Construction method of ecological large-gradient planting roof and soil fixing system

Abstract

The application discloses a kind of construction methods of ecological simulation large slope planting roof and soil fixation system, belong to slope roof structure construction technical field.The application solves the existing ecological simulation planting roof form-finding difficulty, and the problem of soil sliding and loss, by setting secondary structure network on structure roof, form grid isolation unit, avoid the cumulative sliding force of soil body too large, realize building completion surface form-finding;Through setting EPS light filling between secondary structure network, effectively reduce roof load, better adapt to large slope multi-curved surface roof slope finding;Through setting integrated cable anchor, geocell and cable on secondary structure network beam column, instead of traditional retaining plate, more effectively provide anti-sliding effect, and will not damage waterproof layer, at the same time avoid the problem that traditional retaining plate position drainage is not smooth;Compared with traditional slope roof anti-skid system generally applicable to the roof below 50 degrees, the application can adapt to the complex roof of 50 degrees and above slope.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of construction of sloping roof structure, in particular to a construction method of a bionic large-slope planted roof and a soil fixation system. BACKGROUND

[0002] Modern large-scale sports venues increasingly become a landmark existence that exhibits the city spirit and modern architectural aesthetics. In order to pursue unique visual effects and bionic aesthetics, designers widely use streamlined blocks and complex geometric shapes to shape bionic roof structures with large slopes and multiple curved surfaces. Traditional primary structures (such as main trusses and net racks) mainly bear mechanical loads, and their shapes are often based on structural efficiency optimization, which is significantly different from the complex, smooth, and high-precision completed surface shapes of architectural design. This great deviation in shape means that it is impossible to directly achieve a smooth, continuous, and design-intended architectural completed surface on a rough primary structure. Therefore, accurate shape finding of the architectural completed surface is a key problem faced by current complex architectural structures.

[0003] On the other hand, for planted sloping roofs, the sliding and loss of planting soil under the action of gravity, wind, and rainwater erosion can lead to serious consequences. On the one hand, soil sliding causes shear failure of the waterproof layer, accelerates water seepage, leading to corrosion of steel structures, and accumulates excessive sliding load, resulting in excessive deflection of the roof structure. On the other hand, the grass slips off in patches, and the lost soil blocks the drainage system, causing local waterlogging, plant root rot, and reducing the survival rate of vegetation. Therefore, preventing the sliding and loss of soil is a key problem in the design of planted sloping roofs. However, to meet the needs of vegetation growth, planting soil needs to ensure a low density and a large thickness, so it is not possible to achieve anti-sliding by compacting the soil layer, and additional anti-sliding structures need to be set up to ensure the stability of the soil. In the context of large-slope and multi-curved surface planted roofs, the sliding force parallel to the slope increases significantly with the increase of slope, greatly increasing the difficulty of soil anti-sliding, and the roof structure is complex and variable, with stress concentration in local areas, making it difficult to ensure the long-term stability of the soil.

[0004] The traditional anti-sliding system of sloping roofs is composed of soil retaining plates, anti-sliding grids, and retaining walls. Steel bars are pre-embedded on the roof structure layer, and soil retaining plates perpendicular to the sloping roof are set on the waterproof protective layer and fixed by galvanized steel wire and tie belts. By controlling the spacing between the soil retaining plates, the sliding of the roof soil under different slopes is adapted. However, for large-slope and multi-curved surface planted roofs, the soil retaining plates and retaining walls are not flexible enough, and it is difficult to ensure the anti-sliding effect at the places where the curvature changes abruptly. When the slope is close to or greater than 50%, the sliding force increases significantly, and the soil retaining plates are not enough to prevent soil sliding. At the same time, the soil retaining plates are not well drained and are prone to waterlogging, requiring additional drainage systems, increasing construction costs and prolonging construction cycles. In addition, the pre-embedding of steel bars on the structure plate when setting the soil retaining plates affects the anti-sliding and roof waterproof effect.

[0005] In summary, the traditional anti-skid system of sloping roof cannot adapt to the challenge brought by large slope and multi-curved planting roof. SUMMARY

[0006] The purpose of the present application is to provide a construction method of bionic large slope planting roof and soil fixation system, by setting secondary structure network on the structural roof, forming grid isolation unit, avoiding excessive cumulative sliding force of soil body, realizing building finish surface form finding; by setting EPS foam board between the secondary structure network, effectively reducing the roof load, better adapting to large slope and multi-curved roof slope finding; by setting integrated cable anchor and geogrid cable on the secondary structure beam column, replacing the traditional retaining plate, more effectively providing anti-sliding effect, and not damaging the waterproof layer, at the same time avoiding the problem of poor drainage of the traditional retaining plate position; compared with the traditional anti-skid system of sloping roof which is generally applicable to the roof below 50 degrees, the present application can adapt to complex roof with slope of 50 degrees and above, solving the problems raised in the above background art.

[0007] To achieve the above purpose, the present application provides the following technical scheme:

[0008] A construction method of bionic large slope planting roof, comprising the following steps:

[0009] S1, establishing a BIM three-dimensional model on the primary structure roof panel, setting secondary structure beam columns at a predetermined interval to form a grid structure;

[0010] S2, selecting reinforced concrete or steel structure according to the type of roof, dividing the roof into grid units of ≤4m×4m to form a secondary structure network;

[0011] S3, filling EPS foam board in the grid to reduce load and assist in slope finding, forming EPS foam board;

[0012] S4, fixing the EPS board with the secondary structure beam column by using flat steel tie belt, setting 1-3 rows of flat steel tie according to the filling height;

[0013] S5, sequentially setting cushion layer, waterproof layer, root penetration resistant layer, isolation layer, protection layer, drainage board, planting soil layer, integrated anchor, geogrid cable and planting soil layer on the EPS foam board.

[0014] Further, in S1, the secondary structure beam columns are set at a predetermined interval to form a grid structure, comprising:

[0015] The grid structure is composed of round steel columns and round steel beams, and the primary structure roof panel is divided into a grid steel structure unit at an interval of not more than 4 meters;

[0016] A reserved embedded plate is provided between the steel column and the roof panel, and is welded.

[0017] The steel columns are connected by round steel beams to form a mesh-like overall structure.

[0018] Furthermore, in S2, reinforced concrete or steel structure is selected according to the roof type, and the roof is divided into grid units of ≤4m×4m to form a secondary structure network, including:

[0019] After the concrete sloping roof structure layer is constructed, formwork is erected on the original roof, and the concrete is poured in accordance with the procedure of first columns and then beams to form a secondary structural network.

[0020] Furthermore, in S3, EPS foam board is filled within the grid, including:

[0021] EPS foam boards are cut into blocks according to the structural slope to achieve full coverage of the roof filling layer;

[0022] EPS foam board was treated at the secondary structural column location, and a platform was set within 400mm of the secondary structural column to lower the local position by 50mm.

[0023] After the filling layer is completed, it is finished and compacted to prevent water seepage from causing foam to float.

[0024] Furthermore, in S4, 1-3 flat steel ties are set according to the filling height, including:

[0025] Adjust the number of flat steel bars according to the height of the EPS foam board. When the filling height H < 600mm, install one flat steel bar.

[0026] When the filling height is 600mm≤H<1200mm, two layers of flat steel should be installed, one at the top and one at the bottom.

[0027] When the filling height H ≥ 1200mm, three layers of flat steel are installed: upper, middle, and lower.

[0028] A soil stabilization system for an eco-friendly, steeply sloped green roof includes: a core load-bearing unit consisting of columns, steel tie rods / cables, and a ring beam; the core load-bearing unit includes:

[0029] The vertical support system is configured as a circumferential array of steel tube concrete columns or lattice steel columns on the roof as the main compression members.

[0030] The steel frame restraint system is configured as a spatial truss arranged circumferentially along the roof and connected to the vertical columns through rigid nodes;

[0031] The cable-stayed system is configured to arrange prestressed steel rods or cables between adjacent columns to form a radial and circumferential tension network for the roof.

[0032] Furthermore, it also includes:

[0033] The integrated cable anchor is configured to be installed in a secondary structure beam-column joint, and a three-dimensional soil fixation network layer is formed by longitudinal and transverse steel strands.

[0034] The finished geogrid cable is arranged in the network to divide the planting slope surface into a plurality of units, and to ensure that the planting slope surface unit turf is effectively spliced to form a whole.

[0035] Further, the integrated cable anchor adopts different structural forms according to different types of roofs. When the structural roof is a concrete shell, the integrated cable anchor is fixed on the secondary structure beam by a hoop. When the structural roof is a large-slope multi-curved surface continuous steel structure, the integrated cable anchor is fixed on the secondary structure column by a column cap.

[0036] Further, the integrated cable anchor further comprises a predictive adaptive tensioning module arranged in the soil fixation system, which comprises:

[0037] A meteorological data interface is arranged to obtain rainfall intensity prediction information ;

[0038] A soil state sensing array is arranged to monitor real-time soil parameters

[0039] A dynamic tensioning actuator group is arranged to comprise a plurality of electric servo tensioners connected to the cable

[0040] A controller is connected to the interface, array and actuator group, and is configured to:

[0041] The BIM three-dimensional model is called to extract the geometric characteristics of each grid unit of the roof, including local Gaussian curvature and slope ;

[0042] Based on the rainfall intensity prediction information and the geometric characteristics, a real-time hydrodynamic simulation model is run to predict the transient water flow convergence factor , predict the hydraulic gradient and predict the pore water pressure ;

[0043] Based on the prediction results, the dynamic required tension adjustment value of a specific grid unit to maintain the target safety factor is calculated ; the calculation formula is:

[0044]

[0045] Wherein, the sub-items are defined as follows:

[0046]

[0047]

[0048]

[0049] wherein the parameters are defined as follows:

[0050] is the dynamic demand tension adjustment value (N); is the grid cell calculation area (m 2 ); is the transient water flow convergence factor (dimensionless); is the average angle of the cable relative to the slope slip direction (degrees); is the target safety factor (dimensionless); is the predicted self-weight driven shear stress of the soil (Pa); is the predicted transient seepage force generated driven shear stress (Pa); is the benchmark shear strength provided by the system static pre-tension (Pa); is the predicted soil shear strength (Pa); is the predicted soil density based on the simulation model (kg / m 3 ); is the gravitational acceleration (m / s 2 ); is the soil layer thickness (m); is the local slope angle (degrees); is the predicted hydraulic gradient (dimensionless); is the unit weight of water (N / m 3 ); is the effective cohesion of the soil (Pa); is the predicted pore water pressure (Pa); is the effective internal friction angle of the soil (degrees);

[0051] based on the calculated dynamic demand tension adjustment value , the differential tensioning of the dynamic tensioning actuator group is controlled.

[0052] Further, it further comprises an interface micro-slip acoustic fingerprint identification early warning module deployed in the soil stabilization system;

[0053] The interface micro-slip acoustic fingerprint identification early warning module comprises:

[0054] A distributed acoustic sensing (DAS) system, comprising a sensing optical cable laid along the key beam column and / or construction interface of the secondary structure network, and a DAS demodulator;

[0055] A signal processing unit connected to the DAS demodulator;

[0056] The signal processing unit is configured to perform the following steps:

[0057] The DAS demodulator is used to collect high-frequency acoustic signal data streams distributed along the sensing optical cable in real time, and generate a time-space acoustic feature map containing frequency, amplitude and spatial position;

[0058] The time-space acoustic feature map is input into a pre-trained deep learning model, which is trained to distinguish between environmental background noise, normal stress vibration of the structure, and specific acoustic fingerprint signals generated when shear microslip occurs at the interface between the planting soil layer, geogrid or EPS foam board;

[0059] When the model identifies specific acoustic fingerprint signals indicating interface shear microslip between the planting soil layer, geogrid or EPS foam board, the three-dimensional spatial position of the microslip is determined from the time-space acoustic feature map, and an early structure failure warning is issued.

[0060] Compared with the prior art, the beneficial effects of the present application are:

[0061] 1. The present application, by setting a secondary structure network on the structure roof, forming a grid partition unit, planting soil is distributed in each grid, avoiding excessive cumulative sliding force of the soil body, realizing building finish surface shaping, optimizing construction process, and effectively ensuring the forming effect of complex roof; by setting EPS foam board between the secondary structure network, effectively reducing the roof load, at the same time, the EPS foam board is easy to cut, significantly improving the precision and efficiency of complex structure finish surface shaping; and compared with the conventional retaining board, it is more flexible and better adapts to large slope and multi-curved surface roof slope finding.

[0062] 2. The present application, by setting an integrated cable anchor on the secondary structure beam column, can be prefabricated in the factory and installed on site, which can effectively save the construction period; by setting geogrid on the secondary structure network, replacing the traditional retaining board, it can more effectively provide anti-sliding effect, and will not damage the waterproof layer, at the same time, avoiding the problem of poor drainage of the traditional retaining board; and by the cooperation of the secondary structure network and the geogrid system, the anti-sliding performance is better, compared with the traditional slope roof anti-sliding system which is generally applicable to the roof below 50 degrees, the present application can adapt to complex roof with slope of 50 degrees and above. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 is a schematic diagram of the secondary structure network of the steel structure roof of the present application;

[0064] Figure 2 is a top view schematic diagram of the secondary structure network of the steel structure roof of the present application;

[0065] Figure 3The secondary structure network of the concrete roof of the present application;

[0066] Figure 4 The overall schematic diagram of the secondary structure network of the concrete roof of the present application;

[0067] Figure 5 The schematic diagram of the EPS foam board arrangement of the present application;

[0068] Figure 6 The schematic diagram of the secondary structure column position EPS node of the present application;

[0069] Figure 7 The schematic diagram of the secondary structure column position EPS node of the present application from different perspectives;

[0070] Figure 8 The schematic diagram of the steel structure roof integrated anchor of the present application;

[0071] Figure 9 The schematic diagram of the cable and anchor plane arrangement of the present application;

[0072] Figure 10 The schematic diagram of the cable and anchor cross-section arrangement of the present application;

[0073] Figure 11 The schematic diagram of the cable anchor node of the present application.

[0074] In the figure: 1, secondary structure network; 2, EPS foam board; 3, flat steel tie belt; 5, integrated anchor. DETAILED DESCRIPTION

[0075] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0076] To solve the prior art, the traditional anti-skid system of the sloping roof is composed of a retaining plate, an anti-skid grid and a retaining wall, a reinforcing bar is pre-buried on a roof structure layer, a retaining plate perpendicular to the sloping roof is arranged on a waterproof protective layer, the retaining plate is fixed by binding with a galvanized steel wire and a tie belt, the spacing between the retaining plates is controlled to adapt to the sliding of the roof covering soil under different slopes, but for a large-slope multi-curved planting roof, the retaining plate and the retaining wall are not flexible enough to be arranged, it is difficult to guarantee the anti-skid effect at the position where the curvature changes abruptly, and when the slope is close to or greater than 50%, the sliding force increases significantly, and the retaining plate is not enough to prevent the soil from sliding, at the same time, the position of the retaining plate is not good for drainage, and water is easy to stagnate, so an additional drainage system needs to be arranged, which increases the construction cost and prolongs the construction period, in addition, the reinforcing bar needs to be pre-buried on the structure plate when the retaining plate is arranged, which affects the anti-skid and waterproof effects of the roof, please refer to Figures 1-2 The embodiment provides the following technical solutions:

[0077] A construction method of a bionic ecological large-slope planting roof, comprising the following steps:

[0078] S1, a BIM three-dimensional model is established on a primary structure roof plate, secondary structure beams and columns are arranged at a predetermined spacing to form a grid-shaped structure, specifically comprising the following steps:

[0079] After the construction of the sloping roof structure layer is completed, the soil-retaining structure of the special-shaped slope is effectively fixed to realize the final finish surface shape requirement, the primary structure roof plate is divided into a grid-shaped steel structure unit by a grid-shaped structure composed of round steel columns and round steel beams at a spacing of not more than 4 meters;

[0080] A reserved plate is reserved between the steel column and the roof plate, and welding is performed to ensure the quality of the secondary weld;

[0081] The steel column and the steel column are connected by a round steel beam to form a grid-shaped integral structure.

[0082] S2, according to the type of the roof, reinforced concrete or steel structure is selected, the roof is divided into a grid unit of ≤4m*4m to form a secondary structure network 1, specifically comprising the following steps:

[0083] After the construction of the concrete sloping roof structure layer is completed, the formwork is erected on the original roof to realize the final finish surface shape requirement, and pouring is performed according to the procedure of column first and beam later to form the secondary structure network 1. In specific implementation, for a general large-slope concrete shell structure roof, reinforced concrete can be selected to construct the secondary structure network 1 system; for a large-slope multi-curved continuous steel structure roof, in order to reduce the upper load, facilitate formwork construction and guarantee the forming effect, a steel beam column can be selected to construct the secondary structure network 1 system.

[0084] S3, the grid is filled with soil with a density of 18kg / m 3, the EPS foam board with compressive strength ≥ 150kPa, load reduction and auxiliary slope finding, forming the EPS foam board 2, specifically comprising the following steps:

[0085] According to the structural slope, the EPS is cut into blocks to achieve full paving of the roof filling layer; the light EPS foam board is used for the slope layer, which can not only reduce the uniform load of the roof, but also quickly complete the roof slope finding, and also achieve a certain energy-saving and heat-insulating effect. Considering that at the secondary structure column position, the water-facing surface will block the concrete from flowing downstream, resulting in local partial thickening of the column protection layer, compression of the upper part of the method height and construction space of the waterproof roll material; the EPS foam board 2 is specially treated at the secondary structure column position, and a platform is arranged within 400mm of the secondary structure column, so that the local position is lowered by 50mm. In order to ensure the final forming effect and the flatness of each layer of the roof, after the filling layer is constructed, it is repaired and compacted to prevent water seepage from causing the foam to float.

[0086] S4, the EPS board and the secondary structure beam column are fixed by using the flat steel tie belt 3, and 1-3 flat steel ties are arranged according to the filling height, specifically comprising the following steps:

[0087] According to the height of the EPS foam board 2, the number of flat steel is increased or decreased, when the filling height H < 600mm, one 40*4mm flat steel is arranged; when the filling height 600mm≤H < 1200mm, upper and lower two flat steels are arranged; when the filling height H≥1200mm, upper, middle and lower three flat steels are arranged; the two ends of the flat steel are connected with the secondary structure beam column by using M12A2-70 stainless steel bolts and 8mm fillet welds to realize the effect of fixing the EPS filling; at the same time, there is a lateral force concentration at the bottom of the roof, so two or three flat steels are selected for tie.

[0088] S5, the EPS foam board 2 is sequentially provided with a cushion layer, a waterproof layer, a root penetration resistant layer, an isolation layer, a protection layer, a drainage board, a planting soil layer, an integrated anchor 5, a geogrid and a planting soil layer.

[0089] The beneficial effects achieved by the above content are: by arranging the secondary structure network 1 on the structural roof to form a gridized partition unit, the planting soil is distributed in each grid to avoid excessive cumulative sliding force of the soil body, to realize the shape finding of the completed building surface, to optimize the construction process and to effectively ensure the forming effect of the complex roof; by arranging the EPS foam board 2 between the secondary structure network 1, the roof load is effectively reduced, and the EPS foam board 2 is easy to cut, which significantly improves the accuracy and efficiency of the shape finding of the completed complex structure; and compared with the conventional retaining board, it is more flexible and better adapts to the slope finding of the large slope and multi-curved surface roof.

[0090] A soil fixation system for a bionic ecological large-slope planting roof, comprising: a core bearing unit composed of a rigid compression member, i.e., a stand column, a high-strength tensile member, i.e., a steel tie rod / cable, and a ring beam.

[0091] The core bearing unit comprises:

[0092] The vertical support system is configured to arrange the concrete-filled steel tube columns or the latticed steel columns as the main compression members along the circumferential array on the roof.

[0093] The steel frame restraint system is configured to arrange the spatial trusses along the circumferential direction of the roof cover and connect the vertical columns through the rigid nodes such as welding or high-strength bolts.

[0094] The cable tie system is configured to arrange the prestressed steel rods or cables between the adjacent columns to form the radial and circumferential tension network of the roof cover.

[0095] The integrated cable anchor is configured to be installed on the secondary structure network 1 beam-column joint, and then be tied through the longitudinal and transverse steel strands to form a three-dimensional solid soil network layer; the finished geogrid cable is arranged in the network to divide the planting slope surface into a plurality of units to ensure that the planting slope surface units are effectively spliced to form a whole; in the specific implementation, the integrated cable anchor adopts different structural forms according to different types of roof cover, when the structural roof cover is a concrete shell, the integrated cable anchor is fixed on the secondary structure beam by a hoop; when the structural roof cover is a large slope and multi-curved surface continuous steel structure, the integrated cable anchor is fixed on the secondary structure column position in the form of a column cap.

[0096] The above-mentioned beneficial effects are achieved: through the arrangement of the integrated cable anchor on the secondary structure network 1 beam-column, the integrated cable anchor can be prefabricated in the factory and installed on site, which can effectively save the construction period; through the arrangement of the geogrid cable on the secondary structure network 1, the geogrid cable can replace the traditional soil retaining plate to more effectively provide the anti-sliding effect without damaging the waterproof layer, and the problem of poor drainage at the position of the traditional soil retaining plate is avoided; and through the cooperation of the secondary structure network 1 and the geogrid cable system, the anti-sliding performance is better.

[0097] In one embodiment, it is assumed that the bionic large slope planting roof cover is a continuous steel structure roof cover; due to the circular cross section of the structural beam and the large load of the fixing member, the steel frame column position cannot be provided with the top fixing member in the form of the embedded steel bar; therefore, the secondary structure column top is arranged, and the top fixing member and the lateral fixing member are arranged on the secondary structure column top to tie the cable and provide the tensile force parallel to the roof cover; the lateral fixing member is arranged at the column position to arrange the steel strand in the circumferential direction of the roof cover to form the steel strand network to improve the overall stability and enhance the soil restraining capacity; in addition, the top fixing member and the lateral fixing member of the steel strand are not on the same slope, so that two layers of planting soil can be arranged in the form of two layers of steel strands to tie in layers to better restrain the soil.

[0098] In another embodiment, assuming that the bionic large slope planting roof is a concrete shell roof; the concrete frame soil fixation network system itself has a secondary structure beam-column network, which can be used as a cable anchor point to realize effective anchoring of the cable and balance of the spatial force system; anchor iron is pre-set on the secondary structure beam, the cable component penetrates the anchor node, and is reliably connected with the beam body through mechanical anchoring such as: anchor, locking nut or welding, to ensure that the main cable force is effectively transmitted along the beam axis; in order to further constrain the displacement of the structure in the horizontal plane and improve the overall stability, lateral constraints can be added to the key nodes at the top of the system, which can apply active or passive constraint force parallel to the roof plane through rigid connecting pieces such as: steel connecting rods, steel components or prestressed tension rods, and work together with the lower anchoring system to form a spatial anchoring and constraint system resisting three-dimensional load.

[0099] The beneficial effects achieved by the above are: the soil fixation system of the bionic large slope planting roof can be set on a large slope roof of 50° and above, a secondary structure network 1 is set on the structural layer, the roof soil is divided into grid units by the secondary structure network 1 and the EPS foam board 2, the shape finding and positioning of the large slope planting roof are realized, and the overall anti-sliding capacity of the node is improved by the cable system and the geogrid.

[0100] Working principle: the roof is divided into ≤4m×4m grid units by BIM technology, a secondary structure network 1 is constructed by round steel columns and beams or reinforced concrete to provide accurate coordinates and mechanical support for subsequent construction; the grid is filled with EPS foam boards to realize rapid slope finding and load reduction; the EPS is fixed with the secondary structure by flat steel tie belts 3, 1-3 flat steels are set according to the filling height to ensure the stability of the EPS foam board 2; and the EPS layer is sequentially paved with a cushion layer, a waterproof layer, a root penetration resistant layer, an isolation layer, a protection layer, a drainage board and a planting soil layer to form a complete functional layer system; the soil fixation system constructs a core bearing unit by vertical support, steel frame constraint and cable anchor system, converts the sliding force into prestress, and separates the planting soil into independent units by the integral cable anchor and the geogrid to block the continuous sliding surface and ensure the effective splicing and overall stability of the planting slope unit turf; thereby effectively solving the problems of shape finding, load and soil stability of the large slope planting roof. Compared with the traditional slope roof anti-skid system which is generally applicable to roofs below 50 degrees, the present application can adapt to complex roofs with a slope of 50 degrees and above, and has significant economic and ecological benefits.

[0101] In one embodiment, it also includes a predictive self-adaptive tensioning module deployed in the soil fixation system, which includes:

[0102] A meteorological data interface for obtaining rainfall intensity prediction information ;

[0103] Soil state sensing array for monitoring real-time soil parameters;

[0104] A dynamic tensioning actuator assembly, comprising multiple electrically powered servo tensioners connected to the cable;

[0105] The controller, connected to the interface, array, and actuator group, is configured as follows:

[0106] Using the aforementioned BIM 3D model, the geometric features of each grid cell on the roof are extracted, including local Gaussian curvature. and slope ;

[0107] Based on the rainfall intensity prediction information Based on geometric characteristics, a real-time hydrodynamic simulation model is run to predict the transient flow convergence factor of each grid cell. Predicting hydraulic gradients and predicting pore water pressure ;

[0108] Based on the prediction results, calculate the safety factor for a specific grid cell to maintain the target. Required dynamic demand tension adjustment value The calculation formula is as follows:

[0109]

[0110] The sub-items are defined as follows:

[0111]

[0112]

[0113]

[0114] The parameters are defined as follows:

[0115] The dynamic demand tension adjustment value (N); Calculate the area (m²) of each grid cell. 2 ); is the transient flow convergence factor (dimensionless). The average angle (in degrees) between the cable and the direction of slippage on the slope. The target safety factor (dimensionless); The predicted shear stress (Pa) driven by the soil's own weight. The driving shear stress (Pa) generated by the predicted transient seepage force. The baseline shear strength (Pa) provided for the static pretension of the system; The predicted soil shear stress (Pa); is the soil density (kg / m 3 ) predicted based on the simulation model; is the gravity acceleration (m / s 2 ); is the soil layer thickness (m); is the local slope angle (degree); is the predicted hydraulic gradient (dimensionless); is the unit weight of water (N / m 3 ); is the effective soil cohesion (Pa); is the predicted pore water pressure (Pa); is the effective soil internal friction angle (degree);

[0116] adjust the dynamic tension demand based on the calculated dynamic tension adjustment value , control the differential tension of the dynamic tension actuator group.

[0117] The predictive adaptive tensioning module aims to pre-calculate and dynamically adjust the cable tension in the soil stabilization system according to future weather conditions and the complex geometric features of the roof, through a feedforward control strategy, to cope with adverse factors such as transient soil saturation, rapid increase in pore water pressure, and increase in seepage force caused by heavy rainfall, and to ensure that the stability of the soil on the large-slope multi-curved roof always maintains above the preset safety threshold. The core innovation of this module lies in the deep integration of high-precision building information model (BIM), computational fluid dynamics simulation, geotechnical engineering limit equilibrium theory, and adaptive control technology, realizing a technical leap from passive soil stabilization to active, predictive, and locally differential dynamic soil stabilization.

[0118] The hardware architecture of the module is mainly composed of four parts: weather data interface, soil state perception array, dynamic tension actuator group, and central controller. The weather data interface is usually a secure network communication unit responsible for accessing high-resolution short-term weather forecast services in real time through application programming interfaces to obtain hourly rainfall intensity prediction information for the next few hours or even days. These information are the basic input to start predictive control. The soil state perception array is composed of various sensors distributed in different areas and depths of the roof, including but not limited to soil volumetric water content sensors, pore water pressure gauges, and temperature sensors. These sensors transmit real-time soil physical and mechanical parameters to the central controller through wired or wireless means for calibration and correction of the prediction model. The dynamic tension actuator group is the execution mechanism for active control, which is composed of multiple high-precision electric servo tensioners. These tensioners are connected in series to the key cables of the soil stabilization system, usually installed near the integrated cable anchor. Each tensioner has a servo motor, a reduction mechanism, a force sensor, and a displacement encoder integrated inside, allowing independent and precise adjustment of the tension of the connected cable according to the controller's instructions. The central controller is the computing core of the entire module, usually using high-performance industrial-grade processors or embedded systems, and deploying complex simulation models and control algorithms.

[0119] The workflow of the module begins with data collection and geometric model analysis. The central controller first calls the BIM three-dimensional model established on the primary structure roof panel. The BIM model contains accurate three-dimensional geometric information and topological relationships of the roof structure. The geometric analysis engine in the controller performs meshing on the BIM model, dividing the entire roof into multiple calculation units, which correspond to the grid units of the secondary structure network. For each grid unit, the analysis engine extracts key geometric feature parameters, the most important of which are local slope and local Gaussian curvature. Local slope directly affects the sliding component of soil weight down the slope, while local Gaussian curvature is a key indicator of the complexity of the surface. In areas with high Gaussian curvature, the geometric form of the roof changes dramatically. The reason for this innovative introduction of Gaussian curvature as a control parameter is that on a large slope and multi-surface roof, the surface runoff generated by rainfall is not uniformly distributed. Gaussian curvature directly affects the convergence and divergence pattern of water flow. Positive Gaussian curvature areas (convex surfaces) tend to disperse water flow, while negative Gaussian curvature areas (saddle surfaces or valleys) will cause significant convergence of water flow. Traditional soil stabilization designs often ignore this local hydrological effect caused by complex geometric forms.

[0120] After the geometry analysis, the controller activates a real-time hydrodynamic simulation model, which takes the acquired rainfall intensity prediction as input. The simulation model is usually based on shallow water equations or simplified computational fluid dynamics models, aiming to simulate the whole process of rainfall flow, accumulation, infiltration on complex surfaces, and water migration inside the soil. The simulation model takes rainfall intensity as an input boundary condition and takes the geometric features (slope and Gaussian curvature) as coefficients of the control equation. The model calculates the transient water flow accumulation factor for each grid cell in real time. This factor is a dimensionless parameter that quantifies the multiple of average water accumulation in this cell under specific rainfall conditions due to the roof geometry. In the area of negative Gaussian curvature, this factor will be significantly greater than 1.

[0121] Subsequently, the hydrodynamic simulation model further calculates the soil infiltration process. According to the soil permeability coefficient, the initial water content (provided by the soil state perception array in real time), and the calculated surface water depth (determined by the water flow accumulation factor and rainfall intensity), the model predicts the infiltration speed and depth of water in the soil. Based on the migration of water, the model further calculates two key hydrodynamic parameters: the predicted hydraulic gradient and the predicted pore water pressure. The predicted hydraulic gradient describes the driving force of water flow in soil pores, which directly determines the size of seepage force. Under heavy rainfall conditions, especially when water flows rapidly, the hydraulic gradient will increase sharply. The predicted pore water pressure refers to the pressure that water in the soil pores bears. According to the effective stress principle, the increase of pore water pressure will reduce the effective contact stress between soil particles, thereby significantly reducing the shear strength of the soil. This module captures the transient instability risk that traditional methods cannot quantify by accurately predicting the spatiotemporal distribution of these two parameters.

[0122] After obtaining the above key predicted parameters, the controller enters the core stability analysis and dynamic demand tension calculation phase. The goal of this phase is to calculate the additional tension adjustment value that needs to be applied to the cable system to maintain the stability of each grid cell of the soil above the preset target safety factor. The target safety factor is set according to engineering requirements, for example, set to 1.3, meaning that the system's anti-sliding ability needs to be 30% higher than the expected maximum sliding force.

[0123] The calculation process follows the principles of geotechnical engineering limit equilibrium analysis, but innovatively introduces transient hydrodynamic parameters.

[0124] First, calculate the total driving shear stress. The controller needs to calculate the total driving shear stress acting on the soil of a specific grid cell. This total driving shear stress is mainly composed of two parts: the predicted self-weight driving shear stress of the soil, and the predicted driving shear stress generated by the transient seepage force. The predicted self-weight driving shear stress of the soil is calculated according to the predicted soil density (considering the density after water increase), the acceleration of gravity, the thickness of the soil layer, and the sine value of the local slope angle. As the soil moisture content increases, its density increases, and the self-weight driving shear stress also increases. The predicted driving shear stress generated by the transient seepage force is calculated according to the product of the predicted hydraulic gradient, the unit weight of water, and the thickness of the soil layer. The seepage force is the drag force exerted on the soil skeleton when water flows through the soil pores, and it is a non-negligible slip driving force in the case of large slope and large hydraulic gradient.

[0125] Second, calculate the total shear strength. The controller needs to calculate the total shear strength that the soil of this grid cell can provide. The total shear strength is also mainly composed of two parts: the baseline shear strength provided by the system static pre-tension, and the predicted soil self-shear stress. The baseline shear strength is the initial pre-tension that the soil reinforcement system has applied in the design. The predicted soil self-shear stress is calculated using the Mohr-Coulomb strength criterion, but the key is to use the effective stress parameter considering the influence of pore water pressure. The specific calculation method is as follows: first, calculate the total normal stress acting on the slip surface, which is the vertical component of the soil self-weight in the direction perpendicular to the slope (obtained by multiplying the predicted soil density, the acceleration of gravity, the thickness of the soil layer, and the cosine value of the local slope angle). Then, subtract the predicted pore water pressure from the total normal stress to obtain the effective normal stress. Multiply the effective normal stress by the tangent value of the effective internal friction angle of the soil, and then add the effective cohesion of the soil, to finally obtain the predicted soil self-shear stress. It can be seen that the increase of pore water pressure will directly lead to a significant decrease in shear stress.

[0126] Third, determine the required dynamic tension adjustment value. The core logic is to ensure that the total anti-sliding capacity of the system can meet the requirements of the target safety factor under future adverse conditions. The specific steps are as follows: first, multiply the predicted total driving shear stress (including self-weight driving and seepage driving) by the target safety factor to obtain the target anti-sliding capacity (i.e. target shear strength) that the system needs to achieve. Then, subtract the current predicted total shear strength of the system (including static pre-tension and soil self-shear stress) from this target anti-sliding capacity. This gap is the additional shear strength that the system needs to supplement.

[0127] Finally, the shear strength gap is converted into the cable tension adjustment value. Since the cable system provides anti-sliding force through mechanical action, the force transmission efficiency and geometric relationship need to be considered. The controller multiplies the calculated shear strength gap by the calculated area of the grid cell to obtain the total anti-sliding force required. Then, this total anti-sliding force is multiplied by the transient flow convergence factor to consider the amplification effect of local flow convergence on the required anti-sliding force. Finally, this result is divided by the cosine value of the average angle of the cable relative to the sliding direction of the slope. This angle considers the relationship between the cable arrangement direction and the potential sliding direction of the soil, ensuring that the tension of the cable is effectively converted into the anti-sliding component parallel to the slope. After this series of complex calculations, the dynamic demand tension adjustment value required for this grid cell is finally obtained.

[0128] After calculating the demand tension adjustment value of all grid cells, the controller generates control instructions and sends them to the dynamic tensioning actuator group. After receiving the instructions, each electric servo tensioning device starts to act and independently adjusts the tension of the corresponding cable. Because the geometric characteristics and hydrological conditions of different areas are different, the required tension adjustment value is also different, so the system implements a "differential tensioning" strategy. For example, in the negative Gaussian curvature area where water flow convergence is severe, the corresponding cable will be applied with greater tension; while in the convex area where water flow diverges, the tension adjustment may be smaller or even not required. This fine and localized active control can provide the most effective anti-sliding support where it is most needed, while avoiding structural stress concentration and energy waste caused by global over-tensioning.

[0129] The entire predictive adaptive tensioning module forms a closed-loop control system. The soil parameters monitored by the soil state perception array are continuously fed back to the controller for comparison with the predicted results of the simulation model. If there is a significant deviation between the measured value and the predicted value, the controller will trigger the model adaptive calibration mechanism to dynamically adjust the parameters of the simulation model (such as soil permeability coefficient, internal friction angle, etc.) to improve the accuracy of subsequent predictions. This control strategy combining feedforward prediction and feedback calibration ensures that the system has high robustness and reliability when facing complex and variable actual environments.

[0130] In one embodiment, further comprising: an interface micro-slippage acoustic fingerprint identification early warning module deployed in the soil stabilization system;

[0131] The interface micro-slippage acoustic fingerprint identification early warning module comprises:

[0132] A distributed acoustic sensing (DAS) system, comprising a sensing optical cable laid along key beam columns and / or construction interfaces of the secondary structure network 1, and a DAS demodulator;

[0133] A signal processing unit connected to the DAS demodulator;

[0134] The signal processing unit is configured to perform the following steps:

[0135] The DAS demodulator is configured to collect high-frequency acoustic signal data streams distributed along the entire sensing optical cable in real time, and generate a spatiotemporal acoustic feature map containing frequency, amplitude, and spatial position;

[0136] The spatiotemporal acoustic feature map is input into a pre-trained deep learning model, preferably a convolutional neural network (CNN) classifier; the model is trained to distinguish between environmental background noise, normal stress vibration of the structure, and specific acoustic fingerprint signals generated when shear microslip occurs at the interface of multiple layers of construction;

[0137] When the model identifies specific acoustic fingerprint signals indicating that interface shear microslip has occurred between the planting soil layer, geogrid, or EPS foam board 2, the three-dimensional spatial position of the microslip is determined from the spatiotemporal acoustic feature map, and an early structural failure warning is issued.

[0138] The interface microslip fingerprint recognition and warning module aims to solve the problem of monitoring hidden construction interfaces in bionic ecological large-slope planting roofs. Planting roof structures are complex, including secondary structural networks, EPS foam boards 2, waterproof layers, geogrids, and planting soil layers. There are a large number of construction interfaces between these layered structures composed of different materials. Under the action of long-term load, temperature change, moisture erosion, and other factors, these interfaces may experience small shear slip. This microslip is an early sign of structural failure, but traditional point monitoring methods have limited monitoring range and cannot monitor the early failure of hidden interfaces buried deep inside.

[0139] The module innovatively introduces distributed acoustic sensing (DAS) technology and combines advanced deep learning algorithms to achieve real-time, high-precision, and fully distributed monitoring and intelligent identification and warning of microslip at the entire roof construction interface. The core principle is that when a construction interface experiences small shear slip, friction, dislocation, and rupture between materials release transient elastic energy, which propagates outward in the form of acoustic waves. By capturing and analyzing these specific acoustic signals, the occurrence time, spatial position, and intensity characteristics of the microslip event can be inverted.

[0140] The hardware system of the module mainly includes a distributed acoustic sensing (DAS) system and a high-performance signal processing unit. The DAS system is composed of a sensing optical cable, a DAS demodulator, and related optical accessories. The sensing optical cable is the key carrier for realizing distributed monitoring, and it is both a signal transmission medium and a sensor itself. In the present application, the sensing optical cable is strategically laid at key positions that need to be monitored. For example, it can be laid along the key beams and columns of the secondary structure network; more importantly, it can be directly laid on the key construction interfaces, such as between the EPS foam board 2 and the cushion layer, or between the geogrid and the planting soil layer. The laying method of the optical cable ensures good coupling between the optical cable and the structure being measured, and can sensitively perceive the small vibrations of the interface.

[0141] The DAS demodulator is the core equipment of the system, and its working principle is based on Rayleigh scattering and optical time domain reflection technology. The demodulator emits a series of high-frequency coherent laser pulses into the sensing optical cable. When the laser propagates in the optical fiber, it will undergo Rayleigh scattering with the small irregularities in the optical fiber material. Part of the scattered light will be transmitted back to the demodulator along the optical fiber. When external sound waves or vibrations act on the optical fiber, they will cause small deformation of the optical fiber, thereby changing the refractive index and length of the optical fiber at that point, and further causing changes in the phase of the backscattered light. The DAS demodulator detects these phase changes in real time through high-precision photodetectors and demodulation algorithms, thereby inverting the acoustic signals acting on the optical fiber. By measuring the time difference between the emission and reception of laser pulses, the location of the acoustic event can be accurately determined, with a spatial resolution of meters or even sub-meters. Therefore, a sensing optical cable is equivalent to an array of thousands of continuously distributed high-sensitivity microphones.

[0142] The high-performance signal processing unit is usually composed of a server equipped with a high-performance graphics processing unit (GPU) or a field programmable gate array (FPGA), which is responsible for processing the massive data collected by the DAS demodulator and running deep learning recognition algorithms. The DAS system has the characteristics of high frequency response, large dynamic range, and high spatial sampling rate, which will generate a large amount of raw data stream, and puts high requirements on signal processing capability.

[0143] The workflow of the module first involves real-time data acquisition and preprocessing. The DAS system acquires high-frequency acoustic signal data streams distributed along the sensing optical cable in real time at a very high sampling frequency. After receiving the raw data, the signal processing unit first performs preprocessing, including noise reduction, filtering, signal enhancement, and data format conversion. The processed data is organized into a spatio-temporal acoustic feature map. This is a multi-dimensional data structure, which includes time, spatial position (distance along the optical cable), and acoustic signal features (such as amplitude, frequency, or energy) at that spatio-temporal point. This map intuitively shows the propagation and distribution of sound waves in the roof structure.

[0144] The next critical step is intelligent acoustic fingerprint recognition. In actual roofing environments, background noise is very complex (such as wind noise, rain noise, etc.), and the acoustic signals generated by interface micro-slip are often very weak and easily overwhelmed by background noise. Traditional signal processing methods are difficult to effectively distinguish micro-slip signals from noise interference. To solve this problem, this module uses advanced deep learning technology, especially a convolutional neural network (CNN) classifier, to identify specific acoustic fingerprint signals of micro-slip events.

[0145] The application of deep learning models is one of the core innovations of this module. Convolutional neural networks are well suited to processing spatio-temporal acoustic feature maps with spatial and temporal structure characteristics. This model is specially trained to learn and recognize the unique patterns of different types of acoustic events. During the model training phase, a dataset containing a large number of samples is needed. These samples include specific acoustic fingerprint signals generated by different construction interfaces during shear micro-slip (positive samples) obtained through laboratory simulation tests, as well as various environmental background noise and structural normal stress vibration signals (negative samples). Through training, the convolutional neural network model can capture the subtle features of micro-slip signals in terms of frequency distribution, energy release patterns, etc., achieving high-precision recognition.

[0146] During real-time monitoring, the signal processing unit inputs the pre-processed spatio-temporal acoustic feature map into the pre-trained convolutional neural network classifier, and the model analyzes the input map frame by frame. The recognition of specific acoustic fingerprints is based on the unique physical mechanisms of micro-slip events. For example, the frictional slip between soil particles and the signals generated by the shear failure of EPS materials differ in frequency and energy distribution. The model can capture these subtle differences.

[0147] When the convolutional neural network model identifies specific acoustic fingerprint signals indicating interface shear micro-slip between planted soil layers, geogrids, or EPS foam boards 2, the system immediately triggers the early warning mechanism. At the same time, the signal processing unit determines the spatial location of the micro-slip event based on the position information of the signals in the spatio-temporal acoustic feature map. Since the laying path of the sensing optical cable is known in the BIM model, the system can accurately map the one-dimensional position information along the optical cable to the three-dimensional spatial coordinates of the roof.

[0148] Finally, the system issues an early structure failure warning. The warning information can be notified to the management personnel through various ways, such as highlighting the location of micro-slip occurrence on the monitoring interface and sending instant notifications. Early warning provides a valuable time window for management personnel to take timely intervention measures. In addition, this module also has a long-term trend analysis function. By continuously recording and analyzing the frequency, distribution pattern, and intensity changes of micro-slip events, the health status and aging trend of the roof structure can be evaluated.

[0149] The predictive adaptive tensioning module and the interface micro-slip acoustic fingerprint identification early warning module are not isolated, but are closely integrated in a unified intelligent monitoring and control platform, achieving synergistic effect. The two modules form a complementary relationship in function: the former focuses on "prediction and prevention" based on physical models, and the latter focuses on "monitoring and diagnosis" based on measured data.

[0150] In cooperative work, there is an information exchange and linkage mechanism between the two modules. For example, when the interface micro-slip acoustic fingerprint identification early warning module detects a micro-slip event in a certain area, it will feed back the information to the predictive adaptive tensioning module in real time. The controller of the tensioning module can use this information to immediately start the emergency response mechanism and apply additional tension to the cable in that area to suppress the further development of micro-slip and prevent a chain reaction. At the same time, the occurrence of a micro-slip event also indicates that the current prediction model may have deviations or unconsidered factors. The controller can use these measured failure data to perform online learning and optimization of the predictive model, improving the model's adaptability to complex working conditions.

[0151] Conversely, when the tensioning module starts and applies differential tension, it changes the stress distribution and vibration characteristics of the roof structure. The interface micro-slip acoustic fingerprint identification early warning module can monitor these changes and use them as background information. For example, the structural vibration signals generated during tensioning will be identified by the deep learning model as normal operation signals, thus avoiding false positives.

[0152] In summary, by introducing these two intelligent modules, the present application has built an intelligent soil stabilization system that integrates real-time sensing, scientific prediction, intelligent identification, active control, and early warning. The system makes full use of advanced information technology, sensing technology, and artificial intelligence technology, and solves the problems of transient hydrodynamic instability and hidden interface failure monitoring that the traditional static soil stabilization system cannot handle, significantly improving the safety performance, durability, and intelligence level of the bionical large-slope planting roof.

[0153] It should be noted that, in this text, relational terms such as first and second are used merely to distinguish one entity or action from another, and do not necessarily require or imply that there is any such actual relationship or order between these entities or actions. Moreover, the terms "include", "contain" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device.

[0154] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. A soil fixation system for a biomimetic large-slope planted roof, which is applied to a construction method for a biomimetic large-slope planted roof, characterized in that, The method comprises the following steps: S1, establishing a BIM three-dimensional model on a primary structure roof panel, setting secondary structure beams and columns at a predetermined interval to form a grid structure; S2, selecting reinforced concrete or steel structure according to the roof type, dividing the roof into grid units ≤4m×4m to form a secondary structure network (1); S3, filling EPS foam board (2) in the grid to reduce the load and assist in finding the slope; S4, using flat steel tie belts (3) to fix the EPS foam board (2) and the secondary structure beams and columns, and setting 1-3 flat steel ties according to the filling height; S5, sequentially setting the cushion layer, waterproof layer, root penetration resistant layer, isolation layer, protection layer, drainage board, planting soil layer, integrated anchor (5), geogrid and planting soil layer on the EPS foam board (2); A soil fixation system for a large slope planting roof, comprising a core bearing unit composed of a stand column, a steel pull rod / steel cable and a ring beam, wherein the core bearing unit comprises: a vertical support system configured to arrange concrete-filled steel tubular columns or lattice steel columns in a circumferential array on the roof as main compression members; a steel frame constraint system configured to set a spatial truss along the circumference of the roof cover and connect with the vertical columns through rigid nodes; a cable tie system configured to arrange prestressed steel pull rods or steel cables between adjacent columns to form a radial and circumferential tension network of the roof cover; an integrated cable anchor configured to install the integrated cable anchor in the beam column node of the secondary structure network (1) and form a three-dimensional soil fixation network layer through longitudinal and transverse steel wire ties; setting a finished geogrid in the network to divide the planting slope into several units and ensure that the grass on the planting slope units is effectively spliced to form a whole; further comprising a predictive adaptive tensioning module deployed in the soil fixation system; the predictive adaptive tensioning module comprises: A weather data interface for obtaining rainfall intensity prediction information ; a soil state sensing array for monitoring real-time soil parameters; a dynamic tensioning actuator group comprising a plurality of electric servo tensioners connected to the cables; A controller, connected with the interface, the array and the actuator group, configured to call the BIM three-dimensional model, extract the geometric characteristics of each grid unit of the roof, including the local Gaussian curvature and slope ; based on the rainfall intensity prediction information and geometric characteristics, running a real-time hydrodynamic simulation model to predict a transient water flow convergence factor for each grid cell , to predict a hydraulic gradient and to predict a pore water pressure ; Based on the prediction result, a specific grid cell is calculated to maintain a target safety factor The required dynamic demand tension adjustment value The calculation formula is: wherein the sub-items are defined as follows: wherein, is the dynamic demand tension adjustment value; is the grid cell calculation area; is the transient water flow convergence factor; is the average angle of the cable relative to the slope slip direction; is the target safety factor; is the predicted self-weight driven shear stress of the soil; is the predicted transient seepage force driven shear stress; is the benchmark shear strength provided by the system static pre-tension; is the predicted soil shear strength; is the predicted soil density based on the simulation model; is the gravitational acceleration; is the soil layer thickness; is the local slope angle; is the predicted hydraulic gradient; is the unit weight of water; is the effective cohesion of the soil; is the predicted pore water pressure; is the effective internal friction angle of the soil; adjusting the dynamic demand tension based on the calculated dynamic demand tension adjustment value controlling the dynamic tensioning actuators to perform differential tensioning.

2. The soil stabilizing system for planted roof with large slope according to claim 1, characterized in that, in S1, the secondary structure beams and columns are set at a predetermined interval to form a grid structure, comprising: the grid structure is composed of round steel columns and round steel beams, and the primary structure roof panel is divided into a grid steel structure unit at an interval of not more than 4 meters; embed plates are reserved between the steel columns and the roof panel and are welded; round steel beams are used to connect the steel columns to form a grid whole structure.

3. The soil stabilizing system for planted roofs of large slope imitating the ecological system according to claim 1, characterized in that, in S2, the roof is divided into grid units ≤4m×4m to form a secondary structure network (1) according to the roof type, comprising: after completing the construction of the concrete slope roof structure layer, a formwork is erected on the original roof, and pouring is carried out according to the procedure of column first and beam later to form a secondary structure network (1).

4. The soil stabilizing system for planted roofs of large slope imitating the ecological system according to claim 1, characterized in that, in S3, the EPS foam board (2) is filled in the grid, comprising: cutting the EPS foam board (2) according to the structure slope to achieve full paving of the roof cover filling layer; processing the EPS foam board (2) at the secondary structure column position, and setting a platform within a range of 400mm of the secondary structure column to lower the local position by 50mm; After the filling layer is constructed, it is leveled and compacted to prevent water seepage from causing foam to float.

5. The soil stabilizing system for planted roofs of large slope imitating the ecological system according to claim 1, characterized in that, In S4, 1-3 flat steel tie rods are arranged according to the filling height, including: According to the height of the EPS foam board (2), the number of flat steel is increased or decreased, when the filling height H < 600 mm, one flat steel is arranged; When the filling height 600 mm≤H < 1200 mm, two flat steels are arranged on the upper and lower sides; When the filling height H≥1200 mm, three flat steels are arranged on the upper, middle and lower sides.

6. The soil stabilizing system for planted roofs of large slope simulating the ecological environment according to claim 1, characterized in that, When the structural roof is a concrete shell, a hoop is used to fix the integrated cable anchor (5) on the secondary structure beam; When the structural roof is a large slope multi-curved surface continuous steel structure, a column cap is used to fix the integrated cable anchor (5) on the secondary structure column.

7. The soil stabilizing system for planted roofs of steep slope according to claim 1, characterized in that, It also includes an interface micro-slip acoustic fingerprint identification early warning module deployed in the soil fixation system; The interface micro-slip acoustic fingerprint identification early warning module includes: A distributed acoustic sensing system, including a sensing optical cable laid along the key beams and / or construction interfaces of the secondary structure network (1), and a DAS demodulator; A signal processing unit connected to the DAS demodulator; The signal processing unit is configured to perform the following steps: Through the DAS demodulator, real-time acquisition of high-frequency acoustic signal data streams distributed along the sensing optical cable is performed to generate a time-space acoustic feature map containing frequency, amplitude and spatial position; The time-space acoustic feature map is input into a pre-trained deep learning model, which is trained to distinguish between environmental background noise, normal stress vibration of the structure, and specific acoustic fingerprint signals generated when shear micro-slip occurs at the multi-layer construction interface; When the model identifies specific acoustic fingerprint signals indicating that interface shear micro-slip occurs between the planted soil layer, geogrid or the EPS foam board (2), the three-dimensional spatial position of the micro-slip is determined according to the time-space acoustic feature map, and an early structure failure warning is issued.

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