Simulation monitoring full-scale experiment research method for root system layer separation diseases in vegetation covering accumulated snow environment
Patent Information
- Application Number
- CN202510787592.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-12
- Publication Date
- 2025-09-09
Smart Images
Figure CN120609990A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of earthen site protection, and in particular to a full-scale experimental research method for simulating and monitoring root layer separation disease in a vegetation-covered snow environment. Background Art
[0002] Many earthen sites in my country are located in semi-humid, seasonally frozen soil environments. These sites, affected by cold-region conditions such as vegetation cover and winter snow, are subject to long-term freeze-thaw cycles, the coupled effects of snow melt, and disturbance of vegetation roots. These sites are commonly threatened by root zone separation. This condition manifests itself as the interface between the vegetation cover and the underlying rammed earth walls gradually weakens due to frost heave and thaw erosion. This causes the root zone soil to separate under external forces such as gravity and wind, leading to surface uplift and structural instability, severely threatening the integrity and safe preservation of earthen sites.
[0003] Existing research often focuses on the single-factor mechanisms of freeze-thaw, snow accumulation, or vegetation, lacking a systematic analysis of the multi-factor coupling of "freeze-thaw-snow accumulation-vegetation," making it difficult to reveal the full evolutionary process of root stratum separation. Standard indoor tests or small-scale models are unable to realistically simulate the complex responses of full-scale earthen sites, especially the "microstructural damage-macroslip" interaction at the root stratum-wall interface. This results in a lack of accurate data support for disease prediction and prevention. Long-term dynamic monitoring of root stratum separation is scarce, and critical data such as water and heat transport and mechanical response during interface weakening are missing, making it difficult to establish a dynamic prediction model for disease evolution.
[0004] In view of this, there is an urgent need for a full-scale experimental research method for simulation monitoring of root layer separation diseases in vegetation-covered snow environments. Summary of the Invention
[0005] The purpose of the present invention is to provide a full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment, so as to solve the problems raised in the above background technology.
[0006] To achieve the above objectives, according to Figure 1 As shown, the present invention provides a full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment, comprising the following steps:
[0007] S1. Experimental site selection: Conduct a multi-factor comprehensive environmental survey around the site, including obtaining key parameters such as the annual sunshine hours, annual average temperature, maximum wind speed, annual wind direction, natural vegetation type, soil type and structural characteristics, and precipitation and snow accumulation patterns in the area. Combine historical meteorological data with on-site sampling and monitoring data, and select a representative, highly accessible area that does not affect the existing scenic area's view through parameter comparison and landscape coordination assessment methods as the experimental site. Use ring knife sampling and disturbance sampling methods to extract soil samples in the target area, conduct sampling and analysis on the soil at this location, and compare it with various indicators of the site soil, including specific gravity, particle size composition, liquid limit, plastic limit, salt content, and capillary rise height. Verify the similarity in physical and mechanical properties between the soil in this area and the original site's rammed earth material. At the same time, consider the impact of the experimental site on the scenic area and future planning to increase the rationality and feasibility of the site selection.
[0008] S2. Design of the experimental wall: The experimental wall was constructed according to the actual size and proportions of the original site wall. The structure included rammed steps, structural bedding, and a wall base accumulation structure. The width of the experimental wall was no less than 80 cm to allow for the independent deployment of sensors inside and outside the central axis. The rammed layer thickness was 7 cm, and the layers were wet-jointed to ensure consistency of the overall structure. Afterwards, drone scanning technology was used to verify the morphology of the constructed wall to ensure that the spatial scale and edge curvature of the experimental wall were consistent with the original site. The design of the experimental wall should fully consider the key elements of the original site, including the original site wall structure, its shape, size, and proportions. The thickness of the rammed layer affects the structural stability and physical properties of the experimental wall. The ramming process determines the wall density and internal structure, which is related to the experimental wall's response to diseases. The original site environment covers some aspects of climate, soil, and vegetation. Climate affects the physical and chemical changes of the wall, soil determines the properties of the wall material, and vegetation acts on the wall through its root system.
[0009] S3. Design of the monitoring system: The monitoring system is centered around high-resolution, high-frequency, multi-channel automatic data collection, covering meteorological factors, internal water, heat, and salt responses of the wall, surface vegetation, and snow evolution. Specifically:
[0010] The weather station is located in an unobstructed upwind location and uses an integrated micro-meteorological station with functions for measuring wind speed and direction, air temperature and humidity, light radiation, and rainfall and snowfall. Time-lapse cameras are placed on the south, north, and west walls to avoid image omissions, and dual modes of timed and triggered shooting are set. Multi-layer water, heat, and salt sensors (MTD15 model) are embedded inside the wall, arranged in three layers vertically and two rows horizontally to form a heat and moisture flux profile. The data acquisition frequency is set to every 5 minutes, and the imaging frequency is every 10 minutes, with image clarity of no less than 2K. The system is powered by wind and solar hybrid power generation, and a backup battery and remote monitoring module are installed to ensure continuous data transmission.
[0011] S4. Wall Construction: The rammed earth material for the experimental wall was determined to be sandy loam or silt loam based on sampling and analysis results. The moisture content of the selected soil material was adjusted to the optimal moisture content. Specifically, the compaction curve was determined through soil sample testing to ensure that the soil material achieved optimal density and stability during ramming. Ramming was carried out in layers, with each layer being 7 cm thick and the thickness error of the rammed layers not exceeding 0.2 cm. This ensured that the overall structure of the wall was uniform and stable. At the same time, the close connection between the layers was increased to form a solid whole.
[0012] To simulate a real-world environment, the top surface of the wall is covered with a 10cm thick layer of turf soil, and local perennial grass seeds are sown. The turf soil is covered with a uniform thickness, and the grass seeds are sown in a reasonable distribution to simulate the actual root growth process. At the bottom of the wall, a pile layer is set up that is consistent with the ground surface and compacted. The compacted pile layer needs to be cured for more than 10 days to prevent water seepage from interfering with the wall structure.
[0013] S5. Installation of monitoring system: The installation of sensors inside the wall is completed simultaneously with the tamping. Specifically, the cables need to be led out through the reserved channel and must be carefully sealed and waterproofed to prevent moisture intrusion. All data acquisition terminals must be centrally connected to a unified data cabinet, which is installed on the northeast side of the experimental field. This location should be convenient for receiving light and away from terrain obstructions to effectively prevent interference from external factors and increase the stability and reliability of the collected data. After the tamping of the experimental wall is completed, the external monitoring equipment is deployed. The external equipment includes 3 ATL3500 time-lapse photography cameras, which need to be set at different directions and angles. , to take fixed images of the wall; 1 integrated micro-meteorological station, installed at a height of 1m upwind of the prevailing wind direction, which can measure meteorological factors around the experimental wall, covering wind speed, wind direction, air temperature and humidity, light radiation, rainfall and snowfall; 1 set of panoramic monitoring equipment, installed on a high-level platform, covering the entire experimental field, and capable of comprehensively monitoring the overall operation of the experimental field; 1 set of wind-solar generators, with an output voltage of no less than 24V and an energy storage battery capacity of no less than 60Ah; 1 data acquisition cabinet with temperature control, waterproof and dustproof functions, and an internal UPS backup power supply with automatic switching capability during power outages;
[0014] S6. Calibration of the experimental site: All sensors are calibrated and tested before the experiment begins, including zero-point drift detection, time drift correction, and temperature stability testing. During the experiment, data is automatically uploaded daily, and single-point anomalies are identified and marked by the outlier factor model. A three-dimensional spatial interpolation method is used to generate a distribution map of water and heat changes in the wall, which is compared with the actual evolution process. Two micro-meteorological stations are set up at the edge of the site and compared with the data of the main meteorological station. The error does not exceed ±5% to be qualified. A unified time-space-equipment identification system is established to normalize the data and compensate for missing measurements to ensure data comparability. During the experimental site for 365 consecutive days, all modules of the system operate normally, and the uninterrupted monitoring data exceeds 24 hours. The system is determined to be stable and reliable for long-term monitoring and simulation research.
[0015] In terms of sensor calibration, before all monitoring equipment is installed, the accuracy and reliability of the sensors are tested one by one (each performance indicator of the sensor is tested in detail, including sensitivity, resolution, and linearity, to ensure that it meets the experimental requirements). Equipment that does not meet the requirements is replaced to ensure that the signal is stable, the data is normal, and the accuracy meets the standards. After each layer of tamping is completed, the sensor is promptly connected to the data acquisition instrument. After being connected to the data acquisition instrument, the changes in the data are monitored in real time. Through statistical analysis methods, the stability and consistency of the data are judged, and abnormal points are analyzed. If necessary, the equipment is replaced or a backup device is installed to ensure the continuity and reliability of the data.
[0016] In the continuity verification of system operation, a three-dimensional distribution map of temperature, humidity and stress field is generated based on measured data, and gradient analysis is used to verify the physical logic of the stress field distribution; a local outlier factor detection model is constructed, a 95% confidence threshold is set, outlier data points are automatically marked, and data reliability is identified; additional small weather stations are deployed in the weather station area, and synchronous comparisons are made with standard measuring instruments to verify the degree of fit between some parameters of temperature, humidity, wind speed, and light and the trend of changes in the real physical field. A spatiotemporal coordinate system for monitoring data is established to achieve data integration; compensation and correction methods are formulated for environmental interference factors to ensure that the sensors inside the experimental wall and the data from the external weather station are consistent in the spatiotemporal dimensions; for example, through the analysis of the three-dimensional distribution map of temperature, humidity and stress field; using the local outlier factor detection model, the data is deeply analyzed to identify outlier data points and improve data reliability;
[0017] In terms of the stability criteria for the experimental field, the performance requirements for the equipment are as follows: the sensors must output high-precision, stable and continuous data to reflect the temperature and humidity changes inside the experimental wall, and the monitoring results must be consistent with the theoretical distribution; cloud map analysis must verify the spatial coherence of the monitoring points and the full coverage of the data; the requirements for system linkage are as follows: the data from the weather station and time-lapse camera outside the wall must be consistent in time and space with the experimental wall monitoring system, and the physical phenomena recorded by the time-lapse photography must be mutually verified with the real-time sensor data to form a double data guarantee; energy supply requirements: the wind and solar integrated generator must be powered in real time, equipped with a battery as a backup power source, and automatically switch when power generation is insufficient to maintain the operation of the core equipment, so that data collection can be continuous and complete;
[0018] In addition, when actually conducting simulation detection of root layer separation diseases, the experimental field and experimental wall are first established through the above steps and the monitoring system is installed. During the experiment, various sensors collect real-time data on meteorological factors (including wind speed, wind direction, air temperature and humidity, light radiation, rainfall and snowfall), water, heat and salt response inside the wall (such as changes in temperature, humidity and salt content at different depths), surface vegetation (vegetation growth status, root disturbance on the wall) and snow evolution process (snow thickness, melting rate). The time-lapse camera regularly captures images of the wall, including changes in the root layer at the top of the wall, weathering conditions on the windward side, and the operating status of the entire experimental field. After data collection, it is uniformly connected to the data acquisition instrument, summarized and stored in local and remote servers, and data transmission is regularly uploaded to the database via the local area network. After obtaining preliminary monitoring results, the data is comprehensively processed and analyzed.
[0019] Compared with the prior art, the present invention has the following beneficial effects:
[0020] In the full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation-covered snow environment, by constructing a full-scale experimental field, some factors such as top vegetation coverage, thick snow loading and multi-cycle snowmelt erosion are integrated, and the physical simulation of the whole process of disease in a vegetation-covered snow environment is realized for the first time, filling the gap in multi-factor coupling research; an integrated monitoring system of "regional meteorology-wall surface disease-internal water and heat stress" is constructed, and high-precision sensors and time-lapse photography technology are used to simultaneously capture microscopic interface degradation and macroscopic slip characteristics, realizing continuous temporal and spatial tracking of disease evolution; the site selection, soil materials, tamping technology and vegetation transplantation are all based on the original site standards, so that the experimental conditions are consistent with the actual environment, and can be directly used for preventive protection of earthen sites, increasing the reliability of disease control for earthen sites in cold regions. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Figure 1 This is a flowchart of a full-scale experimental research method for simulating and monitoring root layer separation disease in a vegetation-covered snow environment according to the present invention;
[0022] Figure 2This is a schematic diagram of the site selection for the experimental site of the embodiment;
[0023] Figure 3 A schematic diagram of the external monitoring arrangement of an embodiment;
[0024] Figure 4 This is a schematic diagram of the wall monitoring layout in the embodiment;
[0025] Figure 5 Flowchart for making wall of embodiment. DETAILED DESCRIPTION
[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.
[0027] Example
[0028] according to Figure 1 As shown, the embodiment of the present invention provides a full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment, including the following steps:
[0029] S1. Experimental site selection: Conduct a multi-factor comprehensive environmental survey around the site, including obtaining key parameters such as the annual sunshine hours, annual average temperature, maximum wind speed, annual wind direction, natural vegetation type, soil type and structural characteristics, and precipitation and snow accumulation patterns in the area. Combine historical meteorological data with on-site sampling and monitoring data, and select a representative, highly accessible area that does not affect the existing scenic area's view through parameter comparison and landscape coordination assessment methods as the experimental site. Use ring knife sampling and disturbance sampling methods to extract soil samples in the target area, conduct sampling and analysis on the soil at this location, and compare it with various indicators of the site soil, including specific gravity, particle size composition, liquid limit, plastic limit, salt content, and capillary rise height. Verify the similarity in physical and mechanical properties between the soil in this area and the original site's rammed earth material. At the same time, consider the impact of the experimental site on the scenic area and future planning to increase the rationality and feasibility of the site selection.
[0030] Specifically, if Figure 2As shown in the figure, the test site was selected at 280m-320m south of the middle section of the north wall of the outer city of the ruins. This place is located in the vast grassland between the imperial city and the outer city of the ruins. The landscape is well coordinated and it will be easy to integrate into the scenic area planning in the future. It is also reasonably spaced from the ruins, which will not interfere with tourists' visits and will be convenient for professionals to visit. In addition, the site has the same light and temperature change patterns as the ruins, similar natural erosion and wind conditions, similar vegetation types and coverage, and similar soil properties. This can ensure that the test wall is in line with the ruins environment to the greatest extent, making the test results more reliable and effective.
[0031] S2. Design of the experimental wall: The experimental wall was constructed according to the actual size and proportions of the original site wall. The shape included rammed steps, structural bedding, and a wall base accumulation structure. In addition, the width of the experimental wall was no less than 80 cm to enable the independent deployment of sensors inside and outside the central axis. The rammed layer thickness was 7 cm, and the layers were wet-jointed to ensure consistency of the overall structure. Afterwards, drone scanning technology was used to verify the morphology of the constructed wall to ensure that the experimental wall was consistent with the original site in terms of spatial scale and edge curvature. The design of the experimental wall should fully consider the key elements of the original site, including the original site wall form, its shape, size, and proportion. The thickness of the rammed layer affects the structural stability and physical properties of the experimental wall. The ramming process determines the wall density and internal structure, which is related to the experimental wall's response to diseases. The original site environment covers some aspects of climate, soil, and vegetation. Climate affects the physical and chemical changes of the wall, soil determines the properties of the wall material, and vegetation acts on the wall through its root system.
[0032] S3. Design of the monitoring system: The monitoring system is centered around high-resolution, high-frequency, multi-channel automatic data collection, covering meteorological factors, internal water, heat, and salt responses of the wall, surface vegetation, and snow evolution. Specifically:
[0033] The weather station is located in an unobstructed upwind location and uses an integrated micro-meteorological station with functions for measuring wind speed and direction, air temperature and humidity, light radiation, and rainfall and snowfall. Time-lapse cameras are placed on the south, north, and west walls to avoid image omissions, and dual modes of timed and triggered shooting are set. Multi-layer water, heat, and salt sensors (MTD15 model) are embedded inside the wall, arranged in three layers vertically and two rows horizontally to form a heat and moisture flux profile. The data acquisition frequency is set to every 5 minutes, and the imaging frequency is every 10 minutes, with image clarity of no less than 2K. The system is powered by wind and solar hybrid power generation, and a backup battery and remote monitoring module are installed to ensure continuous data transmission.
[0034] In detail, Figure 3As shown in the figure, due to the frequent westerly and northwest winds in the experimental field, the layout of the environmental weather station is chosen to avoid the shadow area of the wall and in the upwind direction of the dominant wind direction of the experimental field, that is, in the northwest corner of the experimental field. The horizontal distance and vertical ground height between the weather station and the wall are greater than 1.5-2 times the wall height. A fully functional and high-precision ultrasonic integrated weather station is selected, which can meet the monitoring needs of multiple indicators of wind speed, wind direction, temperature and humidity in extreme temperature environments, and can conduct comprehensive and accurate monitoring of the local climate around the experimental wall. In terms of macro-phenomenon capture equipment, time-lapse cameras are arranged 2m away from the main body of the experimental wall on the north and south sides of the experimental wall to monitor the changes in the root layer at the top of the wall. A time-lapse camera is installed 4m away from the main body of the experimental wall to monitor the weathering of the entire windward side. A time-lapse camera is installed 5m away from the northwest-southeast diagonal of the experimental wall to monitor the weathering of the entire windward side. -6m, full-field monitoring time-lapse cameras are installed to monitor the operation of the entire experimental field, and 360° panoramic monitoring is installed under the full-field camera in the southeast corner to monitor changes inside and outside the test field; the wind-solar integrated generator, power box and data acquisition instrument cabinet are arranged in the northeast corner of the experimental field 6m away from the wall. The generator converts wind energy and light energy into electrical energy, which is connected to the data acquisition instrument and backup power supply after rectification to ensure stable power supply for the equipment. Each image monitoring device is connected to the power supply through a wire pipe, and a memory card is installed on the device as a basis for local storage; the data acquisition instrument and monitoring equipment have built-in network connection functions. Using the services provided by the communication operator, a local area network is built in the experimental field, and the data acquisition instrument and each monitoring device are connected to the network to transmit the collected data in a timely manner, realizing dynamic and continuous monitoring of changes on the outside of the wall; such as Figure 4 As shown in the figure, the sensors inside the wall use water, heat and salt sensors that integrate water and heat monitoring functions. They are symmetrically arranged inside the wall and the accumulation slope with the central axis of the wall as the reference; key and supplementary monitoring areas are divided, and the sensor density and layout are set differently according to the characteristics of different areas and the potential development of diseases, so as to accurately monitor the water and heat migration patterns inside the site under different light radiation and vegetation coverage conditions; in addition, by installing long-term photography fixed-point collection on the outside of the test wall, combined with acrylic rod rulers deeply embedded in the soil, auxiliary monitoring of wall surface weathering, vegetation growth and snow thickness changes, multiple means are coordinated to ensure that the monitoring system obtains data comprehensively and accurately, providing strong support for in-depth research on the evolution of wall diseases.
[0035] S4. Wall Construction: The rammed earth material for the experimental wall was determined to be sandy loam or silt loam based on sampling and analysis results. The moisture content of the selected soil material was adjusted to the optimal moisture content. Specifically, the compaction curve was determined through soil sample testing to ensure that the soil material achieved optimal density and stability during ramming. Ramming was carried out in layers, with each layer being 7 cm thick and the thickness error of the rammed layers not exceeding 0.2 cm. This ensured that the overall structure of the wall was uniform and stable. At the same time, the close connection between the layers was increased to form a solid whole.
[0036] To simulate a real-world environment, the top surface of the wall is covered with a 10cm thick layer of turf soil, and local perennial grass seeds are sown. The turf soil is covered with a uniform thickness, and the grass seeds are sown in a reasonable distribution to simulate the actual root growth process. At the bottom of the wall, a pile layer is set up that is consistent with the ground surface and compacted. The compacted pile layer needs to be cured for more than 10 days to prevent water seepage from interfering with the wall structure.
[0037] Specific implementation method: The particle size distribution and physical and mechanical properties of the soil used in the experiment should be highly similar to those of the ruins soil; Figure 5 As shown, the experimental soil was tested in detail to accurately determine its optimal moisture content, and the experimental soil was made with the optimal moisture content; in the selected experimental area, a solid wooden mold was used to build the main frame of the experimental wall (according to Figure 5 a); Before construction, the ground of the experimental area needs to be thoroughly weeded and leveled (according to Figure 5 c), remove the debris and uneven parts on the ground, and then use a flat-bottomed rammer to compact the ground foundation (according to Figure 5 d), providing a solid foundation for the tamping of the wall; during the tamping process, the wall is tamped according to the thickness of the tamping layer of the ruins wall. Figure 5 e), bury the sensor according to the designed position (according to Figure 5 b and Figure 5 f), after the wall loses water and becomes relatively stable, remove the mold (according to Figure 5 g), according to the size and shape of the main body, use tools to cut and trim the wall (according to Figure 5 h), control the appearance and size error of the wall to be no more than ±2cm, then, according to the actual shape of the site, cover the top of the wall with the turf dug out in blocks and tamp it down (according to Figure 5 i), the turf should be laid close to the top of the wall, and after compaction and cultivation, it should be watered regularly in the early stage (according to Figure 5 j), the grass can grow normally, making the wall highly similar to the original site in terms of material, structure and appearance, effectively simulating the state of the site under the natural vegetation-covered snow environment, and increasing the reliability of the experimental research object; the accumulation layer at the bottom of the test wall adopts the same ramming process as the wall (according to Figure 5 k), complete the turf cultivation, compaction and watering maintenance work to increase the consistency and reliability of the entire experimental wall.
[0038] S5. Installation of monitoring system: The installation of sensors inside the wall is completed simultaneously with the tamping. Specifically, the cables need to be led out through the reserved channels and must be carefully sealed and waterproofed to prevent moisture intrusion. All data acquisition terminals must be centrally connected to a unified data cabinet, which is installed on the northeast side of the experimental field. This location should be convenient for receiving light and away from terrain obstructions to effectively prevent interference from external factors and increase the stability and reliability of collected data. After the tamping of the experimental wall is completed, the external monitoring equipment is deployed. The external equipment includes 3 ATL3500 time-lapse cameras, which need to be set at different positions and angles to fix the wall image; 1 integrated micro-air A meteorological station, installed 1m upwind of the prevailing wind direction, can measure meteorological factors around the experimental wall, including wind speed, wind direction, air temperature and humidity, light radiation, and rainfall and snowfall. A panoramic monitoring device, installed on a high platform, covers the entire experimental field and can comprehensively monitor the overall operation of the experimental field. A wind and solar generator with an output voltage of no less than 24V and a storage battery capacity of no less than 60Ah is required. A data acquisition cabinet with temperature control, waterproof and dustproof functions, an internal UPS backup power supply, and automatic power-off switching capability ensures that the monitoring system can continue to operate normally in the event of a sudden power outage, thereby increasing the continuity of data collection work.
[0039] Specific implementation method: After the tamping of a single layer of wall is completed, install the MTD15 sensor according to the position of the sensor layout diagram; before installation, remove the tamping holes at the layout location, level the layout surface, use measuring tools to accurately measure and determine the placement of the sensor, straighten the wiring, ensure that the wiring is firm, and avoid damage caused by subsequent construction; then cover the soil to fix the sensor and its wiring. After completing the installation of all sensors on this layer, connect the sensor to the CR1000X data acquisition instrument and set the monitoring frequency to 5 minutes / time. After connection, the operating status of the sensor needs to be verified before proceeding with the tamping construction of the next layer. After the experimental wall was rammed earth, ATL3500 time-lapse cameras, integrated weather stations, panoramic image monitoring equipment, and wind-solar integrated generators were installed around the experimental wall according to the layout diagram of external monitoring equipment. The wind-solar integrated generator was placed in the northeast corner of the test site, and a data acquisition cabinet was installed under the generator. A CR1000X data acquisition instrument was used to collect and transmit test site monitoring data, and a power box was set up next to the generator to reserve power. After the installation of various devices, all monitoring equipment was connected to the data acquisition instrument, and the shooting interval of the time-lapse camera was set to every 10 minutes. The monitoring system constructed through such an installation process can monitor the experimental wall from multiple dimensions and in all directions, effectively obtain the change data of the wall in the vegetation-covered snow freeze-thaw environment, and provide solid and reliable data support for in-depth research on the spatiotemporal evolution of wall diseases in the vegetation-covered snow environment, effectively increasing the accuracy and reliability of the experimental results.
[0040] S6. Calibration of the experimental site: All sensors are calibrated and tested before the experiment begins, including zero-point drift detection, time drift correction, and temperature stability testing. During the experiment, data is automatically uploaded daily, and single-point anomalies are identified and marked by the outlier factor model. A three-dimensional spatial interpolation method is used to generate a distribution map of water and heat changes in the wall, which is compared with the actual evolution process. Two micro-meteorological stations are set up at the edge of the site and compared with the data of the main meteorological station. The error does not exceed ±5% to be qualified. A unified time-space-equipment identification system is established to normalize the data and compensate for missing measurements to ensure data comparability. During the experimental site for 365 consecutive days, all modules of the system operate normally, and the uninterrupted monitoring data exceeds 24 hours. The system is determined to be stable and reliable for long-term monitoring and simulation research.
[0041] In terms of sensor calibration, before all monitoring equipment is installed, the accuracy and reliability of the sensors are tested one by one (each performance indicator of the sensor is tested in detail, including sensitivity, resolution, and linearity, to ensure that it meets the experimental requirements). Equipment that does not meet the requirements is replaced to ensure that the signal is stable, the data is normal, and the accuracy meets the standards. After each layer of tamping is completed, the sensor is promptly connected to the data acquisition instrument. After being connected to the data acquisition instrument, the changes in the data are monitored in real time. Through statistical analysis methods, the stability and consistency of the data are judged, and abnormal points are analyzed. If necessary, the equipment is replaced or a backup device is installed to ensure the continuity and reliability of the data.
[0042] In the continuity check of system operation, a three-dimensional distribution map of temperature, humidity and stress field is generated based on the measured data, and gradient analysis is used to verify the physical logic of the stress field distribution; a local outlier factor detection model is constructed, a 95% confidence threshold is set, outlier data points are automatically marked, and data reliability is identified; additional small meteorological stations are deployed in the meteorological station area, and synchronous comparisons are made with standard measuring instruments to verify the degree of fit between some parameters of temperature, humidity, wind speed, and light and the trend of changes in the real physical field. A spatiotemporal coordinate system for monitoring data is established to achieve data integration; compensation and correction methods are formulated for environmental interference factors to ensure that the sensors inside the experimental wall and the data from the external meteorological station are consistent in the spatiotemporal dimensions; for example, by analyzing the three-dimensional distribution maps of temperature, humidity and stress field, the changes in the physical fields in different regions can be understood, and it can be determined whether the stress field distribution conforms to physical laws; a local outlier factor detection model is used to conduct in-depth analysis of the data, identify outlier data points, and improve data reliability;
[0043] In terms of the stability criteria of the experimental field, the performance requirements for the equipment are as follows: the sensor must output high-precision, stable and continuous data to reflect the temperature and humidity changes inside the experimental wall, and the monitoring results must be consistent with the theoretical distribution; cloud map analysis must verify the spatial coherence of the monitoring points and the full coverage of the data; for system linkage, the data from the weather station outside the wall and the time-lapse camera must be consistent in time and space with the experimental wall monitoring system, and the physical phenomena recorded by the time-lapse photography must be mutually verified with the real-time sensor data to form a double data guarantee; energy supply requirements: the wind and solar integrated generator must be powered in real time, equipped with a battery as a backup power supply, and automatically switch when power generation is insufficient to maintain the operation of the core equipment, so that data collection can be continuous and complete; long-term operation verification is a one-year continuous monitoring. If the data has no abnormal interruptions or obvious fluctuations, fully presents the dynamic changes of the experimental wall and the surrounding environment, and the system meets the design standards in terms of stability, reliability and linkage, then the experimental field is determined to be completed and used for long-term research;
[0044] Furthermore, when conducting actual simulation testing for root layer separation diseases, the experimental field and experimental wall were first established through the aforementioned steps, and a monitoring system was installed. During the experiment, various sensors collected real-time data on meteorological factors (including wind speed, wind direction, air temperature and humidity, light radiation, and rainfall and snowfall), the wall's internal water, heat, and salt response (such as changes in temperature, humidity, and salt content at different depths), surface vegetation (vegetation growth and root disturbances on the wall), and snow accumulation (snow thickness and melting rate). A time-lapse camera captured images of the wall at regular intervals, including changes in the root layer at the top of the wall, weathering on the windward side, and the operating status of the entire experimental field. After data collection, it was uniformly connected to a data logger and aggregated and stored on local and remote servers. Data transmission was regularly uploaded to a database via a local area network. After obtaining preliminary monitoring results, the data was comprehensively processed and analyzed, as detailed below:
[0045] First, data cleaning is performed. By setting data ranges and logical rules, invalid or abnormal data caused by sensor failures and communication anomalies are eliminated to improve data quality. Then, the monitoring data is interpolated and reconstructed. For data missing due to equipment failure or environmental interference, data from adjacent time points or spatial locations are used to perform interpolation calculations through algorithms (such as linear interpolation and spline interpolation) to construct a time-space unified multidimensional data structure, making the data continuous in time series and complete in spatial distribution.
[0046] Subsequently, multi-source fusion analysis is carried out based on the processed data: with the help of a visualization platform, a preliminary analysis of the collected time series data and image data is carried out. For example, a temperature gradient distribution map is generated for different areas of the wall to intuitively display the temperature distribution inside and outside the wall; a moisture migration trend map is drawn to analyze the movement trajectory of moisture inside the wall; through image recognition technology, the root disturbance impact area is identified to understand the effect of vegetation roots on the wall, so as to preliminarily judge the response mechanism of the wall under different environmental factors; specifically, physical modeling methods are used, combined with material mechanics and thermodynamics, to invert the stress-strain field inside the wall, evaluate the changes in internal wall stress caused by root growth and freeze-thaw effects, and then analyze the trend of root layer separation; through image sequence processing algorithms, such as using image difference methods to compare wall images at different time points, the changes in the wall surface are highlighted; texture features are extracted to analyze the degree and pattern of wall surface weathering; deep learning is used to assist in identification to accurately identify signs of vegetation disturbance, such as the impact of vegetation root growth and expansion on the wall surface;
[0047] Finally, a coupling model was established by combining some external conditions such as snowfall, sunlight, and wind direction. The interactions between various environmental factors were comprehensively considered, and the intensity of the role of each factor in the development of the disease was analyzed. Through the above comprehensive and in-depth analysis, an evolutionary path map of the root layer separation disease was finally formed, clearly showing the entire process from occurrence to development of the disease. At the same time, disease-sensitive areas were identified to provide precise intervention suggestions for site protection. For example, in disease-sensitive areas, the frequency of monitoring should be increased and targeted protective measures (such as strengthening walls and controlling vegetation growth) should be taken to effectively prevent and control root layer separation diseases and protect the integrity and safety of the site.
[0048] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.
Claims
1. A full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment, characterized by: The following steps are involved: S1. Experimental Site Selection: A comprehensive multi-factor environmental survey was conducted around the site. Combining historical meteorological and on-site monitoring data, the selected area was selected as the experimental site through parameter comparison and landscape coordination assessment. Soil samples were extracted using both the ring knife sampling method and the disturbance sampling method. S2. Design of the experimental wall: The experimental wall was constructed in accordance with the actual scale of the original ruins wall, with a structure that included rammed earth steps, structural bedding, and a wall foundation accumulation structure. UAV scanning technology was then used to verify the morphology of the completed wall. S3. Design of the Monitoring System: The monitoring system is centered around high-resolution, high-frequency, multi-channel automated data collection, covering meteorological factors, the water, heat, and salt response within the wall, surface vegetation, and the evolution of snow cover. The weather station is located in an unobstructed upwind location, with time-lapse cameras positioned on three walls and multiple layers of water, heat, and salt sensors embedded within the wall. S4. Wall Construction: The rammed earth material for the experimental wall was selected based on the sampling and analysis results. The ramming was carried out in layers, with each layer being 7 cm thick, no less than 80 cm wide, and with a thickness error of no more than 0.2 cm. The top surface was covered with 10 cm thick turf soil, and local perennial grass seeds were sown. The bottom was piled up at the same level as the ground surface, and the ramming and curing were carried out for more than 10 days. S5. Installation of monitoring system: The installation of sensors inside the wall is completed simultaneously with the tamping. After the tamping of the experimental wall is completed, the installation of external monitoring equipment is carried out; S6. Calibration of the experimental site: All sensors are calibrated and tested before the experiment begins. During the experiment, the data are automatically uploaded and anomalies are marked using the outlier factor model. A three-dimensional spatial interpolation method is used to generate a distribution map of water and heat changes in the wall and compare them. Two micro-meteorological stations are set up to compare data to determine whether the system is stable and reliable for long-term monitoring and simulation research.
2. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In S1, the multi-factor comprehensive environmental survey includes obtaining some key parameters in the region, including annual sunshine hours, annual average temperature, maximum wind speed, perennial wind direction, natural vegetation type, soil type and structural characteristics, and precipitation and snow accumulation patterns.
3. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In said S1, extracting soil samples includes sampling and analyzing the soil and comparing it with various indicators of the ruins soil. The various indicators include testing some parameters such as specific gravity, particle size composition, liquid limit, plastic limit, salt content, and capillary rise height to verify the similarity of the physical and mechanical properties of the soil in this area and the rammed earth material of the original ruins.
4. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In the S3, the weather station adopts an integrated micro-weather station, which has some functions of measuring wind speed and direction, air temperature and humidity, light radiation, and rainfall and snowfall; the three walls include the south, north and west walls.
5. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In S3, the multi-layer water, heat and salt sensors are arranged in three layers vertically and in two rows horizontally to form a heat and moisture flux profile. The multi-layer water, heat and salt sensors collect data from inside the wall at a frequency of once every 5 minutes and an image frequency of once every 10 minutes. The image clarity is not less than 2K. The system is powered by wind and solar complementary power generation, and a backup battery and a remote monitoring module are provided to ensure continuity of data transmission.
6. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In said S4, selecting the soil material includes determining whether the soil material is sandy loam or silt loam, adjusting its moisture content to an optimal moisture content, and specifically determining a compaction curve through soil sample testing so that the soil material can achieve optimal density and stability during tamping.
7. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In S5, the layout of sensors inside the wall includes leading out cables through reserved channels. After leading out, they must be carefully sealed and waterproofed. All data acquisition terminals must be centrally connected to a unified data cabinet, which is installed on the northeast side of the experimental site.
8. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In the S5, the external equipment includes three ATL3500 time-lapse cameras, which need to be set at different directions and angles; one integrated micro-meteorological station, installed at a height of 1m upwind of the prevailing wind direction; one set of panoramic monitoring equipment, installed on a high-level platform, covering the entire experimental field; one set of wind and solar generators, with an output voltage of not less than 24V and an energy storage battery capacity of not less than 60Ah; one data acquisition cabinet with temperature control, waterproof and dustproof functions, an internal UPS backup power supply, and the ability to automatically switch in the event of power failure.
9. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In S6, the calibration test includes zero drift detection, time drift correction and temperature stability test.
10. The full-scale experimental research method for simulation monitoring of root layer separation disease in a vegetation covered snow environment according to claim 1 is characterized in that: In the above S6, the micro-weather station establishes a unified time-space-equipment identification system, and the comparison data error does not exceed ±5%, and there is no interruption of more than 24 hours for 365 consecutive days.