A geotechnical engineering monitoring system based on 3D printing prefabrication and a construction method thereof

Abstract

The application discloses a geotechnical engineering monitoring system based on 3D printing prefabrication and a construction method thereof. The geotechnical engineering monitoring system comprises a grid base, a sensor and a data acquisition unit. The grid base is formed by 3D printing prefabrication. Sensor cabins are arranged at part of the intersecting nodes of the rib strips of the grid base. The sensor cabins are of a groove type structure. The sensor is arranged in the sensor cabin and connected with the data acquisition unit. The grid base is a stress contour gradually changing type topological grid. In addition to the rib strip intersecting nodes provided with the sensor cabins, the rest of the rib strip intersecting nodes are all provided with upward extending bionic root system structures. The grid base integrated with the sensor cabins has mechanical reinforcement and intelligent sensing functions, realizes high-precision three-dimensional positioning of the sensor, full-life-cycle physical protection and mechanical continuity interlocking function with the geotechnical body.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering data monitoring technology, specifically a geotechnical engineering monitoring system based on 3D printing prefabrication and its construction method. Background Technology

[0002] In the field of geotechnical structural health monitoring, the installation and fixation of sensors is a critical and challenging technology. Currently, the commonly used method in the industry is to directly place the sensors at predetermined locations on the construction site, and then cover them with soil or pour concrete using simple physical constraints or temporary encapsulation. This method has revealed significant limitations in engineering practice: sensors are highly susceptible to displacement under strong disturbances during subsequent construction, causing the monitoring data to lose spatial representativeness; simultaneously, sensor components and their cables are directly exposed to complex mechanical and chemical environments, resulting in a high damage rate and seriously affecting the long-term reliability and durability of the monitoring system. Furthermore, this on-site point-by-point installation method is cumbersome, inefficient, and interferes with the main construction work, severely impacting project progress.

[0003] To overcome these shortcomings, the concept of prefabrication and encapsulation has been introduced, such as pre-casting sensors into small concrete blocks or placing them within universal protective shells. In recent years, additive manufacturing (3D printing) technology has also begun to be explored for manufacturing customized sensor housings or mounting brackets. These methods offer better shape adaptability and basic protection to some extent. However, these existing technological solutions, including the 3D printing applications already explored, still have fundamental shortcomings. They primarily focus on protective functions, and their structures are mostly closed or solid. While isolating the external medium, this also hinders the formation of a strong, mechanically continuous bond between the sensor and the surrounding soil or concrete, easily leading to interface defects and distortion of stress-strain transfer. More importantly, these solutions lack a systematic design for efficient and reliable integration with the main structure, fail to consider using innovative structures to achieve mechanical interlocking, and fail to incorporate engineering features that facilitate rapid on-site assembly. Their customization is often limited to the external shape, and the technological potential of 3D printing has not been fully realized in areas such as precise sensor positioning, integrated layout of multiple sensor types, and cable management. Therefore, the existing technology system still lacks a comprehensive solution that can simultaneously ensure the precise orientation of the sensor, provide all-round protection, achieve a permanent and robust connection with the host structure, and support rapid modular construction. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a geotechnical engineering monitoring system and its construction method based on 3D printing prefabrication. The grid-type matrix integrating the sensor cabin has both mechanical reinforcement and intelligent sensing functions, realizing high-precision three-dimensional positioning of the sensor, full life cycle physical protection, and mechanical continuity interlocking function with the geotechnical body.

[0005] The technical solution of this invention is as follows: A geotechnical engineering monitoring system based on 3D printing prefabrication includes a grid-type matrix, sensors and a data acquisition unit. The grid-type matrix is ​​prefabricated by 3D printing. Sensor cabins are set at some of the cross nodes of the grid-type matrix ribs. The sensor cabins have a groove-type structure. The sensors are set in the sensor cabins and connected to the data acquisition unit. The grid-type substrate located on the outer periphery of the sensor cabin extends outward from the center of the sensor cabin and is sequentially divided into a stress concentration zone, a transition gradient zone, and an outer standard zone. The stress concentration zone, the transition gradient zone, and the outer standard zone are formed by stress field simulation outward from the center of the sensor cabin, resulting in a stress contour gradient topological grid. The outer standard zone of the stress contour gradient topological grid is a large-aperture sparse grid, the transition gradient zone is a medium-aperture transition grid, and the stress concentration zone is a small-aperture dense grid. In addition to the rib intersections of the sensor compartment, the grid-type substrate is equipped with upward-extending biomimetic root structures at all other rib intersections.

[0006] The large-aperture sparse grid has an opening rate of 60%–70%; the small-aperture dense grid has an opening rate of 15%–25%, and the small-aperture dense grid is obtained by dividing one or more adjacent large-aperture sparse grids on the outer ring of the sensor housing with ribs; the medium-aperture transition grid has an opening rate of 40%–50%, and the medium-aperture transition grid is located between the outer ring of the small-aperture dense grid and the inner ring of the large-aperture sparse grid, and the medium-aperture transition grid is obtained by dividing one or more adjacent large-aperture sparse grids on the outer ring of the small-aperture dense grid with ribs. When the rib length of the large-aperture sparse grid is not less than 50 mm, the small-aperture dense grid is obtained by dividing the adjacent large-aperture sparse grid on the outer ring of the sensor cabin by ribs, and the medium-aperture transition grid is obtained by dividing the adjacent large-aperture sparse grid on the outer ring of the small-aperture dense grid by ribs. When the rib length of the large-aperture sparse grid is less than 50 mm, the small-aperture dense grid is obtained by dividing the outer ring of the sensor housing into two or three adjacent rings of large-aperture sparse grids with ribs. The medium-aperture transition grid is obtained by dividing the outer ring of the small-aperture dense grid into two or three adjacent rings of large-aperture sparse grids with ribs.

[0007] The thickness of the ribs in the transition zone is a gradually decreasing structure, with the thickness gradually decreasing from the end near the stress concentration zone to the end near the outer standard zone.

[0008] The biomimetic root structure includes a main root-like protrusion extending vertically upwards, and a ring of fibrous root-like protrusions distributed around the main root-like protrusion. The fibrous root-like protrusions are obliquely placed, and the angle between the bottom end of the fibrous root-like protrusion and the bottom end of the main root-like protrusion is an acute angle with an angle of 30-60 degrees.

[0009] The top surface of the ribs of the grid-type substrate is provided with barbed anchoring protrusions, which include vertical protrusions and multiple barbed protrusions whose inner ends are connected to the top of the vertical protrusions.

[0010] The tips of the main root-like protrusion and the fibrous root-like protrusion, as well as the outer ends of the barbed protrusion, are all conical pointed structures.

[0011] The sensor housing has a ring of stress breakage lines on its top surface on the annular side. The stress breakage lines are cross-shaped or X-shaped grid-like intersecting lines, and the thickness of the stress breakage lines is 2-5mm.

[0012] The sensor housing has the same shape as the sensor. After the sensor is placed inside the sensor housing, it is in clearance fit with the sensor housing. An encapsulating adhesive layer is provided at the gap. The top of the sensor housing is covered by a cover plate. The top surface of the cover plate is flush with the top surface of the sensor housing. The edge of the cover plate is sealed to the inner wall of the sensor housing.

[0013] The grid-type substrate is coated with a QR code or radio frequency identification label for unique identification.

[0014] A construction method for a geotechnical engineering monitoring system based on 3D printing prefabrication includes the following steps: (1) First, determine the sensor type, quantity, range and deployment density, and establish a three-dimensional model of the grid matrix including sensor housing size, rib routing path, binding hole position, bionic root structure and stress fracture line layer. Select high-strength weather-resistant thermoplastic polymer or fiber-reinforced composite material as 3D printing material, and prefabricate the grid matrix in an integrated manner through 3D printing method. (2) Place the calibrated sensor into the sensor chamber. The sensor leads are led out from the lead hole at the bottom of the sensor chamber. Then inject encapsulating glue into the sensor chamber to form an encapsulating glue layer. The liquid level of the encapsulating glue layer completely submerges the sensor and is lower than the top surface of the sensor chamber. Then install and fix the cover plate to the top of the sensor chamber. After encapsulation, spray a QR code or radio frequency identification label on the grid substrate for unique identification. (3) According to the measurement and layout points, the grid-type base of the packaged sensor is transported and laid to the designated coordinate points. The steel wire rope is used to rigidly tie and fix the grid-type base to the underlying geogrid, geonet, steel mesh or original soil through the prefabricated binding holes. (4) Gather the lead wires of each sensor to the junction point, insert them into the protective pipe in the soil, and lead them to the data acquisition station at the edge of the slope or the shoulder of the road to connect to the data acquisition unit. (5) Spread, level and compact the upper soil layer; (6) After the upper soil layer is filled to the design elevation, all sensors connected to the data acquisition unit are checked for system zero point, parameter configuration and network debugging are performed, and automated long-term monitoring is started. The sensor data is uploaded to the cloud platform in real time for soil and rock health status diagnosis and safety early warning.

[0015] Advantages of this invention: (1) The present invention uses a grid-type substrate with the center of the sensor housing as the center and stress field simulation outward to form a stress contour gradient topological grid. The stress concentration area efficiently transmits the stress changes of the surrounding soil to the sensor sensitive element. The grid opening ratio of the transition gradient area gradually increases, and the spacing of the reinforcing strips changes linearly or exponentially from dense to sparse. The thickness of the reinforcing strips in the transition gradient area is a gradient structure, so as to realize the smooth transition of structural stiffness from the stress concentration area to the outer standard area, avoiding stress concentration caused by sudden stiffness change. The outer standard area adopts a large-diameter grid that matches the mechanical properties of conventional geogrids to ensure that the sensor sensitive element and the commercial grid laid on the periphery have good mechanical matching and deformation coordination.

[0016] (2) At the intersection of some reinforcing bars of the grid-type matrix of the present invention, there is an upward-extending biomimetic root structure, and a barbed anchoring protrusion is provided on the top surface of the reinforcing bar. The main root-like protrusion of the biomimetic root structure is vertically inserted into the soil, providing shear resistance similar to a pin, effectively resisting the horizontal thrust generated by construction compaction. The ring of root-like protrusions of the biomimetic root structure increases the contact area with the soil, so that the soil particles are embedded in the root gaps during compaction, greatly increasing the interface friction angle. The barbed anchoring protrusion can effectively resist the vertical pull-out force. The three work together to form a root-soil composite at the micro interface between the sensor sensitive element and the surrounding soil, thereby ensuring that the sensor sensitive element and the soil deform synchronously when subjected to force, avoiding voiding or relative slippage.

[0017] (3) A stress-breaking line layer is provided on the top surface of the sensor housing of the present invention. When subjected to strong impact loads such as construction rolling, it can preferentially develop controllable micro-cracks or plastic deformations before the sensor. It can effectively dissipate impact energy through an active sacrifice mechanism and achieve physical buffering. At the same time, an encapsulating adhesive layer is injected into the sensor housing, which together with the stress-breaking line layer constitutes a dual buffer system of sacrifice and bearing, which can efficiently absorb the impact energy generated during construction rolling and avoid damage to the sensor's sensitive elements.

[0018] (4) The sensor chamber of the present invention is filled with a sealing adhesive layer and a cover plate is set on the top, which realizes complete physical isolation between the sensor sensitive element and the water, soil, chemical media and coarse particles. It is waterproof, moisture-proof, corrosion-proof and impact-proof. The long-term survival rate of the sensor is increased from less than 60% in the traditional method to more than 95%, which greatly reduces the system maintenance cost.

[0019] (5) The grid-type substrate, sensor cabin, biomimetic root structure, barbed anchoring protrusion and stress breaking line layer of the present invention are prefabricated by 3D printing in one piece, which is fast and the printed structure has high precision.

[0020] (6) The present invention sprays QR codes or radio frequency identification tags on the grid-type substrate for unique identification. During the construction phase, scanning the QR code or radio frequency identification tag on site can directly retrieve the installation drawings and historical test data in the BIM database, which facilitates the traceability of information throughout the entire life cycle. Attached Figure Description

[0021] Figure 1 This is a partial structural schematic diagram of the grid-type substrate of the present invention.

[0022] Figure 2 This is a longitudinal cross-sectional schematic diagram of the sensor of the present invention installed inside the sensor chamber.

[0023] Figure 3 This is a schematic diagram of the biomimetic root system structure of the present invention.

[0024] Figure 4 This is a schematic diagram of the hook-shaped anchoring protrusion of the present invention.

[0025] Reference numerals: 1-Grid-type substrate, 11-Stress concentration area, 12-Transition gradient area, 13-Outer standard area, 2-Sensor housing, 3-Sensor, 4-Encapsulation adhesive layer, 5-Cover plate, 6-Stress breakage line layer, 71-Main root-like protrusion, 72-Firm root-like protrusion, 81-Vertical protrusion, 82-Hook-like protrusion. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] See Figure 1A 3D-printed prefabricated geotechnical engineering monitoring system includes a grid-type substrate 1, sensors 3, and a data acquisition unit. The grid-type substrate 1 is prefabricated by 3D printing. Sensor housings 2 are installed at the intersection of two ribs of the grid-type substrate. The sensor housings 2 have a groove-type structure, and two sensors 3 (a miniature earth pressure gauge and a vibrating wire strain gauge) are respectively installed in their respective sensor housings 2 and connected to the data acquisition unit. The sensor housing 2 of the miniature earth pressure gauge is a circular groove with a diameter of 32 mm and a depth of 15 mm, with a 3 mm diameter lead hole at the center of the bottom. The sensor housing 2 of the vibrating wire strain gauge is 60 mm × 12 mm × 8 mm. The long, narrow groove is mm in diameter. The portion of the grid-type substrate 1 located on the outer periphery of the sensor housing 2 extends outward from the center of the sensor housing 2 and is sequentially divided into a stress concentration zone 11, a transition gradient zone 12, and an outer standard zone 13. The stress concentration zone 11, the transition gradient zone 12, and the outer standard zone 13 are formed by simulating the stress field outward from the center of the sensor housing 2, creating a stress contour gradient topological mesh. The outer standard zone 13 of the stress contour gradient topological mesh is a triangular large-aperture sparse mesh, the transition gradient zone 12 is a triangular medium-aperture transition mesh, and the stress concentration zone 11 is a triangular small-aperture dense mesh. The opening rate of the triangular large-aperture sparse mesh is 60%–70%, and the triangular small-aperture dense mesh… The aperture ratio is 15% to 25%. The dense triangular aperture grid is obtained by dividing the outer ring of the sensor housing 2 with a ring of adjacent large triangular aperture sparse grids (six large triangular aperture sparse grids) by ribs. One large triangular aperture sparse grid is divided into six dense triangular aperture grids by ribs. The aperture ratio of the triangular aperture transition grid is 40% to 50%. The triangular aperture transition grid is located between the outer ring of the dense triangular aperture grid and the inner ring of the large triangular aperture sparse grid. The triangular aperture transition grid is obtained by dividing the outer ring of the dense triangular aperture grid with a ring of adjacent large triangular aperture sparse grids by ribs. One large triangular aperture sparse grid is divided into two triangular aperture transition grids by ribs. Six binding holes are reserved at the four corners and the midpoints of the two long edges of the grid-type substrate 1. The hole diameter is 8 mm and the circumference of the hole is thickened to 8 mm to ensure that it will not crack when the binding force is applied. The grid-type substrate 1 is sprayed with a QR code or radio frequency identification label for unique identification. See Figure 2 After sensor 3 is placed inside sensor housing 2, it is in clearance fit with sensor housing 2. An encapsulating adhesive layer 4 is provided at the gap. The top of sensor housing 2 is covered by a cover plate 5. The top surface of cover plate 5 is flush with the top surface of sensor housing 2. The edge of cover plate 5 is sealed to the inner wall of sensor housing 2. A stress breaking line layer 6 is provided on the top surface of the annular side of sensor housing 2. The stress breaking line layer 6 is a cross-shaped or X-shaped grid of intersecting lines. The thickness of stress breaking line layer 6 is 2-5mm. See Figure 3 and Figure 4 In addition to the rib intersections of the sensor housing 2, the grid-type base 1 also has an upward-extending biomimetic root structure at the other rib intersections. The biomimetic root structure includes a vertically extending main root-like protrusion 71 and a ring of fibrous root-like protrusions 72 distributed around the main root-like protrusion 71. The fibrous root-like protrusions 72 are obliquely placed, and the angle between the bottom of the fibrous root-like protrusions 72 and the bottom of the main root-like protrusion 71 is an acute angle with an angle of 30-60 degrees. The top surface of the ribs of the grid-type base 1 is provided with barbed anchoring protrusions. The barbed anchoring protrusions include a vertical protrusion 81 and multiple barbed protrusions 82 whose inner ends are connected to the top of the vertical protrusion 81. The tops of the main root-like protrusions 71 and the fibrous root-like protrusions 72, as well as the outer ends of the barbed protrusions 82, are all conical pointed structures.

[0028] A construction method for a geotechnical engineering monitoring system based on 3D printing prefabrication includes the following steps: (1) First, determine the type, quantity, range, and layout density of sensor 3. Establish a three-dimensional model of the grid-like matrix, including the dimensions of sensor housing 2, rib routing path, binding hole positions, bionic root structure, and stress fracture line layer 6. Select glass fiber reinforced nylon as the 3D printing material and use an industrial-grade FDM printer to prefabricate the grid-like matrix in one piece using the 3D printing method. Printing parameters: layer height 0.2 mm, nozzle temperature 260℃, heated bed temperature 100℃, and filling density 85%. The printing time for a single piece is about 45 minutes. After printing, the support is removed and the surface is polished. The dimensional tolerance is controlled within ±0.2 mm. (2) In a Class 10,000 cleanroom, place the two calibrated sensors 3 (miniature earth pressure gauge and vibrating wire strain gauge) into the corresponding sensor housing 2. The leads of the sensors 3 are led out from the lead hole at the bottom of the sensor housing 2. Then, inject encapsulating glue (epoxy resin or polyurethane) into the sensor housing 2 to form an encapsulating glue layer. The liquid level of the encapsulating glue layer submerges the top of the sensors 3 by 2 mm. Cure at room temperature for 4 hours. Then, install and fix the cover plate made of polycarbonate material to the top of the sensor housing 2 and seal it by ultrasonic welding. After encapsulation, spray a QR code or radio frequency identification label on the grid substrate for unique identification. (3) After the slope is excavated to the designed horse trail elevation, the slope surface is manually trimmed and galvanized steel wire mesh is laid. The grid-type substrate of the encapsulated sensor 3 is laid on the surface of the galvanized steel wire mesh at a spacing of 1.5m. The grid-type substrate and the galvanized steel wire mesh are tightened and fixed with stainless steel wire. Each binding hole is tied with no less than 3 turns. Adjacent grid-type substrates are connected with nylon cable ties to form a continuous monitoring profile along the longitudinal direction of the horse trail. The installation of a single grid-type substrate takes an average of 3 minutes, which is 15 times more efficient than the traditional burial method (about 45 minutes / point). (4) The lead wires of each sensor 3 are gathered at the junction point and uniformly inserted into the protective pipe (φ25 mm HDPE corrugated pipe) in the soil. They are led to the data acquisition station at the edge of the slope and connected to the multi-channel data acquisition unit. The multi-channel data acquisition unit has a built-in 4G wireless transmission module. The pipe opening of the protective pipe is sealed with fireproof mud, and the pipe body is fixed to the slope protection structure with U-shaped clips every 2 m. (5) Before spraying concrete, an interface agent is sprayed on the surface of the grid matrix to enhance its bonding performance with concrete. Dry spraying is used for construction with a spraying pressure of 0.5 MPa and a thickness of 80 mm per spray. During the spraying process, the reading of the micro earth pressure gauge is monitored in real time. The data shows that the pressure rises steadily without sudden changes, indicating that the grid matrix has not been displaced or damaged. After 24 hours, the rebound material is cleaned up, so that the grid matrix is ​​completely embedded in the slope protection structure. (6) After all sections are installed, all sensors connected to the data acquisition unit are checked for system zero-point verification, parameter configuration and network debugging. The multi-channel data acquisition unit automatically enters continuous monitoring mode, and the sampling frequency is set to 1 time / hour. During periods of rainfall or accelerated deformation, the frequency is automatically increased to 1 time / 10 minutes. The collected data is uploaded to the cloud platform through the IoT card to generate deformation-time curves and cross-verify with the slope radar monitoring data. Since the system has been running for 6 months, the survival rate of sensor 3 is 100%, and the fluctuation pattern of the monitoring data is consistent with the actual working conditions on site.

[0029] During the design phase, the 3D model of the grid-type base and the attributes of the sensors installed on it (type, range, calibration coefficient, installation coordinates) are entered into the BIM model. During the construction phase, scanning the QR code or RFID tag on the grid-type base on-site can directly retrieve the installation drawings and historical test data from the BIM database. During the operation phase, the collected monitoring data is synchronized to the BIM operation and maintenance platform in real time. When the data of a certain measuring point exceeds the limit, the BIM operation and maintenance platform automatically highlights the location and displays the full life cycle file of the sensor, providing a basis for maintenance decisions.

[0030] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A geotechnical engineering monitoring system based on 3D printing prefabrication, characterized in that: It includes a grid-type base, sensors and a data acquisition unit. The grid-type base is pre-formed by 3D printing. Sensor cabins are set at some of the cross nodes of the grid-type base. The sensor cabins have a groove structure. The sensors are set in the sensor cabins and connected to the data acquisition unit. The grid-type substrate located on the outer periphery of the sensor cabin extends outward from the center of the sensor cabin and is sequentially divided into a stress concentration zone, a transition gradient zone, and an outer standard zone. The stress concentration zone, the transition gradient zone, and the outer standard zone are formed by stress field simulation outward from the center of the sensor cabin, resulting in a stress contour gradient topological grid. The outer standard zone of the stress contour gradient topological grid is a large-aperture sparse grid, the transition gradient zone is a medium-aperture transition grid, and the stress concentration zone is a small-aperture dense grid. In addition to the rib intersections of the sensor compartment, the grid-type substrate is equipped with upward-extending biomimetic root structures at all other rib intersections.

2. The geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 1, characterized in that: The large-aperture sparse grid has an opening rate of 60%–70%; the small-aperture dense grid has an opening rate of 15%–25%, and the small-aperture dense grid is obtained by dividing one or more adjacent large-aperture sparse grids on the outer ring of the sensor housing with ribs; the medium-aperture transition grid has an opening rate of 40%–50%, and the medium-aperture transition grid is located between the outer ring of the small-aperture dense grid and the inner ring of the large-aperture sparse grid, and the medium-aperture transition grid is obtained by dividing one or more adjacent large-aperture sparse grids on the outer ring of the small-aperture dense grid with ribs. When the rib length of the large-aperture sparse grid is not less than 50 mm, the small-aperture dense grid is obtained by dividing the adjacent large-aperture sparse grid on the outer ring of the sensor cabin by ribs, and the medium-aperture transition grid is obtained by dividing the adjacent large-aperture sparse grid on the outer ring of the small-aperture dense grid by ribs. When the rib length of the large-aperture sparse grid is less than 50 mm, the small-aperture dense grid is obtained by dividing the outer ring of the sensor housing into two or three adjacent rings of large-aperture sparse grids with ribs. The medium-aperture transition grid is obtained by dividing the outer ring of the small-aperture dense grid into two or three adjacent rings of large-aperture sparse grids with ribs.

3. The geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 1, characterized in that: The thickness of the ribs in the transition zone is a gradually decreasing structure, with the thickness gradually decreasing from the end near the stress concentration zone to the end near the outer standard zone.

4. The geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 1, characterized in that: The biomimetic root structure includes a main root-like protrusion extending vertically upwards, and a ring of fibrous root-like protrusions distributed around the main root-like protrusion. The fibrous root-like protrusions are obliquely placed, and the angle between the bottom end of the fibrous root-like protrusion and the bottom end of the main root-like protrusion is an acute angle with an angle of 30-60 degrees.

5. A geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 4, characterized in that: The top surface of the ribs of the grid-type substrate is provided with barbed anchoring protrusions, which include vertical protrusions and multiple barbed protrusions whose inner ends are connected to the top of the vertical protrusions.

6. A geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 5, characterized in that: The tips of the main root-like protrusions and the fibrous root-like protrusions, as well as the outer ends of the barbed protrusions, are all conical pointed structures.

7. A geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 1, characterized in that: The sensor housing has a ring of stress breakage lines on its top surface on the annular side. The stress breakage lines are cross-shaped or X-shaped grid-like intersecting lines, and the thickness of the stress breakage lines is 2-5 mm.

8. A geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 7, characterized in that: The sensor housing has the same shape as the sensor. After the sensor is placed inside the sensor housing, it is in clearance fit with the sensor housing. An encapsulating adhesive layer is provided at the gap. The top of the sensor housing is covered by a cover plate. The top surface of the cover plate is flush with the top surface of the sensor housing. The edge of the cover plate is sealed to the inner wall of the sensor housing.

9. A geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 8, characterized in that: The grid-type substrate is coated with a QR code or radio frequency identification label for unique identification.

10. A construction method for a geotechnical engineering monitoring system based on 3D printing prefabrication as described in claim 9, characterized in that: Specifically, it includes the following steps: (1) First, determine the sensor type, quantity, range and deployment density, and establish a three-dimensional model of the grid matrix including sensor housing size, rib routing path, binding hole position, bionic root structure and stress fracture line layer. Select high-strength weather-resistant thermoplastic polymer or fiber-reinforced composite material as 3D printing material, and prefabricate the grid matrix in an integrated manner through 3D printing method. (2) Place the calibrated sensor into the sensor chamber. The sensor leads are led out from the lead hole at the bottom of the sensor chamber. Then inject encapsulating glue into the sensor chamber to form an encapsulating glue layer. The liquid level of the encapsulating glue layer completely submerges the sensor and is lower than the top surface of the sensor chamber. Then install and fix the cover plate to the top of the sensor chamber. After encapsulation, spray a QR code or radio frequency identification label on the grid substrate for unique identification. (3) According to the measurement and layout points, the grid-type base of the packaged sensor is transported and laid to the designated coordinate points. The steel wire rope is used to rigidly tie and fix the grid-type base to the underlying geogrid, geonet, steel mesh or original soil through the prefabricated binding holes. (4) Gather the lead wires of each sensor to the junction point, insert them into the protective pipe in the soil, and lead them to the data acquisition station at the edge of the slope or the shoulder of the road to connect to the data acquisition unit. (5) Spread, level and compact the upper soil layer; (6) After the upper soil layer is filled to the design elevation, all sensors connected to the data acquisition unit are checked for system zero point, parameter configuration and network debugging are performed, and automated long-term monitoring is started. The sensor data is uploaded to the cloud platform in real time for soil and rock health status diagnosis and safety early warning.

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