux feature matrix, the eigenvalues and corresponding eigenvectors of the flux matrix are calculated, the eigenvector corresponding to the maximum eigenvalue is obtained, the absolute difference between each component in the column vector of the loading round and the corresponding component in the eigenvector is calculated, if the absolute difference between the flux-resistance response coefficient and the corresponding component in the eigenvector is the largest, the stage of the target agglomerate under the loading round is the skeleton instability stage, if the absolute difference between the agglomerate stripping rate and the corresponding component in the eigenvector is the largest, the stage of the target agglomerate under the loading round is the gradual erosion stage, and if the absolute difference between the flux path reconstruction coefficient and the corresponding component in the eigenvector is the largest, the stage of the target agglomerate under the loading round is the functional degradation stage; If there is more than one maximum value of the absolute difference, the stage of the target agglomerate under the loading round is other stages.

8. The method for analyzing the stability of soil aggregates according to claim 1, characterized in that: The logic of setting the instability condition is: the relative difference between the flux-resistance response coefficient and the flux-resistance response coefficient of the previous loading round is called the change rate of the flux-resistance response coefficient, the relative difference between the agglomerate stripping rate and the agglomerate stripping rate of the previous loading round is called the change rate of the agglomerate stripping rate, and the relative difference between the flux path reconstruction coefficient and the flux path reconstruction coefficient of the previous loading round is called the change rate of the flux path reconstruction coefficient. For the flux-resistance response coefficient, the agglomerate stripping rate and the flux path reconstruction coefficient, corresponding threshold values and corresponding change rate threshold values are set respectively. At least one of the flux-resistance response coefficient, the agglomerate stripping rate and the flux path reconstruction coefficient is greater than the corresponding threshold value as the basic instability condition. For the target agglomerate in other stages, the instability condition is set as the basic instability condition. For the target agglomerate in the skeleton instability stage, the instability condition is set as: meeting the basic instability condition or the change rate of the flux-resistance response coefficient being greater than the corresponding flux-resistance response coefficient change rate threshold value. For the target agglomerate in the gradual erosion stage, the instability condition is set as: meeting the basic instability condition or the change rate of the agglomerate stripping rate being greater than the corresponding agglomerate stripping rate change rate threshold value. For the target aggregate in the functional degradation stage, the destabilization condition is set as: meeting the basic destabilization condition or the change rate of the flux path reconstruction coefficient is greater than the corresponding flux path reconstruction coefficient change rate threshold.

9. An analysis system for soil aggregate stability, characterized by: The system is used to implement the soil aggregate stability analysis method of any one of claims 1-8, and specifically comprises: The action screening module is used to irrigate the soil in the film root zone with drip irrigation water added with a fluorescent tracer, dry-screen the soil after irrigation, and obtain aggregates containing the fluorescent tracer after dry screening, which are recorded as target aggregates. The feature extraction module is used to load mixed fertilizer liquid into the target aggregates round by round, and obtain the penetration signals of the target aggregates at each loading round, which include flux-resistance response signals, micro-aggregate peeling signals, and flux path reconstruction signals. The classification and judgment module is used to determine the stage of the target aggregates at each loading round based on the penetration signals, which includes being divided into skeleton destabilization stage, gradual erosion stage, functional degradation stage, or other stages, and setting a destabilization condition for the target aggregates in each stage. The qualified judgment module is used to continuously load the target aggregates until the destabilization condition is met, derive the loading round number when the target aggregates are destabilized, and compare it with the preset service life loading round number, and if the loading round number when the target aggregates are destabilized is greater than the preset service life loading round number, the target aggregate stability is determined to be qualified.

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